diff --git a/macpal/bin/gen-blueberry-3d.mjs b/macpal/bin/gen-blueberry-3d.mjs
new file mode 100644
index 000000000..1e018b931
--- /dev/null
+++ b/macpal/bin/gen-blueberry-3d.mjs
@@ -0,0 +1,202 @@
+#!/usr/bin/env node
+// macpal/bin/gen-blueberry-3d.mjs — render a 3D blueberry pal as an OBJ.
+//
+// Meshy-6 text-to-3d via the fal.ai queue API (fal-ai/meshy/v6/text-to-3d).
+// Text → fully-textured mesh; we pull the OBJ + GLB + PBR texture PNGs down
+// into macpal/Resources/blueberry-3d/ so MacPal's SceneKit avatar can load it.
+//
+//   node macpal/bin/gen-blueberry-3d.mjs                 # default cute pal
+//   node macpal/bin/gen-blueberry-3d.mjs --lowpoly       # game-asset look
+//   node macpal/bin/gen-blueberry-3d.mjs --prompt "…"    # custom prompt
+//   node macpal/bin/gen-blueberry-3d.mjs --force         # re-render (ignore cache)
+//
+// A submitted job keeps running (and billing) on fal even if this process
+// dies, so the queue handle is persisted beside the output — a rerun RESUMES
+// the in-flight job instead of paying twice. (Same discipline as fal-seedance.)
+
+import { mkdirSync, existsSync, readFileSync, writeFileSync, unlinkSync } from "node:fs";
+import { resolve, dirname } from "node:path";
+import { fileURLToPath } from "node:url";
+import { falKey } from "../../pop/lib/fal-seedance.mjs";
+
+const HERE = dirname(fileURLToPath(import.meta.url));
+const OUT_DIR = resolve(HERE, "../Resources/blueberry-3d");
+const ENDPOINT = "fal-ai/meshy/v6/text-to-3d";
+
+const argv = process.argv.slice(2);
+const has = (f) => argv.includes(f);
+const opt = (f, d) => {
+  const i = argv.indexOf(f);
+  return i >= 0 && argv[i + 1] ? argv[i + 1] : d;
+};
+
+const FORCE = has("--force");
+const LOWPOLY = has("--lowpoly");
+
+// The blueberry pal: one plump, friendly berry with a tiny leaf-crown and a
+// soft dusty bloom — a desktop companion, not a photoreal fruit. Texture
+// prompt carries the surface look so geometry stays clean.
+const PROMPT = opt("--prompt",
+  "A single cute cartoon blueberry character, one plump round berry with a soft " +
+  "matte deep-blue skin and a gentle frosty bloom, a small five-point star calyx " +
+  "crown and one tiny green leaf on top, simple friendly mascot, smooth clean " +
+  "geometry, centered, full body, neutral pose.");
+const TEXTURE_PROMPT =
+  "soft matte blueberry skin, deep indigo-blue with a dusty powder-blue bloom, " +
+  "a subtle pale star calyx, fresh green leaf, gentle hand-illustrated look.";
+
+const input = {
+  prompt: PROMPT,
+  mode: "full",                                  // textured, one shot
+  model_type: LOWPOLY ? "lowpoly" : "standard",
+  topology: "triangle",                          // ModelIO/SceneKit-friendly
+  target_polycount: LOWPOLY ? 8000 : 30000,
+  should_remesh: true,
+  symmetry_mode: "auto",
+  texture_prompt: TEXTURE_PROMPT,
+  enable_pbr: true,
+};
+
+const OBJ_OUT = `${OUT_DIR}/blueberry.obj`;
+const QUEUE_PATH = `${OUT_DIR}/.queue.json`;
+const sleep = (ms) => new Promise((r) => setTimeout(r, ms));
+const log = (...a) => console.log(...a);
+
+if (existsSync(OBJ_OUT) && !FORCE) {
+  log(`✓ cached → ${OBJ_OUT}  (use --force to re-render)`);
+  process.exit(0);
+}
+
+mkdirSync(OUT_DIR, { recursive: true });
+
+let key;
+try {
+  key = falKey();
+} catch (e) {
+  console.error(`✗ ${e.message}`);
+  console.error("  Add FAL_KEY to aesthetic-computer-vault/.devcontainer/envs/devcontainer.env");
+  console.error("  or run with FAL_KEY=… node macpal/bin/gen-blueberry-3d.mjs");
+  process.exit(1);
+}
+const auth = { Authorization: `Key ${key}`, "Content-Type": "application/json" };
+
+log(`▸ blueberry 3D · Meshy-6 text-to-3d · ${input.model_type} · ${input.target_polycount} tris`);
+
+// ── submit (or resume) ───────────────────────────────────────────────────
+let queued = null;
+if (existsSync(QUEUE_PATH)) {
+  queued = JSON.parse(readFileSync(QUEUE_PATH, "utf8"));
+  log(`  ↻ resuming in-flight job from ${QUEUE_PATH.split("/").pop()}`);
+}
+
+const MAX_SUBMIT = 4;
+for (let attempt = 1; !queued && attempt <= MAX_SUBMIT; attempt++) {
+  const res = await fetch(`https://queue.fal.run/${ENDPOINT}`, {
+    method: "POST", headers: auth, body: JSON.stringify(input),
+  });
+  if (res.ok) {
+    queued = await res.json();
+    writeFileSync(QUEUE_PATH, JSON.stringify(queued, null, 2));
+    break;
+  }
+  const err = await res.text();
+  // fal billing-state lag shows up as a spurious 403; retry transients.
+  const transient = res.status === 429 || res.status >= 500 || res.status === 403;
+  if (transient && attempt < MAX_SUBMIT) {
+    log(`  ⚠ submit ${res.status} — retry ${attempt}/${MAX_SUBMIT - 1} in ${5 * attempt}s`);
+    await sleep(5000 * attempt);
+    continue;
+  }
+  console.error(`✗ submit ${res.status}: ${err.slice(0, 300)}`);
+  process.exit(1);
+}
+
+// ── poll (rides out transient network failures) ───────────────────────────
+const MAX_NET_FAILS = 8;
+let netFails = 0;
+const tryFetch = async (...args) => {
+  try {
+    const res = await fetch(...args);
+    netFails = 0;
+    return res;
+  } catch (err) {
+    netFails++;
+    log(`  ⚠ ${err.cause?.code ?? err.message} — retry ${netFails}/${MAX_NET_FAILS}`);
+    if (netFails >= MAX_NET_FAILS) throw err;
+    await sleep(5000 * netFails);
+    return null;
+  }
+};
+
+const t0 = Date.now();
+let status = "";
+let lastTick = 0;
+while (status !== "COMPLETED") {
+  await sleep(4000);
+  const res = await tryFetch(queued.status_url, { headers: auth });
+  if (!res) continue;
+  const body = await res.json();
+  const elapsed = ((Date.now() - t0) / 1000).toFixed(0);
+  if (body.status !== status) {
+    status = body.status;
+    lastTick = Date.now();
+    log(`  ${status.toLowerCase()} · ${elapsed}s`);
+  } else if (Date.now() - lastTick > 12000) {
+    lastTick = Date.now();
+    log(`  ${status.toLowerCase()} · ${elapsed}s`);
+  }
+  if (status === "FAILED" || body.error) {
+    unlinkSync(QUEUE_PATH);
+    console.error(`✗ generation failed: ${JSON.stringify(body).slice(0, 300)}`);
+    process.exit(1);
+  }
+}
+
+let result = null;
+while (!result) {
+  const res = await tryFetch(queued.response_url, { headers: auth });
+  if (res) result = await res.json();
+}
+
+// ── download artifacts ─────────────────────────────────────────────────────
+const urls = result.model_urls || {};
+if (!urls.obj?.url) {
+  console.error(`✗ no OBJ in response: ${JSON.stringify(result).slice(0, 400)}`);
+  process.exit(1);
+}
+
+const download = async (url, dest) => {
+  for (let i = 0; i < MAX_NET_FAILS; i++) {
+    const res = await tryFetch(url);
+    if (!res) continue;
+    if (!res.ok) { console.error(`  ⚠ ${res.status} for ${dest.split("/").pop()}`); return false; }
+    const buf = Buffer.from(await res.arrayBuffer());
+    writeFileSync(dest, buf);
+    log(`  ↓ ${dest.split("/").pop()} · ${(buf.length / 1e6).toFixed(2)}MB`);
+    return true;
+  }
+  return false;
+};
+
+await download(urls.obj.url, OBJ_OUT);
+if (urls.glb?.url) await download(urls.glb.url, `${OUT_DIR}/blueberry.glb`);   // self-contained backup
+if (result.thumbnail?.url) await download(result.thumbnail.url, `${OUT_DIR}/blueberry-thumb.png`);
+
+// PBR texture maps — MacPal applies base_color to the SceneKit material; the
+// rest are kept for future PBR shading.
+const tex = (result.texture_urls && result.texture_urls[0]) || {};
+for (const [kind, file] of Object.entries(tex)) {
+  if (file?.url) await download(file.url, `${OUT_DIR}/blueberry-${kind}.png`);
+}
+
+// Record provenance so a rebuild is reproducible.
+writeFileSync(`${OUT_DIR}/meshy.json`, JSON.stringify({
+  endpoint: ENDPOINT, input, seed: result.seed ?? null,
+  actual_prompt: result.actual_prompt ?? null,
+  model_urls: urls,
+}, null, 2));
+
+try { unlinkSync(QUEUE_PATH); } catch {}
+
+log(`✓ ${((Date.now() - t0) / 1000).toFixed(0)}s → ${OUT_DIR}`);
+log(`  blueberry.obj${urls.glb ? " + .glb" : ""}${tex.base_color ? " + base_color texture" : ""}`);
diff --git a/marketing/campaigns/arxiv-ac-cover/cover-prompt.txt b/marketing/campaigns/arxiv-ac-cover/cover-prompt.txt
new file mode 100644
index 000000000..29f4f2c1e
--- /dev/null
+++ b/marketing/campaigns/arxiv-ac-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a small handheld screen he holds in both hands showing one big blinking block-cursor caret with a bright pink dot beside it — the text prompt as instrument — peering into it, one finger poised to type.
\ No newline at end of file
diff --git a/marketing/campaigns/arxiv-api-cover/cover-prompt.txt b/marketing/campaigns/arxiv-api-cover/cover-prompt.txt
new file mode 100644
index 000000000..2500b2c27
--- /dev/null
+++ b/marketing/campaigns/arxiv-api-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a single big round glowing power button (a boot key) cupped in both hands, his thumb just about to press it, watching it intently.
diff --git a/marketing/campaigns/arxiv-archaeology-cover/cover-prompt.txt b/marketing/campaigns/arxiv-archaeology-cover/cover-prompt.txt
new file mode 100644
index 000000000..4d784d4a4
--- /dev/null
+++ b/marketing/campaigns/arxiv-archaeology-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a 3.5-inch floppy disk he is gently brushing dirt off with a small soft brush, as though he just excavated it from the ground.
\ No newline at end of file
diff --git a/marketing/campaigns/arxiv-calarts-cover/cover-prompt.txt b/marketing/campaigns/arxiv-calarts-cover/cover-prompt.txt
new file mode 100644
index 000000000..cafa37f0d
--- /dev/null
+++ b/marketing/campaigns/arxiv-calarts-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a small blank stretched canvas panel propped on his knee, a pencil in his other hand, hesitating before the empty surface.
diff --git a/marketing/campaigns/arxiv-calarts-news-cover/cover-prompt.txt b/marketing/campaigns/arxiv-calarts-news-cover/cover-prompt.txt
new file mode 100644
index 000000000..225c688cc
--- /dev/null
+++ b/marketing/campaigns/arxiv-calarts-news-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a small architectural scale-model of a long, low, board-formed brutalist concrete slab building held across his lap — a jagged diagonal crack has sheared one chunk free so it floats slightly away from the rest; he studies the break with a quiet frown.
diff --git a/marketing/campaigns/arxiv-comp-strats-cover/cover-prompt.txt b/marketing/campaigns/arxiv-comp-strats-cover/cover-prompt.txt
new file mode 100644
index 000000000..2b7124e92
--- /dev/null
+++ b/marketing/campaigns/arxiv-comp-strats-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a round buckler-sized shield of nested concentric brass-and-copper rings, holding it up on one forearm and studying its layers.
diff --git a/marketing/campaigns/arxiv-complex-cover/cover-prompt.txt b/marketing/campaigns/arxiv-complex-cover/cover-prompt.txt
new file mode 100644
index 000000000..19a83dd4f
--- /dev/null
+++ b/marketing/campaigns/arxiv-complex-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a hand-addressed, stamped and postmarked mail-art parcel with a folded paper score peeking from a torn flap, turning it over to read the postmark.
\ No newline at end of file
diff --git a/marketing/campaigns/arxiv-creative-capital-cover/cover-prompt.txt b/marketing/campaigns/arxiv-creative-capital-cover/cover-prompt.txt
new file mode 100644
index 000000000..780940af7
--- /dev/null
+++ b/marketing/campaigns/arxiv-creative-capital-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: he cradles a single heavy cream paper grant envelope in both hands, flap down and closed with a round blob of deep oxblood sealing wax pressed by a blank intaglio seal — no letters, just the impressed concentric ridge of an unreadable device. he tilts it toward a warm raking light to study the wax relief, thumb resting just below the seal, the deckled edge catching the light, absorbed in the unopened award letter rather than the camera.
diff --git a/marketing/campaigns/arxiv-creative-time-cover/cover-prompt.txt b/marketing/campaigns/arxiv-creative-time-cover/cover-prompt.txt
new file mode 100644
index 000000000..b0981b81b
--- /dev/null
+++ b/marketing/campaigns/arxiv-creative-time-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: he cradles a heavy round-drummed civic carbon-arc searchlight on its low splayed tripod across his lap, leaning over it to study its glowing hot white-gold lens face up close, one hand steadying the weathered riveted cast housing, the thick power cable looping down off the drum past his knee — the single broad beam rising from the lens and fanning into a soft cone that dissolves to nothing above him.
diff --git a/marketing/campaigns/arxiv-dead-ends-cover/cover-prompt.txt b/marketing/campaigns/arxiv-dead-ends-cover/cover-prompt.txt
new file mode 100644
index 000000000..bffa07dff
--- /dev/null
+++ b/marketing/campaigns/arxiv-dead-ends-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a dormant plant bulb cut open to reveal its pale latent core, cradled in his open palm, examined with quiet curiosity.
\ No newline at end of file
diff --git a/marketing/campaigns/arxiv-diversity-cover/cover-prompt.txt b/marketing/campaigns/arxiv-diversity-cover/cover-prompt.txt
new file mode 100644
index 000000000..061607802
--- /dev/null
+++ b/marketing/campaigns/arxiv-diversity-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a worn library card-catalog index card with a brass punch-rod through it, holding it close and reading the pencilled citation.
diff --git a/marketing/campaigns/arxiv-eyebeam-cover/cover-prompt.txt b/marketing/campaigns/arxiv-eyebeam-cover/cover-prompt.txt
new file mode 100644
index 000000000..aa00716af
--- /dev/null
+++ b/marketing/campaigns/arxiv-eyebeam-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: he cradles a single round enameled residency lapel badge in both hands, tilting it toward the window light to study it — the badge two inches across with a polished brass rim and a matte-black face, at its centre a glowing soft-cyan pixel-burst of eight short rays around one bright pixel ringed by concentric printed-circuit traces like an eye-iris, a small enamel chip missing from the lower-left rim exposing the brass beneath, no lettering anywhere on it, held close and angled as he turns it in the light.
diff --git a/marketing/campaigns/arxiv-folk-songs-cover/cover-prompt.txt b/marketing/campaigns/arxiv-folk-songs-cover/cover-prompt.txt
new file mode 100644
index 000000000..b558b6332
--- /dev/null
+++ b/marketing/campaigns/arxiv-folk-songs-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a single chunky QWERTY laptop keycap engraved with one bold eighth note, pressing it with one finger as if it sounds.
\ No newline at end of file
diff --git a/marketing/campaigns/arxiv-fraserin-cover/cover-prompt.txt b/marketing/campaigns/arxiv-fraserin-cover/cover-prompt.txt
new file mode 100644
index 000000000..abeed1f03
--- /dev/null
+++ b/marketing/campaigns/arxiv-fraserin-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: he cradles a heavy rectangular cast-brass institutional donor-wall plaque across his lap with both hands, tilting it up into a low raking light to study the engraved face — a warm patina'd brass tablet with a softly bevelled edge, two small screws at the top corners, and a stack of eight or nine slim ruled horizontal name-bands of engraved donor names rendered as illegible scribble-gestalt, his thumb resting along the taller engraved dedication line at the top.
diff --git a/marketing/campaigns/arxiv-futures-cover/cover-prompt.txt b/marketing/campaigns/arxiv-futures-cover/cover-prompt.txt
new file mode 100644
index 000000000..575ca342d
--- /dev/null
+++ b/marketing/campaigns/arxiv-futures-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a rescued beige surplus business laptop open on his lap, its screen freshly booted into the colorful AC interface, looking quietly pleased.
\ No newline at end of file
diff --git a/marketing/campaigns/arxiv-goodiepal-cover/cover-prompt.txt b/marketing/campaigns/arxiv-goodiepal-cover/cover-prompt.txt
new file mode 100644
index 000000000..c085b8a21
--- /dev/null
+++ b/marketing/campaigns/arxiv-goodiepal-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a worn cardboard-bound radical-music score book held shut by a thick rubber band, holding it in his lap.
diff --git a/marketing/campaigns/arxiv-hand-and-loop-cover/cover-prompt.txt b/marketing/campaigns/arxiv-hand-and-loop-cover/cover-prompt.txt
new file mode 100644
index 000000000..e20698f89
--- /dev/null
+++ b/marketing/campaigns/arxiv-hand-and-loop-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: nothing held — instead one of his hands is raised and a trailing drawn line-cord uncoils from his fingertips and curls back into a closed, self-returning loop in the air beside him.
diff --git a/marketing/campaigns/arxiv-hathitrust-cover/cover-prompt.txt b/marketing/campaigns/arxiv-hathitrust-cover/cover-prompt.txt
new file mode 100644
index 000000000..89cc25a1a
--- /dev/null
+++ b/marketing/campaigns/arxiv-hathitrust-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: he cradles a single thick oxblood-red leather-bound book upright in his lap, tilting its spine toward himself to study it — the spine faces up under his gaze, oxblood leather with three gilt horizontal bands top and bottom and a dignified elephant head stamped large in gold leaf in profile at its centre, trunk curling upward; one hand steadies the spine while the other rests open across the cover, no readable letters or title text anywhere on the book.
diff --git a/marketing/campaigns/arxiv-heavy-manners-library-cover/cover-prompt.txt b/marketing/campaigns/arxiv-heavy-manners-library-cover/cover-prompt.txt
new file mode 100644
index 000000000..0965e60cc
--- /dev/null
+++ b/marketing/campaigns/arxiv-heavy-manners-library-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: he cradles in his lap a hand-stencilled 7-inch dub-reggae record sleeve of age-yellowed cardboard — deep brick-red spray-paint stencil shapes across its top reading as a band name but not as real words, the matte black vinyl peeking half an inch out of the open top — and with one hand he tilts the sleeve up toward the light to study a mismatched manila library checkout pocket glued to its lower corner, a date-due slip half-tucked inside, his head bowed over it absorbed.
\ No newline at end of file
diff --git a/marketing/campaigns/arxiv-holden-cover/cover-prompt.txt b/marketing/campaigns/arxiv-holden-cover/cover-prompt.txt
new file mode 100644
index 000000000..8f25fee79
--- /dev/null
+++ b/marketing/campaigns/arxiv-holden-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a hand-thrown salt-glazed earthenware potter's jug incised with a divided monochord string-line around its belly, cradled in both hands.
\ No newline at end of file
diff --git a/marketing/campaigns/arxiv-identity-cover/cover-prompt.txt b/marketing/campaigns/arxiv-identity-cover/cover-prompt.txt
new file mode 100644
index 000000000..ad74b7cdd
--- /dev/null
+++ b/marketing/campaigns/arxiv-identity-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: an old brass skeleton key whose bow is shaped like an @ symbol and whose bit is cut like a cryptographic key, held up and turned in the light.
diff --git a/marketing/campaigns/arxiv-internet-archive-cover/cover-prompt.txt b/marketing/campaigns/arxiv-internet-archive-cover/cover-prompt.txt
new file mode 100644
index 000000000..7c8dd94d3
--- /dev/null
+++ b/marketing/campaigns/arxiv-internet-archive-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: he cradles a small architectural scale model of a Greek-revival temple in his lap, both hands steadying it — four tall fluted columns supporting a triangular pediment in warm sandstone tones, a single round oculus at the centre of the pediment — tilting it slightly toward himself to study the columns, absorbed in the little building, not looking up.
diff --git a/marketing/campaigns/arxiv-kidlisp-cards-cover/cover-prompt.txt b/marketing/campaigns/arxiv-kidlisp-cards-cover/cover-prompt.txt
new file mode 100644
index 000000000..fdab127f9
--- /dev/null
+++ b/marketing/campaigns/arxiv-kidlisp-cards-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a printed index card bearing one chunky pixel-art starburst above two lines of monospace code, held up and read.
diff --git a/marketing/campaigns/arxiv-kidlisp-cover/cover-prompt.txt b/marketing/campaigns/arxiv-kidlisp-cover/cover-prompt.txt
new file mode 100644
index 000000000..bf908e6c8
--- /dev/null
+++ b/marketing/campaigns/arxiv-kidlisp-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a single oversized open Lisp parenthesis, like a glowing bracket-wand, from whose tip bursts a small spray of chunky rainbow pixel-seeds, held out before him.
\ No newline at end of file
diff --git a/marketing/campaigns/arxiv-kidlisp-reference-cover/cover-prompt.txt b/marketing/campaigns/arxiv-kidlisp-reference-cover/cover-prompt.txt
new file mode 100644
index 000000000..75b494b0a
--- /dev/null
+++ b/marketing/campaigns/arxiv-kidlisp-reference-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a fat pair of Lisp parentheses cupped in both hands cradling one glowing pixel-seed spark between them.
diff --git a/marketing/campaigns/arxiv-latency-cover/cover-prompt.txt b/marketing/campaigns/arxiv-latency-cover/cover-prompt.txt
new file mode 100644
index 000000000..f5daeba50
--- /dev/null
+++ b/marketing/campaigns/arxiv-latency-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a single keyboard keycap with a tiny speaker cone set into its hollow underside, held up to his ear, listening.
diff --git a/marketing/campaigns/arxiv-machine-project-cover/cover-prompt.txt b/marketing/campaigns/arxiv-machine-project-cover/cover-prompt.txt
new file mode 100644
index 000000000..86d30b5e0
--- /dev/null
+++ b/marketing/campaigns/arxiv-machine-project-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: an old low 1930s wood-framed shop window propped on his knees, warm cream amateur hand-painted lettering-shapes across its glass; he holds it up and peers through it.
diff --git a/marketing/campaigns/arxiv-mellon-cover/cover-prompt.txt b/marketing/campaigns/arxiv-mellon-cover/cover-prompt.txt
new file mode 100644
index 000000000..9f18880eb
--- /dev/null
+++ b/marketing/campaigns/arxiv-mellon-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a round ornate aged-brass foundation seal — a raised laurel-leaf border ringing a small classical lyre in relief — cradled in both hands and tilted to the light.
diff --git a/marketing/campaigns/arxiv-microvision-cover/cover-prompt.txt b/marketing/campaigns/arxiv-microvision-cover/cover-prompt.txt
new file mode 100644
index 000000000..8ff9ab033
--- /dev/null
+++ b/marketing/campaigns/arxiv-microvision-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a tiny silver MEMS scanning micromirror, a fingernail-sized polished-silicon square in a beige ceramic chip carrier with fine gold bond-wires, pinched between thumb and forefinger and held up to the light.
diff --git a/marketing/campaigns/arxiv-network-audit-cover/cover-prompt.txt b/marketing/campaigns/arxiv-network-audit-cover/cover-prompt.txt
new file mode 100644
index 000000000..651938af3
--- /dev/null
+++ b/marketing/campaigns/arxiv-network-audit-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a blank brass identity nameplate engraved with a single lowercase @ symbol, held in both hands and examined.
diff --git a/marketing/campaigns/arxiv-new-inc-cover/cover-prompt.txt b/marketing/campaigns/arxiv-new-inc-cover/cover-prompt.txt
new file mode 100644
index 000000000..e14433ca1
--- /dev/null
+++ b/marketing/campaigns/arxiv-new-inc-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a hexagonal bone-white enamel pin with a thin gold border, two small crossed slate-blue implements inside it (a soldering iron with an orange bead of light at its tip, and a fine paintbrush), held up between thumb and forefinger.
diff --git a/marketing/campaigns/arxiv-nom-cover/cover-prompt.txt b/marketing/campaigns/arxiv-nom-cover/cover-prompt.txt
new file mode 100644
index 000000000..be49a4b7b
--- /dev/null
+++ b/marketing/campaigns/arxiv-nom-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a small bug-eyed green muncher creature (mostly one enormous grinning open mouth) perched on his open palm, chomping a chunky pixel number tile.
diff --git a/marketing/campaigns/arxiv-notepat-cover/cover-prompt.txt b/marketing/campaigns/arxiv-notepat-cover/cover-prompt.txt
new file mode 100644
index 000000000..eaff24774
--- /dev/null
+++ b/marketing/campaigns/arxiv-notepat-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a single oversized keycap that is also a piano key, held up and pressed with one finger as if sounding a single note.
diff --git a/marketing/campaigns/arxiv-open-schools-cover/cover-prompt.txt b/marketing/campaigns/arxiv-open-schools-cover/cover-prompt.txt
new file mode 100644
index 000000000..27129a68b
--- /dev/null
+++ b/marketing/campaigns/arxiv-open-schools-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a school Chromebook laptop, shut and wrapped in a padlocked chain, held on his lap as he frowns at the lock.
diff --git a/marketing/campaigns/arxiv-penrose-cover/cover-prompt.txt b/marketing/campaigns/arxiv-penrose-cover/cover-prompt.txt
new file mode 100644
index 000000000..f35dd6a09
--- /dev/null
+++ b/marketing/campaigns/arxiv-penrose-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a small contraption of a single graph-node bead held in equilibrium by three taut coiled springs, held up and gently tugged.
\ No newline at end of file
diff --git a/marketing/campaigns/arxiv-pieces-cover/cover-prompt.txt b/marketing/campaigns/arxiv-pieces-cover/cover-prompt.txt
new file mode 100644
index 000000000..f3e353309
--- /dev/null
+++ b/marketing/campaigns/arxiv-pieces-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a single handwritten musical score sheet, held up in both hands and read.
diff --git a/marketing/campaigns/arxiv-pioneer-works-cover/cover-prompt.txt b/marketing/campaigns/arxiv-pioneer-works-cover/cover-prompt.txt
new file mode 100644
index 000000000..5f05c266a
--- /dev/null
+++ b/marketing/campaigns/arxiv-pioneer-works-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a salvaged red-brick arched foundry window with a smooth uncarved stone keystone, Flemish-bond brick, held on his lap as he looks it over.
diff --git a/marketing/campaigns/arxiv-plork-cover/cover-prompt.txt b/marketing/campaigns/arxiv-plork-cover/cover-prompt.txt
new file mode 100644
index 000000000..5601579b2
--- /dev/null
+++ b/marketing/campaigns/arxiv-plork-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a hand-built hemispherical geodesic-dome loudspeaker whose shell is faintly mapped as planet Earth, cradled in his lap like an instrument.
diff --git a/marketing/campaigns/arxiv-recurse-cover/cover-prompt.txt b/marketing/campaigns/arxiv-recurse-cover/cover-prompt.txt
new file mode 100644
index 000000000..ef75f7724
--- /dev/null
+++ b/marketing/campaigns/arxiv-recurse-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: an off-white index card hand-typed on a manual typewriter, held up and read — on it a pure ASCII drawing of nested squares (a square inside a square inside a square) made from hyphens, pipes and pluses.
diff --git a/marketing/campaigns/arxiv-rhizome-cover/cover-prompt.txt b/marketing/campaigns/arxiv-rhizome-cover/cover-prompt.txt
new file mode 100644
index 000000000..af500de22
--- /dev/null
+++ b/marketing/campaigns/arxiv-rhizome-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a single beige 3.5-inch floppy disk, its white label hand-doodled in looping cyan ballpoint, held up and turned over in his fingers.
diff --git a/marketing/campaigns/arxiv-sampling-cover/cover-prompt.txt b/marketing/campaigns/arxiv-sampling-cover/cover-prompt.txt
new file mode 100644
index 000000000..26f0fdc9b
--- /dev/null
+++ b/marketing/campaigns/arxiv-sampling-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a small square pixel-painting whose chunky colored pixels encode a recorded sound as a waveform image, held up and studied.
\ No newline at end of file
diff --git a/marketing/campaigns/arxiv-score-analysis-cover/cover-prompt.txt b/marketing/campaigns/arxiv-score-analysis-cover/cover-prompt.txt
new file mode 100644
index 000000000..9ac511676
--- /dev/null
+++ b/marketing/campaigns/arxiv-score-analysis-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a single music score-page on a small folding conductor's stand before him, its staff lines doubling as the ruled lines of a README, which he points at.
\ No newline at end of file
diff --git a/marketing/campaigns/arxiv-sfpc-cover/cover-prompt.txt b/marketing/campaigns/arxiv-sfpc-cover/cover-prompt.txt
new file mode 100644
index 000000000..1f928b7c1
--- /dev/null
+++ b/marketing/campaigns/arxiv-sfpc-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a small black pine-framed classroom chalkboard on his lap with a loose white-chalk LED-and-resistor schematic sketched across it (battery, resistor zigzag, LED triangle, closed loop); he points at it.
diff --git a/marketing/campaigns/arxiv-studio-museum-cover/cover-prompt.txt b/marketing/campaigns/arxiv-studio-museum-cover/cover-prompt.txt
new file mode 100644
index 000000000..2b72a0101
--- /dev/null
+++ b/marketing/campaigns/arxiv-studio-museum-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a small architectural model of an inverted brownstone stoop — three reddish-brown stone steps with a slim wrought-iron railing, the steps reading downward like an invitation — cradled in both hands.
diff --git a/marketing/campaigns/arxiv-sustainability-cover/cover-prompt.txt b/marketing/campaigns/arxiv-sustainability-cover/cover-prompt.txt
new file mode 100644
index 000000000..c250a775e
--- /dev/null
+++ b/marketing/campaigns/arxiv-sustainability-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a nearly-empty glass tip jar with a single lone coin in the bottom, held up and peered into with a deadpan look.
diff --git a/marketing/campaigns/arxiv-the-kitchen-cover/cover-prompt.txt b/marketing/campaigns/arxiv-the-kitchen-cover/cover-prompt.txt
new file mode 100644
index 000000000..a73387cc4
--- /dev/null
+++ b/marketing/campaigns/arxiv-the-kitchen-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a vintage Sony Portapak: the boxy hand-held reel-to-reel camera-head held up toward his eye, the half-inch tape deck resting on his lap, a coiled umbilical cable looping between them.
diff --git a/marketing/campaigns/arxiv-ucla-arts-cover/cover-prompt.txt b/marketing/campaigns/arxiv-ucla-arts-cover/cover-prompt.txt
new file mode 100644
index 000000000..bb263ab96
--- /dev/null
+++ b/marketing/campaigns/arxiv-ucla-arts-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a small white architectural model of a modernist Meier-idiom university art building, held on his lap and regarded.
diff --git a/marketing/campaigns/arxiv-url-tradition-cover/cover-prompt.txt b/marketing/campaigns/arxiv-url-tradition-cover/cover-prompt.txt
new file mode 100644
index 000000000..9be3be95d
--- /dev/null
+++ b/marketing/campaigns/arxiv-url-tradition-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a long drawn browser address-bar (a URL field) with a typed path and a blinking cursor, held taut between his hands like a ribbon of text.
diff --git a/marketing/campaigns/arxiv-whistlegraph-cover/cover-prompt.txt b/marketing/campaigns/arxiv-whistlegraph-cover/cover-prompt.txt
new file mode 100644
index 000000000..84f757f91
--- /dev/null
+++ b/marketing/campaigns/arxiv-whistlegraph-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a butterfly drawn as one single continuous marker line — a whistlegraph graphic score — which he is mid-drawing in the air with a marker, lips pursed as if whistling it.
\ No newline at end of file
diff --git a/marketing/campaigns/essay-may-26-cover/cover-prompt.txt b/marketing/campaigns/essay-may-26-cover/cover-prompt.txt
new file mode 100644
index 000000000..6edcd068f
--- /dev/null
+++ b/marketing/campaigns/essay-may-26-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: a single soft cumulus cloud cupped gently in both hands, regarded with a faint deadpan calm.
diff --git a/marketing/campaigns/keymaps-cover/cover-prompt.txt b/marketing/campaigns/keymaps-cover/cover-prompt.txt
new file mode 100644
index 000000000..8f456d5bb
--- /dev/null
+++ b/marketing/campaigns/keymaps-cover/cover-prompt.txt
@@ -0,0 +1,125 @@
+one of the reference images is a finished colored-pencil drawing of
+the man singing on a chair with the laptop draped over his knees —
+that is the COMPOSITION reference. recreate that drawing faithfully:
+same man, same pose, same chair, same flipped-down laptop, same
+swirling notes, same style — changing ONLY the laptop's screen
+contents, which must now match the colorful tile interface
+screenshot among the references, tile for tile.
+
+A photograph of a colored-pencil and gouache drawing on pure white
+paper, square. Confident hatching and striping build tone. Tapered
+pencil edges. Optical mixing in patterned surfaces. Visible paper
+grain. Print-work sensibility. Diegetic light only — never overlay
+glow. Candid iphone-snapshot tone — NOT cinematic, NOT an
+advertisement hero pose. The figure never looks at the camera. The
+drawing dissolves softly to pure white paper at the edges with no
+hard frame, no border, no caption, no wordmark, no title lettering
+anywhere on the page.
+
+the scene: a tiny acoustic concert with an audience of nobody — one
+man alone, sitting on a simple wooden chair in white space, no room,
+no floor line beyond a soft hatched shadow under the chair legs,
+performing his heart out. the FULL FIGURE is in frame as one
+complete gestalt: head, both arms, the whole chair, both legs, and
+both shoes entirely inside the picture, nothing cropped by any edge
+— the man-chair-laptop unit floats as a single drawn object in the
+middle of the white paper with generous white margin on all four
+sides, like a figure study centered on the page. it's the man in the reference photos —
+recognizably him, medium-length brown hair tucked behind one ear. he
+wears his usual outfit: a plain solid button-down shirt, mostly
+buttoned but relaxed, top button undone, no graphic print — a
+bright-yellow torpedo-shaped fountain pen with a gold clip tucked in
+the chest pocket, and a small yellow embroidered bear-shaped badge
+stitched on the chest, part of the shirt itself.
+
+his instrument, on his lap: the exact laptop shown in the laptop
+reference image — a black Lenovo ThinkPad Yoga 11e, the small
+convertible whose lid rotates a full 360 degrees through the
+watchband hinge, as the reference's ghosted lid positions show. the base sits flat on
+his thighs, keyboard facing up toward him; the lid is folded ALL
+the way around and DOWN — rotated past 180 degrees at the hinge on
+the front edge of the base — so the screen panel hangs down over
+the front of his knees, like a little marquee draped from his lap,
+with the SCREEN facing OUT at the audience — at the camera. the
+keyboard stays fully visible from the front-above, his hands on it;
+the screen panel hangs vertically below the keyboard plane, in
+front of his shins, facing us. nothing stands up behind the
+keyboard — the lid is down over the knees, not raised. matte black,
+chunky student-laptop proportions, and SMALL — an 11-to-12-inch
+machine that looks compact on a grown man's lap, noticeably narrower
+than his knees are apart, almost toylike — never a wide 15-inch
+slab.
+
+the screen, fully visible to the camera, shows the interface from
+the tile-interface reference screenshot, reproduced faithfully —
+and because the flipped-back panel does not rotate its picture, the
+interface appears UPSIDE DOWN to the audience, exactly as the
+reference screenshot is oriented. the tile grid arithmetic is
+exact and non-negotiable: TWO side-by-side banks of note tiles,
+one bank per octave, and each bank is EXACTLY 4 TILES WIDE and
+3 TILES TALL — a full chromatic octave of 12 tiles per bank laid
+out in reading order, 24 tiles total, with a narrow gap between
+the two banks. each tile is a wide flat rectangle of a different
+candy color, every tile in a bank the same size, packed edge to
+edge in a clean 4-column by 3-row lattice like a sheet of postage
+stamps. a thin vertical slider strip hugs the OUTER edge of each
+bank — one at the far left of the left bank, one at the far right
+of the right bank — the per-octave volume faders. count the
+columns: four in the left bank, four in the right bank. never cut
+off, crop, or merge a column or row; both banks fit on the screen
+whole, all edges visible. this geometry is the entire concept of
+the image — the two banks are the instrument's two octaves, one
+for each of his two hands: a drawing that loses a column has
+broken the instrument, like drawing a piano with six white keys
+per octave. the audience must be able to read the two complete
+4-by-3 banks at a glance. directly below the banks (in the
+audience's upside-down view) runs the thin pale waveform strip,
+and further down the remaining interface rows sit smaller and
+fainter. beyond the tile blocks: the thin waveform strip and
+the small slider rows, as in the screenshot. render it all as flat
+hand-hatched color fields matching the screenshot's layout and
+palette; small note labels may stay illegible. the interface is
+alive, not inert: in the reference, three tiles are PRESSED
+mid-chord — bright saturated red, blue, and yellow against their
+pastel neighbors — keep those pressed tiles lit exactly as the
+screenshot shows them.
+
+his pose: both hands on the keyboard like a pianist — left hand on
+its half, right hand on its half, fingers on the letter keys, hands
+still — and he is SINGING HIS HEART OUT, pure joy: chin lifted high,
+eyes scrunched shut with happiness, mouth wide open mid-note, big
+beaming grin shaping the note, eyebrows up, head tipped back a
+little, shoulders lifted like he's mid-bounce, one heel raised off
+the ground tapping time — the unguarded face of someone having the
+best time of his life playing a song he loves.
+
+the music: pencil-drawn musical note glyphs — quarter notes, eighth
+notes, beamed pairs, one sharp sign — pour from his open mouth and
+from the laptop and SWIRL around the whole figure in space: a
+volumetric helix of notes that circles behind his shoulders, in
+front of his knees, around the chair, near and far — near notes
+drawn larger and darker, far notes smaller and fainter, overlapping
+the figure where the spiral passes in front of him — so the swirl
+reads as a three-dimensional current of music wrapping the
+man-chair-laptop unit, thinning and dissolving into the white paper
+before reaching any edge. simple hand-drawn glyphs in dark pencil
+with hints of the screen's candy colors, never a printed music-font
+look.
+
+palette: white paper as the ground; matte black laptop as the
+biggest dark mass; the candy-colored tile grid on the screen as the
+brightest passage; muted earth tone on the shirt; warm brown hair;
+pale wooden chair; dark pencil note glyphs. hand-drawn, hatched,
+print-comic restraint.
+
+avoid: a third panel — the laptop is exactly TWO slabs joined at
+ONE hinge, base and lid, nothing more; any screen standing up
+behind the keyboard — the lid is folded down in front of the
+keyboard, so behind the keyboard there is only him; photoreal
+rendering; cinematic glow; any css-overlay light; motion blur of
+any kind; soft-focus haze — the drawing is crisp throughout,
+confident pencil lines from foreground to back; extra furniture,
+desks, cables, mugs, microphones, or props; any second screen;
+screens on the lid back or base; any readable institutional
+lettering; tank tops or invented garments; the chartreuse green
+laptop — this is the black ThinkPad scene.
diff --git a/marketing/campaigns/keymaps-cover/refs-unused/ac-native-notepat-original.png b/marketing/campaigns/keymaps-cover/refs-unused/ac-native-notepat-original.png
new file mode 100644
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diff --git a/marketing/campaigns/os-cover/cover-prompt.txt b/marketing/campaigns/os-cover/cover-prompt.txt
new file mode 100644
index 000000000..d5c1b1628
--- /dev/null
+++ b/marketing/campaigns/os-cover/cover-prompt.txt
@@ -0,0 +1,7 @@
+A photograph of a colored-pencil and gouache drawing on pure white paper, square. Confident hatching and striping build tone. Tapered pencil edges. Optical mixing in patterned surfaces. Visible paper grain. Print-work sensibility. Diegetic light only — never overlay glow. Candid iphone-snapshot tone — NOT cinematic, NOT an advertisement hero pose. The figure never looks at the camera. The drawing dissolves softly to pure white paper at the edges with no hard frame, no border, no caption, no wordmark, no title lettering anywhere on the page.
+
+the scene: one man alone, sitting on a simple wooden chair in white space — no room, no floor line beyond a soft hatched shadow under the chair legs. the FULL FIGURE is in frame as one complete gestalt: head, both arms, the whole chair, both legs, and both shoes entirely inside the picture, nothing cropped by any edge — the man-and-chair unit floats as a single drawn object in the middle of the white paper with generous white margin on all four sides, like a figure study centered on the page.
+
+it's the man in the reference photos — recognizably him, medium-length brown hair tucked behind one ear. he wears his usual outfit: a plain solid button-down shirt, mostly buttoned but relaxed, top button undone, no graphic print — a bright-yellow torpedo-shaped fountain pen with a gold clip tucked in the chest pocket, and a small yellow embroidered bear-shaped badge stitched on the chest, part of the shirt itself.
+
+his prop: he holds a single rugged USB flash drive up to the light between thumb and forefinger, tilting it and studying it with a faint deadpan half-grin — as though the entire bare-metal computer operating system fits on that one small stick, an amber boot-LED glowing in its side. the gesture is quiet and absorbed, a man marveling at a tiny object, not presenting it to a camera.
diff --git a/papers/arxiv-kidlisp/kidlisp.blg b/papers/arxiv-kidlisp/kidlisp.blg
index 0cb52690b..5e7e3f3ff 100644
--- a/papers/arxiv-kidlisp/kidlisp.blg
+++ b/papers/arxiv-kidlisp/kidlisp.blg
@@ -1,4 +1,4 @@
-This is BibTeX, Version 0.99d (TeX Live 2023)
+This is BibTeX, Version 0.99e (TeX Live 2026)
 Capacity: max_strings=200000, hash_size=200000, hash_prime=170003
 The top-level auxiliary file: kidlisp.aux
 The style file: plainnat.bst
diff --git a/papers/arxiv-score-analysis/figures/pals.pdf b/papers/arxiv-score-analysis/figures/pals.pdf
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diff --git a/papers/corporate-graphics-platter/README.md b/papers/corporate-graphics-platter/README.md
new file mode 100644
index 000000000..dbd80dcc4
--- /dev/null
+++ b/papers/corporate-graphics-platter/README.md
@@ -0,0 +1,48 @@
+# Corporate Graphics — platter
+
+A reference library of historic bank, corporate, seal, and privacy/identity
+marks, collected to inform the **REGARDE** logo work (the consent gate —
+*"nothing about you, without you."*). The brief is *trust*, and this is the
+lineage a trust/consent mark should sit inside: notary seals, institutional
+monograms, and the modernist abstract marks that made organizations feel solid.
+
+**66 marks** fetched from Wikimedia Commons, organized into four sections with
+per-mark provenance (designer, year, motif, aesthetic register, why-it-matters).
+The whole point is **aesthetic range** — to break out of a single flat-vector
+default and find genuinely different ways in.
+
+## Sections
+
+| Section | Marks | What it teaches | Sheet |
+|---|---|---|---|
+| [Banks & Finance](banks-finance/manifest.md) | 16 | how money signals trust — heraldic animals, swiss slashes, vault geometry | `banks-finance/_sheet-banks-finance.png` |
+| [Modernist Designer Canon](modernist-canon/manifest.md) | 19 | abstract geometry = institutional solidity (Rand, Chermayeff & Geismar, Bass, Vignelli) | `modernist-canon/_sheet-modernist-canon.png` |
+| [Seals · Monograms · Notary](seals-monograms/manifest.md) | 15 | the verification grammar closest to a consent *receipt* — engraved seals, certification roundels, authority monograms | `seals-monograms/_sheet-seals-monograms.png` |
+| [Surveillance · Security · Consent](surveillance-consent/manifest.md) | 16 | the category REGARDE actually competes in — and its clichés to avoid | `surveillance-consent/_sheet-surveillance-consent.png` |
+
+## How this informs REGARDE
+
+Four distinct registers to pull the logo toward, instead of the flat-green-on-cream
+default:
+
+1. **Engraved seal / intaglio** — the Great Seal's all-seeing eye, Treasury's
+   scales (1789), the Penny Black. A consent *receipt* is literally a seal; the
+   anti-surveillance pitch can *reclaim* the all-seeing-eye as a **returned gaze**.
+2. **Swiss constructivist** — Stankowski's Deutsche Bank slash, NatWest's cubes:
+   one geometric idea, growth held in a stable frame.
+3. **Heraldic-flattened** — Lloyds' horse, Barclays' eagle, UBS's keys: a guardian
+   emblem modernized to flat. A gate-keeper animal is on-brief.
+4. **Negative-space / figure-ground** — FedEx's arrow, PBS's faces: the meaning
+   hidden in the counter. REGARDE's "you held inside the gate" wants exactly this.
+
+The surveillance-consent section maps the **clichés to diverge from**: padlocks,
+blue shields, green checks, fingerprints. REGARDE's opening is to look *unlike*
+a security vendor — warmer, more civic, a seal not a shield.
+
+## Provenance & use
+
+These are third-party trademarks, collected from Wikimedia Commons under their
+respective licenses **for design research / moodboard reference only** — not for
+redistribution or any REGARDE deliverable. Each `manifest.md` lists the source.
+Tooling: `fetch-logos.mjs` (collect), `lib-data.mjs` (captions), `finalize.mjs`
+(manifests + contact sheets).
diff --git a/papers/corporate-graphics-platter/banks-finance/_sheet-banks-finance.png b/papers/corporate-graphics-platter/banks-finance/_sheet-banks-finance.png
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new file mode 100644
index 000000000..fcad98673
--- /dev/null
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diff --git a/papers/corporate-graphics-platter/banks-finance/manifest.md b/papers/corporate-graphics-platter/banks-finance/manifest.md
new file mode 100644
index 000000000..f01f9a028
--- /dev/null
+++ b/papers/corporate-graphics-platter/banks-finance/manifest.md
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+# Banks & Finance
+
+16 marks · Wikimedia Commons reference library for the REGARDE logo work.
+
+| mark | by | year | motif | aesthetic register | why it matters |
+|---|---|---|---|---|---|
+| **American Express** | — | 1970s | the Blue Box | corporate trust blue | the box as security / containment |
+| **Bank of America** | Lippincott | 1998 | abstract flag stripes | patriotic geometric | flag fragment = nation-scale trust |
+| **Barclays** | — | — | spread eagle | heraldic, flattened | centuries-old eagle modernized to flat |
+| **BBVA** | Landor | 2019 | geometric wordmark | contemporary sans | softened modern banking |
+| **Chase** | Chermayeff & Geismar | 1960 | octagon / vault aperture | mid-century geometric | first major US abstract bank mark — negative center reads as a vault |
+| **Citi** | Pentagram (Paula Scher) | 1998 | red arc over wordmark | wordmark + gesture | the arc as umbrella/protection |
+| **Deutsche Bank** | Anton Stankowski | 1974 | slash in a square | swiss constructivist | growth (diagonal) held in a stable frame |
+| **HSBC** | Henry Steiner | 1983 | hexagon from St Andrew's cross | heraldic→geometric | from a 19th-c house flag; hexagon = containment |
+| **ING** | — | — | lion | dutch heraldic, flat | heritage animal flattened to friendly |
+| **Lloyds Bank** | — | 1884 | black horse | inherited shop-sign heraldry | a goldsmith's shop sign become a brand |
+| **Mastercard** | Pentagram (2016) | 1968 | two overlapping circles | gestalt overlap | intersection = exchange |
+| **Monte dei Paschi di Siena** | — | — | heraldic shield | italian heraldry | the world's oldest surviving bank's arms |
+| **NatWest** | — | 1968 | three cubes / arrows | swiss geometric | money moving three directions |
+| **Santander** | — | — | flame / spark | contemporary flat | warmth + energy in red |
+| **UBS** | — | — | three keys | heraldic | keys = confidence, security, discretion |
+| **Wells Fargo** | — | — | stagecoach | americana heritage | trust signalled through history |
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diff --git a/papers/corporate-graphics-platter/banks-finance/wells-fargo-stagecoach.svg b/papers/corporate-graphics-platter/banks-finance/wells-fargo-stagecoach.svg
new file mode 100644
index 000000000..cb3e09ce1
--- /dev/null
+++ b/papers/corporate-graphics-platter/banks-finance/wells-fargo-stagecoach.svg
@@ -0,0 +1,9 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<svg width="300" height="300" version="1.1" viewBox="0 0 79.375 79.375" xmlns="http://www.w3.org/2000/svg">
+ <g transform="translate(25.4942 -110.859)">
+  <g transform="matrix(.990763 0 0 -.990763 -69.4197 851.617)">
+   <path d="m44.335 667.549h80.115v80.115h-80.115z" fill="#dd1e25"/>
+   <path d="m113.38 698.373c0 3.219-1.328 5.093-3.783 5.093-2.456 0-3.783-1.874-3.783-5.093 0-3.238 1.309-5.093 3.783-5.093 2.473 0 3.783 1.855 3.783 5.093m2.983 0c0-3.965-2.819-6.748-6.766-6.748-3.929 0-6.766 2.783-6.766 6.748 0 3.947 2.855 6.748 6.766 6.748 3.928 0 6.766-2.801 6.766-6.748m-20.445-.5819c0-.3631.055-.6001.2-.8911h2.165v-3.219c-.709-.292-1.419-.419-2.146-.419-2.62 0-3.984 1.873-3.984 5.111s1.364 5.111 3.838 5.111c1.655 0 2.619-.819 3.183-2.237l.2-.509h1.31v3.255c-1.637.782-3.11 1.128-4.82 1.128-4.002 0-6.693-2.674-6.693-6.766 0-4.111 2.619-6.73 6.693-6.73 1.618 0 3.292.455 5.092 1.346v5.675h-4.838c-.145-.291-.2-.51-.2-.8549m-11.059 3.31c0 1.328-.819 2.0369-2.456 2.0369h-2.146v-4.092h2.146c1.619 0 2.456.746 2.456 2.0551m-14.242-3.7101-1.783 4.82-1.782-4.82zm17.77-3.965c.11-.1999.164-.4369.164-.746 0-.309-.054-.546-.164-.746-.4-.054-.909-.09-1.418-.09-1.764 0-2.619.727-2.82 2.419l-.072.636c-.218 1.837-.819 2.546-2.819 2.546h-1.001v-3.874h1.728v-1.5819h-11.441v1.5819h1.492l-.837 2.274h-4.729l-.837-2.274h1.528v-1.5819h-4.82v1.5819h1.273l4.456 11.15h2.419l4.548-11.15h2.51v9.567h-1.546v1.583h7.312c2.601 0 4.292-1.2919 4.292-3.365 0-2.055-1.691-3.147-3.328-3.22v-.054c1.655-.127 2.328-1.055 2.492-2.492l.072-.673c.109-1.055.328-1.528 1.164-1.528.146 0 .273.019.382.037m-27.72 9.712c1.218 0 1.637-.527 2.037-2.055l.127-.491h1.31v4.129h-10.967v-1.583h1.546v-9.567h-1.546v-1.5819h6.074v1.5819h-1.819v3.711h3.747c.146.309.2.545.2.909 0 .346-.054.564-.2.873h-3.747v4.074zm55.26 11.697c0 2.001-1.219 3.383-3.511 3.91l-2.31.528c-1.346.309-1.909.837-1.909 1.727 0 1.074.855 1.747 2.528 1.747s2.655-.601 3.037-2.019l.164-.618h1.309v3.146c-1.473.7461-3.037 1.127-4.62 1.127-3.11 0-5.11-1.491-5.11-3.891 0-1.856 1.163-3.22 3.401-3.711l2.31-.509c1.473-.328 2.019-.91 2.019-1.874 0-1.182-.892-1.837-2.674-1.837-2.019 0-3.056.801-3.51 2.328l-.237.783h-1.309v-3.566c1.655-.818 3.237-1.1819 5.365-1.1819 3.056 0 5.057 1.5279 5.057 3.9109m-11.642.8h-1.309l-.146-.637c-.364-1.618-.873-2.127-2.073-2.127h-2.528v9.5661h1.728v1.5829h-5.985v-1.5829h1.547v-9.5661h-1.547v-1.583h10.313zm-11.459 0h-1.31l-.145-.637c-.364-1.618-.873-2.127-2.073-2.127h-2.529v9.5661h1.728v1.5829h-5.984v-1.5829h1.546v-9.5661h-1.546v-1.583h10.313zm-37.015-4.347-3.202 11.1491h-1.455v1.5829h5.93v-1.5829h-1.71l2.128-7.6751 2.546 9.258h2.62l2.6-9.276 2.092 7.6931h-1.782v1.5829h15.425v-4.129h-1.31l-.127.491c-.401 1.528-.819 2.0551-2.037 2.0551h-3.019v-3.8371h3.656c.145-.309.199-.528.199-.873 0-.364-.054-.5999-.199-.91h-3.656v-3.946h3.146c1.182 0 1.71.509 2.074 2.127l.145.637h1.31v-4.347h-10.931v1.583h1.546v9.5661h-2.512l-3.183-11.1491h-2.528l-2.583 9.239-2.655-9.239z" fill="#fefefe"/>
+  </g>
+ </g>
+</svg>
diff --git a/papers/corporate-graphics-platter/fetch-logos.mjs b/papers/corporate-graphics-platter/fetch-logos.mjs
new file mode 100644
index 000000000..5081bdb81
--- /dev/null
+++ b/papers/corporate-graphics-platter/fetch-logos.mjs
@@ -0,0 +1,162 @@
+// fetch-logos.mjs — build the corporate-graphics reference library.
+// For each curated entry: search Wikimedia Commons → pick the best image file
+// → fetch original (svg/png) → rasterize svg to a 600px png for contact sheets.
+// Writes per-category manifest.md + a fetch log. Idempotent-ish (skips existing).
+//
+//   node fetch-logos.mjs [category]   (omit to run all four)
+
+import { writeFileSync, existsSync, mkdirSync } from "node:fs";
+import { execFileSync } from "node:child_process";
+import { join } from "node:path";
+
+const HERE = new URL(".", import.meta.url).pathname;
+const UA = "ac-research/1.0 (mail@aesthetic.computer) logo-reference-library";
+const sleep = (ms) => new Promise((r) => setTimeout(r, ms));
+
+// metadata is OURS (captions); the fetch only resolves the image.
+// columns: slug, query, name, by, year, motif, register, note
+const LIB = {
+  "banks-finance": [
+    ["chase-octagon", "Chase bank logo", "Chase", "Chermayeff & Geismar", "1960", "abstract octagon / vault aperture", "mid-century geometric", "first major US abstract bank mark — the negative center reads as a vault/aperture"],
+    ["deutsche-bank-slash", "Deutsche Bank logo", "Deutsche Bank", "Anton Stankowski", "1974", "slash inside a square", "swiss constructivist", "growth (diagonal) held in a stable frame (square)"],
+    ["hsbc-hexagon", "HSBC logo", "HSBC", "Henry Steiner", "1983", "hexagon from St Andrew's cross", "heraldic→geometric", "derived from a 19th-c house flag; hexagon = containment"],
+    ["barclays-eagle", "Barclays logo", "Barclays", "—", "—", "spread eagle", "heraldic, flattened", "a centuries-old spread eagle modernized to flat"],
+    ["lloyds-black-horse", "Lloyds Bank logo", "Lloyds Bank", "—", "1884 heritage", "black horse", "inherited shop-sign heraldry", "a literal goldsmith's-shop sign become a brand"],
+    ["natwest-cubes", "NatWest logo", "NatWest", "—", "1968", "three cubes / arrows", "swiss geometric", "money moving three directions"],
+    ["citi-arc", "Citi logo", "Citi", "Pentagram (Paula Scher)", "1998", "red arc over wordmark", "wordmark + gesture", "the arc as umbrella/protection (the napkin-sketch mark)"],
+    ["santander-flame", "Santander logo", "Santander", "—", "—", "flame / spark", "contemporary flat", "warmth + energy in red"],
+    ["mastercard-circles", "Mastercard logo", "Mastercard", "(Pentagram 2016 refresh)", "1968", "two overlapping circles", "gestalt overlap", "intersection = exchange"],
+    ["amex-bluebox", "American Express logo", "American Express", "—", "1970s", "the Blue Box", "corporate trust blue", "the box as security / containment"],
+    ["ubs-keys", "UBS logo", "UBS", "—", "—", "three keys", "heraldic", "keys = confidence, security, discretion"],
+    ["ing-lion", "ING Group logo", "ING", "—", "—", "lion", "dutch heraldic, flat orange", "heritage animal flattened to friendly"],
+    ["bbva-mark", "BBVA logo", "BBVA", "Landor", "2019", "geometric wordmark", "contemporary sans", "softened modern banking"],
+    ["wells-fargo-stagecoach", "Wells Fargo logo", "Wells Fargo", "—", "—", "stagecoach", "americana heritage", "trust signalled through history"],
+    ["bank-of-america", "Bank of America logo", "Bank of America", "Lippincott", "1998", "abstract flag stripes", "patriotic geometric", "flag fragment = nation-scale trust"],
+    ["monte-paschi-siena", "Monte dei Paschi di Siena logo", "Banca Monte dei Paschi di Siena", "—", "—", "heraldic shield", "italian heraldry", "the world's oldest surviving bank's arms"],
+  ],
+  "modernist-canon": [
+    ["rand-ibm", "IBM logo", "IBM", "Paul Rand", "1972", "8-bar striped letters", "rationalist", "stripes = scan-lines + unity; speed made stable"],
+    ["rand-ups", "UPS logo Paul Rand", "UPS (old)", "Paul Rand", "1961", "shield + package + bow", "heraldic-modern", "a parcel made into a coat of arms"],
+    ["rand-abc", "ABC logo", "ABC", "Paul Rand", "1962", "lowercase bauhaus circles", "bauhaus geometric", "minimal letterforms = quiet confidence"],
+    ["rand-westinghouse", "Westinghouse logo", "Westinghouse", "Paul Rand", "1960", "circuit 'W'", "atomic-age", "a circuit board read as a monogram"],
+    ["rand-next", "NeXT logo Paul Rand", "NeXT", "Paul Rand", "1986", "tilted cube", "playful-rational", "the famous $100k cube"],
+    ["cg-mobil", "Mobil logo", "Mobil", "Chermayeff & Geismar", "1964", "red O wordmark", "minimalist", "the single red O does all the work"],
+    ["cg-nbc-peacock", "NBC peacock logo", "NBC", "Chermayeff & Geismar", "1986", "six-feather peacock", "broadcast color", "color itself as the message"],
+    ["cg-pbs", "PBS logo", "PBS", "Chermayeff & Geismar", "1984", "P-head profiles", "figure-ground", "many faces = the public"],
+    ["cg-natgeo", "National Geographic logo", "National Geographic", "Chermayeff & Geismar", "—", "yellow rectangle", "portal", "the yellow frame as a window onto the world"],
+    ["bass-bell", "Bell System logo Saul Bass", "Bell System", "Saul Bass", "1969", "bell in a circle", "simplification", "a century of marks reduced to one bell"],
+    ["bass-att-globe", "AT&T globe logo", "AT&T", "Saul Bass", "1983", "striped globe", "line-network", "lines = the global network, wrapping a sphere"],
+    ["bass-united", "United Airlines logo Saul Bass", "United Airlines", "Saul Bass", "1974", "tulip 'U'", "gestural geometric", "the U that flew for 36 years"],
+    ["bass-minolta", "Minolta logo", "Minolta", "Saul Bass", "1978", "wordmark + curves", "japanese-modern", "soft motion in a tech wordmark"],
+    ["vignelli-american-airlines", "American Airlines AA logo 1967", "American Airlines", "Massimo Vignelli", "1967", "AA + eagle", "helvetica + flag", "Helvetica discipline, lasted to 2013"],
+    ["vignelli-knoll", "Knoll logo", "Knoll", "Massimo Vignelli", "—", "wordmark", "swiss typographic", "furniture as pure typography"],
+    ["lippincott-walmart-spark", "Walmart logo", "Walmart", "Lippincott", "2008", "spark / sunburst", "friendly flat", "an asterisk of warmth"],
+    ["fedex-arrow", "FedEx logo", "FedEx", "Lindon Leader (Landor)", "1994", "hidden arrow", "negative space", "the canonical negative-space mark"],
+    ["nike-swoosh", "Nike logo", "Nike", "Carolyn Davidson", "1971", "swoosh", "single gesture", "motion as a one-stroke mark"],
+    ["apple-logo", "Apple Inc logo", "Apple", "Rob Janoff", "1977", "bitten apple", "friendly silhouette", "a bite for scale + recognizability"],
+    ["paul-rand-enron", "Enron logo Paul Rand", "Enron", "Paul Rand", "1996", "tilted color bars 'E'", "rand late-style", "Rand's last major mark"],
+  ],
+  "seals-monograms": [
+    ["us-treasury-seal", "Seal of the United States Department of the Treasury", "US Treasury", "—", "1789", "scales + chevron of stars", "engraved federal seal", "balance + key = fiscal authority"],
+    ["great-seal-us", "Great Seal of the United States", "Great Seal of the United States", "—", "1782", "eagle + shield", "engraved heraldry", "the ur-seal of American officialdom"],
+    ["federal-reserve-seal", "Seal of the Federal Reserve System", "Federal Reserve", "—", "—", "eagle seal", "engraved", "monetary authority as engraved roundel"],
+    ["ul-mark", "UL certification mark", "Underwriters Laboratories", "—", "1894", "UL in a circle", "certification roundel", "the literal safety-trust stamp on a billion products"],
+    ["woolmark", "Woolmark", "Woolmark", "Francesco Saroglia", "1964", "skein swirl", "one of the great marks", "purity certification as continuous-line sculpture"],
+    ["ce-mark", "CE marking", "CE marking", "—", "1985", "geometric C+E", "conformity geometry", "constructed from circles — pure compliance form"],
+    ["bsi-kitemark", "BSI kitemark", "BSI Kitemark", "—", "1903", "kite shape", "british standard", "a monogram folded into a kite"],
+    ["good-housekeeping-seal", "Good Housekeeping Seal", "Good Housekeeping", "—", "1909", "circular guarantee", "editorial seal", "a magazine's promise made into a stamp"],
+    ["fairtrade-mark", "Fairtrade certification mark", "Fairtrade", "—", "2002", "yin-yang figure", "certification roundel", "a person + sky in a blue/green disc"],
+    ["usda-organic", "USDA organic seal", "USDA Organic", "—", "2002", "circular badge", "government certification", "trust via federal roundel"],
+    ["vw-monogram", "Volkswagen logo", "Volkswagen", "—", "1939", "V over W in a circle", "geometric monogram", "two letters locked in a wheel"],
+    ["unilever-u", "Unilever logo", "Unilever", "Wolff Olins (Miles Newlyn)", "2004", "U built of 25 icons", "monogram-as-mosaic", "authority spelled from many small marks"],
+    ["chanel-cc", "Chanel logo", "Chanel", "Coco Chanel", "1925", "interlocking C's", "luxury monogram", "mirror symmetry = the locked seal of luxury"],
+    ["penguin-roundel", "Penguin Books logo", "Penguin Books", "Edward Young", "1935", "penguin in an oval", "publisher's device", "a colophon — the book-trade's seal"],
+    ["mit-seal", "MIT seal", "MIT", "—", "1864", "artisan + scholar", "academic engraving", "the university seal as authority template"],
+    ["penny-black", "Penny Black", "Penny Black (stamp)", "—", "1840", "engraved profile", "intaglio portrait", "the first postage stamp — a state-issued mark of paid trust"],
+  ],
+  "surveillance-consent": [
+    ["norton-by-symantec", "Norton Symantec logo", "Norton", "—", "—", "yellow check in circle", "security yellow", "the check inside a ring = 'verified, protected'"],
+    ["tor-onion", "Tor project logo", "Tor", "—", "—", "onion", "activist flat", "layers = anonymity"],
+    ["signal-messenger", "Signal messenger logo", "Signal", "—", "—", "speech bubble", "friendly privacy", "privacy made warm, not cold"],
+    ["eff", "Electronic Frontier Foundation logo", "EFF", "—", "—", "wordmark / fist", "digital-rights", "advocacy, not product"],
+    ["lets-encrypt", "Let's Encrypt logo", "Let's Encrypt", "—", "2014", "open padlock", "open-security", "the lock made friendly + free"],
+    ["mozilla", "Mozilla logo", "Mozilla", "johnson banks", "2017", "moz://a wordmark", "wordmark-as-URL", "the protocol slashes built into the name"],
+    ["firefox", "Firefox logo", "Firefox", "—", "—", "fox around a globe", "warm tech", "guardian animal wrapping the web"],
+    ["okta", "Okta logo", "Okta", "—", "—", "circular O", "identity SaaS blue", "the ring as gate/identity"],
+    ["openid", "OpenID logo", "OpenID", "—", "—", "stylized ID", "standards mark", "decentralized identity, orange"],
+    ["w3c", "W3C logo", "W3C", "—", "—", "wordmark", "standards body", "the web's own authority mark"],
+    ["icann", "ICANN logo", "ICANN", "—", "—", "globe / wordmark", "governance", "who governs the namespace"],
+    ["aadhaar", "Aadhaar logo", "Aadhaar (UIDAI)", "—", "2010", "sun + fingerprint", "national-ID", "a billion-person identity mark — the fingerprint sun"],
+    ["digicert", "DigiCert logo", "DigiCert", "—", "—", "checkmark", "certificate authority", "the CA that issues web trust"],
+    ["duckduckgo", "DuckDuckGo logo", "DuckDuckGo", "—", "—", "duck in a circle", "friendly privacy-search", "an animal, not a padlock"],
+    ["fido-alliance", "FIDO Alliance logo", "FIDO Alliance", "—", "—", "checkmark / wordmark", "passwordless standard", "the body behind passkeys"],
+    ["privacy-badger", "Privacy Badger logo", "Privacy Badger (EFF)", "—", "—", "badger", "activist mascot", "privacy as a scrappy animal"],
+  ],
+};
+
+const BAD_EXT = /\.(webm|ogv|ogg|pdf|tif|tiff|gif|djvu|stl|mid|wav|webp)$/i;
+async function searchCommons(query) {
+  const url = `https://commons.wikimedia.org/w/api.php?action=query&list=search&srsearch=${encodeURIComponent(query)}&srnamespace=6&srlimit=10&format=json`;
+  const r = await fetch(url, { headers: { "User-Agent": UA } });
+  if (!r.ok) throw new Error(`search ${r.status}`);
+  const j = await r.json();
+  const hits = (j.query?.search || []).map((s) => s.title.replace(/^File:/, ""));
+  // prefer svg, then png; prefer titles with "logo"/"seal"; skip media/docs
+  const ok = hits.filter((t) => !BAD_EXT.test(t) && /\.(svg|png|jpe?g)$/i.test(t));
+  const score = (t) => (/\.svg$/i.test(t) ? 0 : /\.png$/i.test(t) ? 1 : 2) + (/logo|seal|mark|wordmark/i.test(t) ? 0 : 0.5);
+  ok.sort((a, b) => score(a) - score(b));
+  return ok[0] || null;
+}
+
+async function fetchFile(title, destBase) {
+  const ext = (title.match(/\.(svg|png|jpe?g)$/i)?.[1] || "png").toLowerCase();
+  const url = `https://commons.wikimedia.org/wiki/Special:FilePath/${encodeURIComponent(title.replace(/ /g, "_"))}`;
+  const r = await fetch(url, { headers: { "User-Agent": UA } });
+  if (!r.ok) throw new Error(`fetch ${r.status}`);
+  const buf = Buffer.from(await r.arrayBuffer());
+  const orig = `${destBase}.${ext}`;
+  writeFileSync(orig, buf);
+  // ensure a png twin for contact sheets
+  const png = `${destBase}.png`;
+  if (ext === "svg") {
+    try {
+      execFileSync("rsvg-convert", ["-w", "600", "-b", "white", orig, "-o", png]);
+    } catch {
+      execFileSync("magick", ["-background", "white", "-density", "200", orig, "-resize", "600x", png]);
+    }
+  } else if (ext !== "png") {
+    execFileSync("magick", [orig, "-resize", "600x", png]);
+  }
+  return { ext, title };
+}
+
+const onlyCat = process.argv[2];
+const cats = onlyCat ? [onlyCat] : Object.keys(LIB);
+for (const cat of cats) {
+  const dir = join(HERE, cat);
+  mkdirSync(dir, { recursive: true });
+  const rows = [];
+  const misses = [];
+  for (const [slug, query, name, by, year, motif, register, note] of LIB[cat]) {
+    const base = join(dir, slug);
+    if (existsSync(`${base}.png`)) { console.log(`· ${cat}/${slug} cached`); continue; }
+    try {
+      const title = await searchCommons(query);
+      if (!title) throw new Error("no image hit");
+      const { ext, title: t } = await fetchFile(title, base);
+      console.log(`✓ ${cat}/${slug}  ←  ${t}`);
+      rows.push({ slug, name, by, year, motif, register, note, src: t, ext });
+    } catch (e) {
+      console.log(`✗ ${cat}/${slug}: ${e.message}`);
+      misses.push({ slug, name, query, why: e.message });
+    }
+    await sleep(350);
+  }
+  // manifest
+  const head = `# ${cat} — corporate-graphics reference\n\n${rows.length} marks fetched from Wikimedia Commons.\n\n| mark | by | year | motif | register | why it matters | source (commons) |\n|---|---|---|---|---|---|---|\n`;
+  const body = rows.map((r) => `| **${r.name}** | ${r.by} | ${r.year} | ${r.motif} | ${r.register} | ${r.note} | ${r.src} |`).join("\n");
+  writeFileSync(join(dir, "manifest.md"), head + body + "\n");
+  if (misses.length) writeFileSync(join(dir, "MISSES.md"), `# misses\n\n` + misses.map((m) => `- ${m.slug} (${m.name}) — "${m.query}" — ${m.why}`).join("\n") + "\n");
+  console.log(`— ${cat}: ${rows.length} fetched, ${misses.length} missed —`);
+}
+console.log("done");
diff --git a/papers/corporate-graphics-platter/finalize.mjs b/papers/corporate-graphics-platter/finalize.mjs
new file mode 100644
index 000000000..ebb8027bb
--- /dev/null
+++ b/papers/corporate-graphics-platter/finalize.mjs
@@ -0,0 +1,67 @@
+// finalize.mjs — top up seals, rebuild manifests from disk, build contact sheets.
+import { writeFileSync, existsSync, readdirSync } from "node:fs";
+import { execFileSync } from "node:child_process";
+import { join } from "node:path";
+import { META } from "./lib-data.mjs";
+
+const HERE = new URL(".", import.meta.url).pathname;
+const UA = "ac-research/1.0 (mail@aesthetic.computer) logo-reference-library";
+const sleep = (ms) => new Promise((r) => setTimeout(r, ms));
+const CATS = ["banks-finance", "modernist-canon", "seals-monograms", "surveillance-consent"];
+const TITLE = {
+  "banks-finance": "Banks & Finance",
+  "modernist-canon": "Modernist Designer Canon",
+  "seals-monograms": "Seals · Monograms · Notary",
+  "surveillance-consent": "Surveillance · Security · Consent",
+};
+
+// reliable direct-filename top-ups for the thin seals category
+const TOPUP = [
+  ["seals-monograms", "scotus-seal", "Seal of the United States Supreme Court.svg"],
+  ["seals-monograms", "doj-seal", "Seal of the United States Department of Justice.svg"],
+  ["seals-monograms", "wordpress-w", "WordPress blue logo.svg"],
+  ["seals-monograms", "yale-shield", "Yale University Shield 1.svg"],
+];
+async function grab(cat, slug, title) {
+  const base = join(HERE, cat, slug);
+  if (existsSync(`${base}.png`)) return console.log(`· ${slug} cached`);
+  const url = `https://commons.wikimedia.org/wiki/Special:FilePath/${encodeURIComponent(title.replace(/ /g, "_"))}`;
+  const r = await fetch(url, { headers: { "User-Agent": UA } });
+  if (!r.ok) return console.log(`✗ ${slug}: ${r.status}`);
+  const ext = title.match(/\.(svg|png|jpe?g)$/i)[1].toLowerCase();
+  writeFileSync(`${base}.${ext}`, Buffer.from(await r.arrayBuffer()));
+  if (ext === "svg") {
+    try { execFileSync("rsvg-convert", ["-w", "600", "-b", "white", `${base}.svg`, "-o", `${base}.png`]); }
+    catch { execFileSync("magick", ["-background", "white", "-density", "200", `${base}.svg`, "-resize", "600x", `${base}.png`]); }
+  }
+  console.log(`✓ ${slug}  ←  ${title}`);
+}
+for (const [c, s, t] of TOPUP) { await grab(c, s, t); await sleep(300); }
+
+// rebuild manifests from disk + build contact sheets
+const HELV = "/System/Library/Fonts/Helvetica.ttc";
+let grand = 0;
+for (const cat of CATS) {
+  const dir = join(HERE, cat);
+  const pngs = readdirSync(dir).filter((f) => /\.png$/.test(f) && !f.startsWith("_")).sort();
+  const rows = pngs.map((f) => {
+    const slug = f.replace(/\.png$/, "");
+    const m = META[slug] || [slug, "—", "—", "—", "—", "—"];
+    return { slug, f, name: m[0], by: m[1], year: m[2], motif: m[3], register: m[4], note: m[5] };
+  });
+  grand += rows.length;
+  const head = `# ${TITLE[cat]}\n\n${rows.length} marks · Wikimedia Commons reference library for the REGARDE logo work.\n\n| mark | by | year | motif | aesthetic register | why it matters |\n|---|---|---|---|---|---|\n`;
+  writeFileSync(join(dir, "manifest.md"),
+    head + rows.map((r) => `| **${r.name}** | ${r.by} | ${r.year} | ${r.motif} | ${r.register} | ${r.note} |`).join("\n") + "\n");
+  // contact sheet (labelled tiles)
+  const tiles = rows.map((r) => join(dir, r.f));
+  const cols = 4;
+  execFileSync("magick", [
+    "montage", ...tiles,
+    "-font", HELV, "-pointsize", "20", "-fill", "#141414", "-label", "%t",
+    "-tile", `${cols}x`, "-geometry", "300x300+10+12", "-background", "#EFEEE8",
+    join(dir, `_sheet-${cat}.png`),
+  ]);
+  console.log(`— ${cat}: ${rows.length} marks → _sheet-${cat}.png`);
+}
+console.log(`done · ${grand} marks total`);
diff --git a/papers/corporate-graphics-platter/fix-logos.mjs b/papers/corporate-graphics-platter/fix-logos.mjs
new file mode 100644
index 000000000..285023f76
--- /dev/null
+++ b/papers/corporate-graphics-platter/fix-logos.mjs
@@ -0,0 +1,63 @@
+// fix-logos.mjs — replace off-target search picks with direct Commons files.
+// Tries candidate filenames in order; falls back to a refined search.
+import { writeFileSync, existsSync, unlinkSync, readdirSync } from "node:fs";
+import { execFileSync } from "node:child_process";
+import { join } from "node:path";
+
+const HERE = new URL(".", import.meta.url).pathname;
+const UA = "ac-research/1.0 (mail@aesthetic.computer) logo-reference-library";
+const sleep = (ms) => new Promise((r) => setTimeout(r, ms));
+
+// slug → { cat, candidates:[exact Commons filenames], query (fallback) }
+const FIXES = [
+  ["rand-abc", "modernist-canon", ["American Broadcasting Company Logo.svg", "ABC 1962 logo.svg"], "American Broadcasting Company Paul Rand logo"],
+  ["bass-united", "modernist-canon", ["United Airlines Logo (1974).svg", "United Airlines logo (1974-1993).svg", "Saul Bass United Airlines logo.svg"], "United Airlines tulip Saul Bass logo"],
+  ["barclays-eagle", "banks-finance", ["Barclays logo.svg", "Barclays Bank logo.svg", "Barclays.svg"], "Barclays Bank eagle logo"],
+  ["citi-arc", "banks-finance", ["Citi.svg", "Citibank logo.svg", "Citigroup.svg"], "Citibank red arc logo"],
+  ["unilever-u", "seals-monograms", ["Unilever.svg", "Unilever logo.svg"], "Unilever U logo"],
+  ["woolmark", "seals-monograms", ["Woolmark.svg", "Woolmark logo.svg"], "Woolmark logo"],
+  ["penguin-roundel", "seals-monograms", ["Penguin Books logo.svg", "Penguin Books.svg"], "Penguin Books publisher logo"],
+  ["mit-seal", "seals-monograms", ["MIT Seal.svg", "Seal of the Massachusetts Institute of Technology.svg"], "MIT seal logo"],
+  ["good-housekeeping-seal", "seals-monograms", ["Good Housekeeping Seal.svg", "Good Housekeeping logo.svg"], "Good Housekeeping seal logo"],
+  ["cg-natgeo", "modernist-canon", ["National Geographic logo.svg", "Natgeologo.svg"], "National Geographic yellow rectangle logo"],
+];
+
+async function exists(title) {
+  const url = `https://commons.wikimedia.org/wiki/Special:FilePath/${encodeURIComponent(title.replace(/ /g, "_"))}`;
+  const r = await fetch(url, { method: "HEAD", headers: { "User-Agent": UA }, redirect: "follow" });
+  return r.ok ? title : null;
+}
+async function searchOne(query) {
+  const url = `https://commons.wikimedia.org/w/api.php?action=query&list=search&srsearch=${encodeURIComponent(query)}&srnamespace=6&srlimit=10&format=json`;
+  const r = await fetch(url, { headers: { "User-Agent": UA } });
+  const j = await r.json();
+  const hits = (j.query?.search || []).map((s) => s.title.replace(/^File:/, "")).filter((t) => /\.svg$/i.test(t) && /logo|seal|mark/i.test(t));
+  return hits[0] || null;
+}
+async function grab(title, base) {
+  const ext = title.match(/\.(svg|png|jpe?g)$/i)[1].toLowerCase();
+  const url = `https://commons.wikimedia.org/wiki/Special:FilePath/${encodeURIComponent(title.replace(/ /g, "_"))}`;
+  const r = await fetch(url, { headers: { "User-Agent": UA } });
+  if (!r.ok) throw new Error(`${r.status}`);
+  writeFileSync(`${base}.${ext}`, Buffer.from(await r.arrayBuffer()));
+  if (ext === "svg") {
+    try { execFileSync("rsvg-convert", ["-w", "600", "-b", "white", `${base}.svg`, "-o", `${base}.png`]); }
+    catch { execFileSync("magick", ["-background", "white", "-density", "200", `${base}.svg`, "-resize", "600x", `${base}.png`]); }
+  }
+  return title;
+}
+
+for (const [slug, cat, candidates, query] of FIXES) {
+  const dir = join(HERE, cat);
+  const base = join(dir, slug);
+  // wipe old twins
+  for (const f of readdirSync(dir)) if (f.startsWith(slug + ".")) { try { unlinkSync(join(dir, f)); } catch {} }
+  let chosen = null;
+  for (const c of candidates) { if (await exists(c)) { chosen = c; break; } await sleep(150); }
+  if (!chosen) chosen = await searchOne(query);
+  if (!chosen) { console.log(`✗ ${slug}: no replacement found`); continue; }
+  try { await grab(chosen, base); console.log(`✓ ${slug}  ←  ${chosen}`); }
+  catch (e) { console.log(`✗ ${slug}: ${e.message}`); }
+  await sleep(300);
+}
+console.log("fixes done");
diff --git a/papers/corporate-graphics-platter/lib-data.mjs b/papers/corporate-graphics-platter/lib-data.mjs
new file mode 100644
index 000000000..20b1b35b3
--- /dev/null
+++ b/papers/corporate-graphics-platter/lib-data.mjs
@@ -0,0 +1,73 @@
+// shared caption metadata, keyed by slug: [name, by, year, motif, register, note]
+export const META = {
+  // banks-finance
+  "chase-octagon": ["Chase", "Chermayeff & Geismar", "1960", "octagon / vault aperture", "mid-century geometric", "first major US abstract bank mark — negative center reads as a vault"],
+  "deutsche-bank-slash": ["Deutsche Bank", "Anton Stankowski", "1974", "slash in a square", "swiss constructivist", "growth (diagonal) held in a stable frame"],
+  "hsbc-hexagon": ["HSBC", "Henry Steiner", "1983", "hexagon from St Andrew's cross", "heraldic→geometric", "from a 19th-c house flag; hexagon = containment"],
+  "barclays-eagle": ["Barclays", "—", "—", "spread eagle", "heraldic, flattened", "centuries-old eagle modernized to flat"],
+  "lloyds-black-horse": ["Lloyds Bank", "—", "1884", "black horse", "inherited shop-sign heraldry", "a goldsmith's shop sign become a brand"],
+  "natwest-cubes": ["NatWest", "—", "1968", "three cubes / arrows", "swiss geometric", "money moving three directions"],
+  "citi-arc": ["Citi", "Pentagram (Paula Scher)", "1998", "red arc over wordmark", "wordmark + gesture", "the arc as umbrella/protection"],
+  "santander-flame": ["Santander", "—", "—", "flame / spark", "contemporary flat", "warmth + energy in red"],
+  "mastercard-circles": ["Mastercard", "Pentagram (2016)", "1968", "two overlapping circles", "gestalt overlap", "intersection = exchange"],
+  "amex-bluebox": ["American Express", "—", "1970s", "the Blue Box", "corporate trust blue", "the box as security / containment"],
+  "ubs-keys": ["UBS", "—", "—", "three keys", "heraldic", "keys = confidence, security, discretion"],
+  "ing-lion": ["ING", "—", "—", "lion", "dutch heraldic, flat", "heritage animal flattened to friendly"],
+  "bbva-mark": ["BBVA", "Landor", "2019", "geometric wordmark", "contemporary sans", "softened modern banking"],
+  "wells-fargo-stagecoach": ["Wells Fargo", "—", "—", "stagecoach", "americana heritage", "trust signalled through history"],
+  "bank-of-america": ["Bank of America", "Lippincott", "1998", "abstract flag stripes", "patriotic geometric", "flag fragment = nation-scale trust"],
+  "monte-paschi-siena": ["Monte dei Paschi di Siena", "—", "—", "heraldic shield", "italian heraldry", "the world's oldest surviving bank's arms"],
+  // modernist-canon
+  "rand-ibm": ["IBM", "Paul Rand", "1972", "8-bar striped letters", "rationalist", "stripes = scan-lines + unity"],
+  "rand-ups": ["UPS (old)", "Paul Rand", "1961", "shield + package + bow", "heraldic-modern", "a parcel made into a coat of arms"],
+  "rand-abc": ["ABC", "Paul Rand", "1962", "lowercase bauhaus circles", "bauhaus geometric", "minimal letterforms = quiet confidence"],
+  "rand-westinghouse": ["Westinghouse", "Paul Rand", "1960", "circuit 'W'", "atomic-age", "a circuit board read as a monogram"],
+  "rand-next": ["NeXT", "Paul Rand", "1986", "tilted cube", "playful-rational", "the famous $100k cube"],
+  "cg-mobil": ["Mobil", "Chermayeff & Geismar", "1964", "red O wordmark", "minimalist", "the single red O does all the work"],
+  "cg-nbc-peacock": ["NBC", "Chermayeff & Geismar", "1986", "six-feather peacock", "broadcast color", "color itself as the message"],
+  "cg-pbs": ["PBS", "Chermayeff & Geismar", "1984", "P-head profiles", "figure-ground", "many faces = the public"],
+  "cg-natgeo": ["National Geographic", "Chermayeff & Geismar", "—", "yellow rectangle", "portal", "the yellow frame as a window"],
+  "bass-bell": ["Bell System", "Saul Bass", "1969", "bell in a circle", "simplification", "a century of marks reduced to one bell"],
+  "bass-att-globe": ["AT&T", "Saul Bass", "1983", "striped globe", "line-network", "lines = the global network"],
+  "bass-minolta": ["Minolta", "Saul Bass", "1978", "wordmark + curves", "japanese-modern", "soft motion in a tech wordmark"],
+  "vignelli-american-airlines": ["American Airlines", "Massimo Vignelli", "1967", "AA + eagle", "helvetica + flag", "Helvetica discipline, lasted to 2013"],
+  "vignelli-knoll": ["Knoll", "Massimo Vignelli", "—", "wordmark", "swiss typographic", "furniture as pure typography"],
+  "lippincott-walmart-spark": ["Walmart", "Lippincott", "2008", "spark / sunburst", "friendly flat", "an asterisk of warmth"],
+  "fedex-arrow": ["FedEx", "Lindon Leader (Landor)", "1994", "hidden arrow", "negative space", "the canonical negative-space mark"],
+  "nike-swoosh": ["Nike", "Carolyn Davidson", "1971", "swoosh", "single gesture", "motion as a one-stroke mark"],
+  "apple-logo": ["Apple", "Rob Janoff", "1977", "bitten apple", "friendly silhouette", "a bite for scale + recognizability"],
+  "paul-rand-enron": ["Enron", "Paul Rand", "1996", "tilted color bars 'E'", "rand late-style", "Rand's last major mark"],
+  // seals-monograms
+  "us-treasury-seal": ["US Treasury", "—", "1789", "scales + chevron of stars", "engraved federal seal", "balance + key = fiscal authority"],
+  "great-seal-us": ["Great Seal of the US", "—", "1782", "eagle + shield", "engraved heraldry", "the ur-seal of American officialdom"],
+  "federal-reserve-seal": ["Federal Reserve", "—", "—", "eagle seal", "engraved", "monetary authority as engraved roundel"],
+  "ul-mark": ["Underwriters Laboratories", "—", "1894", "UL in a circle", "certification roundel", "the literal safety-trust stamp"],
+  "ce-mark": ["CE marking", "—", "1985", "geometric C+E", "conformity geometry", "constructed from circles — pure compliance form"],
+  "bsi-kitemark": ["BSI Kitemark", "—", "1903", "kite shape", "british standard", "a monogram folded into a kite"],
+  "fairtrade-mark": ["Fairtrade", "—", "2002", "yin-yang figure", "certification roundel", "a person + sky in a disc"],
+  "usda-organic": ["USDA Organic", "—", "2002", "circular badge", "government certification", "trust via federal roundel"],
+  "vw-monogram": ["Volkswagen", "—", "1939", "V over W in a circle", "geometric monogram", "two letters locked in a wheel"],
+  "chanel-cc": ["Chanel", "Coco Chanel", "1925", "interlocking C's", "luxury monogram", "mirror symmetry = the locked seal of luxury"],
+  "penny-black": ["Penny Black (stamp)", "—", "1840", "engraved profile", "intaglio portrait", "the first postage stamp — a state mark of paid trust"],
+  "scotus-seal": ["US Supreme Court", "—", "—", "eagle seal", "engraved judicial", "the highest court's roundel"],
+  "doj-seal": ["US Dept of Justice", "—", "—", "eagle + shield seal", "engraved federal", "justice rendered as an official stamp"],
+  "wordpress-w": ["WordPress", "—", "—", "circled W", "open-source monogram", "a letter in a ring = an institution"],
+  "yale-shield": ["Yale University", "—", "—", "shield + book", "academic heraldry", "knowledge bound in a coat of arms"],
+  // surveillance-consent
+  "norton-by-symantec": ["Norton", "—", "—", "yellow check in circle", "security yellow", "check in a ring = verified, protected"],
+  "tor-onion": ["Tor", "—", "—", "onion", "activist flat", "layers = anonymity"],
+  "signal-messenger": ["Signal", "—", "—", "speech bubble", "friendly privacy", "privacy made warm, not cold"],
+  "eff": ["EFF", "—", "—", "wordmark", "digital-rights", "advocacy, not product"],
+  "lets-encrypt": ["Let's Encrypt", "—", "2014", "open padlock", "open-security", "the lock made friendly + free"],
+  "mozilla": ["Mozilla", "johnson banks", "2017", "moz://a wordmark", "wordmark-as-URL", "the protocol slashes built into the name"],
+  "firefox": ["Firefox", "—", "—", "fox around a globe", "warm tech", "guardian animal wrapping the web"],
+  "okta": ["Okta", "—", "—", "circular O", "identity SaaS blue", "the ring as gate / identity"],
+  "openid": ["OpenID", "—", "—", "stylized ID", "standards mark", "decentralized identity, orange"],
+  "w3c": ["W3C", "—", "—", "wordmark", "standards body", "the web's own authority mark"],
+  "icann": ["ICANN", "—", "—", "globe / wordmark", "governance", "who governs the namespace"],
+  "aadhaar": ["Aadhaar (UIDAI)", "—", "2010", "sun + fingerprint", "national-ID", "a billion-person identity mark"],
+  "digicert": ["DigiCert", "—", "—", "checkmark", "certificate authority", "the CA that issues web trust"],
+  "duckduckgo": ["DuckDuckGo", "—", "—", "duck in a circle", "friendly privacy-search", "an animal, not a padlock"],
+  "fido-alliance": ["FIDO Alliance", "—", "—", "checkmark / wordmark", "passwordless standard", "the body behind passkeys"],
+  "privacy-badger": ["Privacy Badger (EFF)", "—", "—", "badger", "activist mascot", "privacy as a scrappy animal"],
+};
diff --git a/papers/corporate-graphics-platter/modernist-canon/_sheet-modernist-canon.png b/papers/corporate-graphics-platter/modernist-canon/_sheet-modernist-canon.png
new file mode 100644
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diff --git a/papers/corporate-graphics-platter/modernist-canon/cg-pbs.svg b/papers/corporate-graphics-platter/modernist-canon/cg-pbs.svg
new file mode 100644
index 000000000..eaa0757d4
--- /dev/null
+++ b/papers/corporate-graphics-platter/modernist-canon/cg-pbs.svg
@@ -0,0 +1,142 @@
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diff --git a/papers/corporate-graphics-platter/modernist-canon/manifest.md b/papers/corporate-graphics-platter/modernist-canon/manifest.md
new file mode 100644
index 000000000..888c44642
--- /dev/null
+++ b/papers/corporate-graphics-platter/modernist-canon/manifest.md
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+# Modernist Designer Canon
+
+19 marks · Wikimedia Commons reference library for the REGARDE logo work.
+
+| mark | by | year | motif | aesthetic register | why it matters |
+|---|---|---|---|---|---|
+| **Apple** | Rob Janoff | 1977 | bitten apple | friendly silhouette | a bite for scale + recognizability |
+| **AT&T** | Saul Bass | 1983 | striped globe | line-network | lines = the global network |
+| **Bell System** | Saul Bass | 1969 | bell in a circle | simplification | a century of marks reduced to one bell |
+| **Minolta** | Saul Bass | 1978 | wordmark + curves | japanese-modern | soft motion in a tech wordmark |
+| **Mobil** | Chermayeff & Geismar | 1964 | red O wordmark | minimalist | the single red O does all the work |
+| **National Geographic** | Chermayeff & Geismar | — | yellow rectangle | portal | the yellow frame as a window |
+| **NBC** | Chermayeff & Geismar | 1986 | six-feather peacock | broadcast color | color itself as the message |
+| **PBS** | Chermayeff & Geismar | 1984 | P-head profiles | figure-ground | many faces = the public |
+| **FedEx** | Lindon Leader (Landor) | 1994 | hidden arrow | negative space | the canonical negative-space mark |
+| **Walmart** | Lippincott | 2008 | spark / sunburst | friendly flat | an asterisk of warmth |
+| **Nike** | Carolyn Davidson | 1971 | swoosh | single gesture | motion as a one-stroke mark |
+| **Enron** | Paul Rand | 1996 | tilted color bars 'E' | rand late-style | Rand's last major mark |
+| **ABC** | Paul Rand | 1962 | lowercase bauhaus circles | bauhaus geometric | minimal letterforms = quiet confidence |
+| **IBM** | Paul Rand | 1972 | 8-bar striped letters | rationalist | stripes = scan-lines + unity |
+| **NeXT** | Paul Rand | 1986 | tilted cube | playful-rational | the famous $100k cube |
+| **UPS (old)** | Paul Rand | 1961 | shield + package + bow | heraldic-modern | a parcel made into a coat of arms |
+| **Westinghouse** | Paul Rand | 1960 | circuit 'W' | atomic-age | a circuit board read as a monogram |
+| **American Airlines** | Massimo Vignelli | 1967 | AA + eagle | helvetica + flag | Helvetica discipline, lasted to 2013 |
+| **Knoll** | Massimo Vignelli | — | wordmark | swiss typographic | furniture as pure typography |
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diff --git a/papers/corporate-graphics-platter/modernist-canon/rand-ibm.svg b/papers/corporate-graphics-platter/modernist-canon/rand-ibm.svg
new file mode 100644
index 000000000..26c069485
--- /dev/null
+++ b/papers/corporate-graphics-platter/modernist-canon/rand-ibm.svg
@@ -0,0 +1,31 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<svg width="31.2mm" height="10.6mm" version="1.1" viewBox="0 0 31.2 10.6" xmlns="http://www.w3.org/2000/svg" xmlns:cc="http://creativecommons.org/ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:xlink="http://www.w3.org/1999/xlink">
+ <title>IBM i logo</title>
+ <desc>An operating system for IBM Power Systems</desc>
+ <defs>
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+ <metadata>
+  <rdf:RDF>
+   <cc:Work rdf:about="">
+    <dc:format>image/svg+xml</dc:format>
+    <dc:type rdf:resource="http://purl.org/dc/dcmitype/StillImage"/>
+    <dc:title>IBM i logo</dc:title>
+   </cc:Work>
+  </rdf:RDF>
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index 000000000..fc7ac6e54
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diff --git a/papers/corporate-graphics-platter/seals-monograms/manifest.md b/papers/corporate-graphics-platter/seals-monograms/manifest.md
new file mode 100644
index 000000000..9b4b78723
--- /dev/null
+++ b/papers/corporate-graphics-platter/seals-monograms/manifest.md
@@ -0,0 +1,21 @@
+# Seals · Monograms · Notary
+
+15 marks · Wikimedia Commons reference library for the REGARDE logo work.
+
+| mark | by | year | motif | aesthetic register | why it matters |
+|---|---|---|---|---|---|
+| **BSI Kitemark** | — | 1903 | kite shape | british standard | a monogram folded into a kite |
+| **CE marking** | — | 1985 | geometric C+E | conformity geometry | constructed from circles — pure compliance form |
+| **Chanel** | Coco Chanel | 1925 | interlocking C's | luxury monogram | mirror symmetry = the locked seal of luxury |
+| **US Dept of Justice** | — | — | eagle + shield seal | engraved federal | justice rendered as an official stamp |
+| **Fairtrade** | — | 2002 | yin-yang figure | certification roundel | a person + sky in a disc |
+| **Federal Reserve** | — | — | eagle seal | engraved | monetary authority as engraved roundel |
+| **Great Seal of the US** | — | 1782 | eagle + shield | engraved heraldry | the ur-seal of American officialdom |
+| **Penny Black (stamp)** | — | 1840 | engraved profile | intaglio portrait | the first postage stamp — a state mark of paid trust |
+| **US Supreme Court** | — | — | eagle seal | engraved judicial | the highest court's roundel |
+| **Underwriters Laboratories** | — | 1894 | UL in a circle | certification roundel | the literal safety-trust stamp |
+| **US Treasury** | — | 1789 | scales + chevron of stars | engraved federal seal | balance + key = fiscal authority |
+| **USDA Organic** | — | 2002 | circular badge | government certification | trust via federal roundel |
+| **Volkswagen** | — | 1939 | V over W in a circle | geometric monogram | two letters locked in a wheel |
+| **WordPress** | — | — | circled W | open-source monogram | a letter in a ring = an institution |
+| **Yale University** | — | — | shield + book | academic heraldry | knowledge bound in a coat of arms |
diff --git a/papers/corporate-graphics-platter/seals-monograms/penny-black.png b/papers/corporate-graphics-platter/seals-monograms/penny-black.png
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new file mode 100644
index 000000000..1c67a5fbd
--- /dev/null
+++ b/papers/corporate-graphics-platter/seals-monograms/us-treasury-seal.svg
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diff --git a/papers/corporate-graphics-platter/surveillance-consent/aadhaar.svg b/papers/corporate-graphics-platter/surveillance-consent/aadhaar.svg
new file mode 100644
index 000000000..c786eba69
--- /dev/null
+++ b/papers/corporate-graphics-platter/surveillance-consent/aadhaar.svg
@@ -0,0 +1,30 @@
+<?xml version="1.0" encoding="UTF-8"?>
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+ <title>Aadhaar hindi logo</title>
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index 000000000..e06397b74
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diff --git a/papers/corporate-graphics-platter/surveillance-consent/manifest.md b/papers/corporate-graphics-platter/surveillance-consent/manifest.md
new file mode 100644
index 000000000..315537e07
--- /dev/null
+++ b/papers/corporate-graphics-platter/surveillance-consent/manifest.md
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+# Surveillance · Security · Consent
+
+16 marks · Wikimedia Commons reference library for the REGARDE logo work.
+
+| mark | by | year | motif | aesthetic register | why it matters |
+|---|---|---|---|---|---|
+| **Aadhaar (UIDAI)** | — | 2010 | sun + fingerprint | national-ID | a billion-person identity mark |
+| **DigiCert** | — | — | checkmark | certificate authority | the CA that issues web trust |
+| **DuckDuckGo** | — | — | duck in a circle | friendly privacy-search | an animal, not a padlock |
+| **EFF** | — | — | wordmark | digital-rights | advocacy, not product |
+| **FIDO Alliance** | — | — | checkmark / wordmark | passwordless standard | the body behind passkeys |
+| **Firefox** | — | — | fox around a globe | warm tech | guardian animal wrapping the web |
+| **ICANN** | — | — | globe / wordmark | governance | who governs the namespace |
+| **Let's Encrypt** | — | 2014 | open padlock | open-security | the lock made friendly + free |
+| **Mozilla** | johnson banks | 2017 | moz://a wordmark | wordmark-as-URL | the protocol slashes built into the name |
+| **Norton** | — | — | yellow check in circle | security yellow | check in a ring = verified, protected |
+| **Okta** | — | — | circular O | identity SaaS blue | the ring as gate / identity |
+| **OpenID** | — | — | stylized ID | standards mark | decentralized identity, orange |
+| **Privacy Badger (EFF)** | — | — | badger | activist mascot | privacy as a scrappy animal |
+| **Signal** | — | — | speech bubble | friendly privacy | privacy made warm, not cold |
+| **Tor** | — | — | onion | activist flat | layers = anonymity |
+| **W3C** | — | — | wordmark | standards body | the web's own authority mark |
diff --git a/papers/corporate-graphics-platter/surveillance-consent/mozilla.png b/papers/corporate-graphics-platter/surveillance-consent/mozilla.png
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diff --git a/papers/corporate-graphics-platter/surveillance-consent/w3c.svg b/papers/corporate-graphics-platter/surveillance-consent/w3c.svg
new file mode 100644
index 000000000..25161a57d
--- /dev/null
+++ b/papers/corporate-graphics-platter/surveillance-consent/w3c.svg
@@ -0,0 +1,6 @@
+<svg xmlns="http://www.w3.org/2000/svg" id="Ebene_1" viewBox="5.01 23.88 199.99 95.24">
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diff --git a/pop/americomputadora/americomputadora.illy.txt b/pop/americomputadora/americomputadora.illy.txt
new file mode 100644
index 000000000..d5e68ff3d
--- /dev/null
+++ b/pop/americomputadora/americomputadora.illy.txt
@@ -0,0 +1,35 @@
+americomputadora — album cover. a warm, slightly surreal tabletop still
+life that fuses three things into one little world: america, a computer,
+and a kid's explorer adventure. square.
+
+a cozy handmade diorama photographed at golden hour, soft and tactile.
+warm dusty colors — faded cream, soft sky blue, dusty rose-red, gentle
+gold — like a sun-bleached vintage postcard. tender and a touch funny, not
+slick, not corporate. NO text, NO words, NO letters, NO logos, NO brand
+marks anywhere.
+
+centerpiece: a chunky old beige desktop computer with a rounded CRT
+monitor, the kind from the late 1990s, its screen glowing a soft warm
+amber. a simple little smile or heart shape glows faintly on the screen —
+hand-drawn, pixelated, sweet. NO apple, NO windows, NO brand badge — a
+plain generic beige machine.
+
+draped loosely over the top corner of the monitor, a small piece of faded
+star-pattern bunting — soft worn cloth with a few cream stars on dusty blue
+and rose stripes, gently patriotic but vintage and threadbare, NOT a real
+flag, NO official insignia.
+
+beside the computer on the table: a small child's explorer backpack in
+warm purple-and-orange canvas, and a rolled paper trail-map with a dotted
+winding path drawn on it, like a cartoon adventure route — the explorer
+motif, but NObody, NO cartoon character, NO mascot, NO face. just the
+little backpack and the map.
+
+behind it all, a soft painted backdrop: a gentle winding dotted path
+leading over low rolling hills into a warm hazy sky. dreamy, storybook,
+out of focus.
+
+composition: the beige computer centered and dominant, bunting on its
+corner, backpack and map nestled at its base, path receding behind. warm
+even light, soft shadows, shallow depth of field. cozy, surreal, sincere.
+NO text anywhere in the image.
diff --git a/pop/americomputadora/bin/clean.mjs b/pop/americomputadora/bin/clean.mjs
new file mode 100644
index 000000000..ef217eea5
--- /dev/null
+++ b/pop/americomputadora/bin/clean.mjs
@@ -0,0 +1,164 @@
+#!/usr/bin/env node
+// clean.mjs — isolate the words from the recordings.
+//
+// the america/dora utterances were cut straight from full mixes, so crowd,
+// band and theme-music ride under every word — and the whisper transform in
+// bin/hooks.mjs smears that bed into the breath. fix at the source:
+//
+//   1. demucs (two-stems) separates each FULL source recording into
+//      vocals/accompaniment — full songs give the model context that
+//      sub-second clips can't.  cached in .cache/demucs/.
+//   2. every clip in clips.json is re-cut from the vocal stem, then
+//      denoised (afftdn), silence-trimmed on both ends (the music bleed is
+//      silence now, so the word boundary tightens itself), faded, loudnormed.
+//   3. results overwrite utterances/<group>/ — same names, cleaner words.
+//
+// after this, re-run `node bin/hooks.mjs build` (delete stale snapped/ first
+// or pass --resnap here) so the combination library inherits the clean cuts.
+//
+// usage:
+//   node bin/clean.mjs               # separate + re-cut america/dora
+//   node bin/clean.mjs --resnap      # …then rebuild snapped/ + hooks.html
+//   node bin/clean.mjs --group dora  # one group only
+
+import { spawnSync } from "node:child_process";
+import { existsSync, mkdirSync, readFileSync, rmSync, renameSync } from "node:fs";
+import { basename, dirname, join, extname } from "node:path";
+import { fileURLToPath } from "node:url";
+
+const HERE = dirname(fileURLToPath(import.meta.url));
+const ROOT = dirname(HERE);
+const SR = 48_000;
+
+const argv = process.argv.slice(2);
+const flags = {};
+for (let i = 0; i < argv.length; i++) {
+  const a = argv[i];
+  if (a.startsWith("--")) {
+    const k = a.slice(2), n = argv[i + 1];
+    if (n !== undefined && !n.startsWith("--")) { flags[k] = n; i++; } else flags[k] = true;
+  }
+}
+
+const slug = (s) => s.toLowerCase().replace(/[^a-z0-9]+/g, "-").replace(/^-|-$/g, "");
+const srcSlug = (srcRel) => basename(srcRel, extname(srcRel));
+
+const clips = JSON.parse(readFileSync(join(ROOT, "clips.json"), "utf8"))
+  .filter((c) => c.start != null && c.end != null)
+  .filter((c) => !flags.group || c.group === flags.group);
+
+// ── 1. demucs each needed span (cached) ─────────────────────────────────
+// whole recordings give the model context that sub-second clips can't —
+// but marathon sources (3-hour episode compilations) would OOM an 8 GB
+// machine, so anything over LONG_SRC gets a ±15 s proxy window per clip
+// and only that window is separated.
+const cacheDir = join(ROOT, ".cache", "demucs");
+const proxyDir = join(ROOT, ".cache", "proxies");
+mkdirSync(cacheDir, { recursive: true });
+mkdirSync(proxyDir, { recursive: true });
+const LONG_SRC = 600; // seconds
+const CTX = 15;       // proxy context either side of the clip
+
+function probeDur(p) {
+  const r = spawnSync("ffprobe", ["-v", "error", "-show_entries", "format=duration", "-of", "csv=p=0", p], { encoding: "utf8" });
+  return +r.stdout.trim() || 0;
+}
+
+const srcDur = {};
+for (const s of [...new Set(clips.map((c) => c.source))]) srcDur[s] = probeDur(join(ROOT, s));
+
+// per clip: which file goes through demucs, where its stem lands, and the
+// time offset between source timestamps and that stem.
+const jobs = clips.map((c) => {
+  if (srcDur[c.source] <= LONG_SRC) {
+    return { clip: c, input: join(ROOT, c.source), stemName: srcSlug(c.source), offset: 0 };
+  }
+  const winStart = Math.max(0, c.start - CTX);
+  const stemName = `${srcSlug(c.source)}-${slug(c.tag)}`;
+  const proxy = join(proxyDir, `${stemName}.wav`);
+  if (!existsSync(proxy)) {
+    spawnSync("ffmpeg", [
+      "-hide_banner", "-y", "-loglevel", "error",
+      "-ss", String(winStart), "-i", join(ROOT, c.source),
+      "-t", String((c.end - c.start + CTX * 2).toFixed(3)),
+      "-ac", "2", "-ar", "44100", proxy,
+    ], { stdio: ["ignore", "ignore", "inherit"] });
+  }
+  return { clip: c, input: proxy, stemName, offset: winStart };
+});
+
+const stemFor = (j) => join(cacheDir, "htdemucs", j.stemName, "vocals.wav");
+const todo = [...new Map(jobs.filter((j) => !existsSync(stemFor(j))).map((j) => [j.input, j])).values()];
+if (todo.length) {
+  console.log(`# demucs — separating ${todo.length} input(s), one at a time (8 GB machine):`);
+  for (const j of todo) {
+    console.log(`  · ${basename(j.input)} (${probeDur(j.input).toFixed(0)}s)`);
+    const res = spawnSync("demucs", ["--two-stems=vocals", "-o", cacheDir, j.input],
+      { stdio: ["ignore", "inherit", "inherit"] });
+    if (res.status !== 0) { console.error(`✗ demucs failed on ${basename(j.input)}`); process.exit(1); }
+  }
+} else {
+  console.log("# demucs — all vocal stems cached");
+}
+
+// ── 2. re-cut every word from its vocal stem ────────────────────────────
+// pad the cut a touch, then let silence-trim find the true word boundary:
+// denoise → trim head → fade in → (reversed) trim tail → fade out → loudnorm.
+const PAD = 0.06;
+const CLEAN_CHAIN =
+  "afftdn=nf=-30," +
+  "silenceremove=start_periods=1:start_threshold=-38dB:start_silence=0.02," +
+  "afade=t=in:d=0.006," +
+  "areverse," +
+  "silenceremove=start_periods=1:start_threshold=-38dB:start_silence=0.02," +
+  "afade=t=in:d=0.02," +
+  "areverse," +
+  "loudnorm=I=-14:TP=-1:LRA=11";
+
+console.log(`\n# re-cutting ${clips.length} words from vocal stems:`);
+let made = 0, fellBack = 0;
+for (const j of jobs) {
+  const c = j.clip;
+  const stem = stemFor(j);
+  const outDir = join(ROOT, "utterances", c.group);
+  mkdirSync(outDir, { recursive: true });
+  const name = `${srcSlug(c.source)}-${slug(c.tag)}`;
+  const outAbs = join(outDir, `${name}.wav`);
+  const tmp = outAbs + ".clean.tmp.wav";
+  const dur = c.end - c.start + PAD * 2;
+  const cut = (input, offset) => spawnSync("ffmpeg", [
+    "-hide_banner", "-y", "-loglevel", "error",
+    "-ss", String(Math.max(0, c.start - offset - PAD).toFixed(3)), "-i", input,
+    "-t", String(dur.toFixed(3)),
+    "-af", CLEAN_CHAIN + (c.gain_db ? `,volume=${c.gain_db}dB` : ""),
+    "-ac", "1", "-ar", String(SR), tmp,
+  ], { stdio: ["ignore", "ignore", "inherit"] }).status === 0;
+
+  let ok = cut(stem, j.offset) && probeDur(tmp) > 0.08;
+  if (!ok) {
+    // stem came up empty for this span (separation miss) — fall back to the
+    // original mix with denoise+trim only, and say so.
+    ok = cut(join(ROOT, c.source), 0) && probeDur(tmp) > 0.08;
+    if (ok) { console.log(`  ! ${c.group}/${name} — stem empty, denoised the mix cut instead`); fellBack++; }
+  }
+  if (ok) {
+    renameSync(tmp, outAbs);
+    console.log(`  ✓ ${c.group}/${name}.wav  (${probeDur(outAbs).toFixed(2)}s)`);
+    made++;
+  } else {
+    rmSync(tmp, { force: true });
+    console.log(`  ✗ ${c.group}/${name} — both stem and mix cut failed, kept old file`);
+  }
+}
+console.log(`\n# ${made}/${clips.length} re-cut clean${fellBack ? ` (${fellBack} fell back to denoised mix)` : ""}`);
+
+// ── 3. optional resnap ──────────────────────────────────────────────────
+if (flags.resnap) {
+  const groups = flags.group ? [flags.group] : [...new Set(clips.map((c) => c.group))];
+  for (const g of groups) {
+    rmSync(join(ROOT, "snapped", g), { recursive: true, force: true });
+    console.log(`# cleared snapped/${g}/`);
+  }
+  const res = spawnSync("node", [join(HERE, "hooks.mjs")], { stdio: "inherit" });
+  process.exit(res.status ?? 0);
+}
diff --git a/pop/americomputadora/bin/gen-illy.mjs b/pop/americomputadora/bin/gen-illy.mjs
new file mode 100644
index 000000000..67546cf57
--- /dev/null
+++ b/pop/americomputadora/bin/gen-illy.mjs
@@ -0,0 +1,93 @@
+#!/usr/bin/env node
+// americomputadora/bin/gen-illy.mjs — generate the album cover via
+// gpt-image-2 (text-to-image, no identity refs — it's an object still
+// life, not a portrait), then embed it into the mastered mp3 as ID3 art.
+//
+// Prompt: pop/americomputadora/americomputadora.illy.txt (papers voice)
+// Output: pop/americomputadora/out/americomputadora-cover.png
+// Embed:  pop/americomputadora/out/americomputadora.mp3 (ID3v2 picture)
+//
+// Usage:
+//   node bin/gen-illy.mjs            # cached if cover exists
+//   node bin/gen-illy.mjs --force    # regenerate
+//   node bin/gen-illy.mjs --embed-only
+
+import { readFileSync, writeFileSync, existsSync, mkdirSync, renameSync } from "node:fs";
+import { resolve, dirname } from "node:path";
+import { fileURLToPath } from "node:url";
+import { spawnSync } from "node:child_process";
+
+const HERE = dirname(fileURLToPath(import.meta.url));
+const LANE = resolve(HERE, "..");
+const REPO = resolve(LANE, "..", "..");
+
+const flags = {};
+for (let i = 2; i < process.argv.length; i++) {
+  if (process.argv[i].startsWith("--")) flags[process.argv[i].slice(2)] = true;
+}
+const FORCE = flags.force === true;
+const SIZE = "1024x1024";
+
+const PROMPT_PATH = `${LANE}/americomputadora.illy.txt`;
+const OUT_PATH = `${LANE}/out/americomputadora-cover.png`;
+const MP3_PATH = `${LANE}/out/americomputadora.mp3`;
+mkdirSync(`${LANE}/out`, { recursive: true });
+
+function loadOpenAIKey() {
+  if (process.env.OPENAI_API_KEY) return process.env.OPENAI_API_KEY;
+  const vault = `${REPO}/aesthetic-computer-vault/.devcontainer/envs/devcontainer.env`;
+  if (existsSync(vault)) {
+    for (const line of readFileSync(vault, "utf8").split("\n")) {
+      if (line.startsWith("OPENAI_API_KEY=")) {
+        return line.slice("OPENAI_API_KEY=".length).trim().replace(/^['"]|['"]$/g, "");
+      }
+    }
+  }
+  throw new Error("OPENAI_API_KEY not set and not found in vault");
+}
+
+function embedCover() {
+  if (!existsSync(OUT_PATH) || !existsSync(MP3_PATH)) {
+    console.warn(`  ⚠ skip embed — need both ${OUT_PATH} and ${MP3_PATH}`);
+    return;
+  }
+  const tmp = `${MP3_PATH}.embed.mp3`;
+  const r = spawnSync("ffmpeg", ["-hide_banner", "-y", "-loglevel", "error",
+    "-i", MP3_PATH, "-i", OUT_PATH,
+    "-map", "0:a", "-map", "1:v", "-c", "copy", "-id3v2_version", "3",
+    "-metadata:s:v", "title=cover", "-metadata:s:v", "comment=Cover (front)",
+    "-disposition:v", "attached_pic", tmp], { stdio: "inherit" });
+  if (r.status !== 0 || !existsSync(tmp)) { console.error("✗ embed failed"); return; }
+  renameSync(tmp, MP3_PATH);
+  console.log(`✓ cover embedded → ${MP3_PATH.replace(REPO + "/", "")}`);
+}
+
+if (flags["embed-only"]) { embedCover(); process.exit(0); }
+
+if (existsSync(OUT_PATH) && !FORCE) {
+  console.log(`✓ cached cover → ${OUT_PATH.replace(REPO + "/", "")} (use --force to regen)`);
+  embedCover();
+  process.exit(0);
+}
+
+const apiKey = loadOpenAIKey();
+const prompt = readFileSync(PROMPT_PATH, "utf8").trim();
+console.log(`▸ americomputadora cover · ${SIZE} · gpt-image-2`);
+const t0 = Date.now();
+
+const res = await fetch("https://api.openai.com/v1/images/generations", {
+  method: "POST",
+  headers: { Authorization: `Bearer ${apiKey}`, "content-type": "application/json" },
+  body: JSON.stringify({ model: "gpt-image-2", prompt, size: SIZE, quality: "high", n: 1 }),
+});
+if (!res.ok) {
+  console.error(`✗ OpenAI ${res.status}: ${(await res.text()).slice(0, 600)}`);
+  process.exit(1);
+}
+const json = await res.json();
+const b64 = json.data?.[0]?.b64_json;
+if (!b64) { console.error(`✗ no image: ${JSON.stringify(json).slice(0, 280)}`); process.exit(1); }
+writeFileSync(OUT_PATH, Buffer.from(b64, "base64"));
+console.log(`✓ ${((Date.now() - t0) / 1000).toFixed(1)}s → ${OUT_PATH.replace(REPO + "/", "")}`);
+
+embedCover();
diff --git a/pop/americomputadora/bin/hooks.mjs b/pop/americomputadora/bin/hooks.mjs
new file mode 100644
index 000000000..cf2fb98ef
--- /dev/null
+++ b/pop/americomputadora/bin/hooks.mjs
@@ -0,0 +1,635 @@
+#!/usr/bin/env node
+// hooks.mjs — the full-phrase combination machine.
+//
+// every utterance in utterances/<group>/ gets autotuned ("snapped") to every
+// target MIDI note the hook variants in melody.json ask of its slot, plus a
+// whispered twin (FFT phase-randomization — breathy ghost of the same word).
+// the snapped library lives in snapped/<group>/ and is indexed by hooks.json.
+//
+// from there every combination of the phrase — america × computer × dora —
+// is playable instantly in hooks.html (no per-combo render), and `flight`
+// stitches a batch of random combos to mp3 for couch listening.
+//
+// usage:
+//   node bin/hooks.mjs                 # build + page (the default)
+//   node bin/hooks.mjs build           # snap library only
+//   node bin/hooks.mjs page            # regenerate hooks.html from hooks.json
+//   node bin/hooks.mjs flight          # 24 random stitched combos → out/hooks/
+//   node bin/hooks.mjs flight --count 64 --variant 4 --whisper
+//   node bin/hooks.mjs flight --seed 7 # reproducible flight
+//   node bin/hooks.mjs render --fav hooks-favorites.json  # stitch exported favorites
+
+import { spawn, spawnSync } from "node:child_process";
+import {
+  existsSync, mkdirSync, readdirSync, readFileSync, writeFileSync, unlinkSync,
+} from "node:fs";
+import { resolve, dirname, join, basename } from "node:path";
+import { fileURLToPath } from "node:url";
+import { tmpdir } from "node:os";
+
+import { readWavMono } from "../../lib/wav.mjs";
+
+const SR = 48_000;
+const HERE = dirname(fileURLToPath(import.meta.url));
+const ROOT = dirname(HERE);
+const GROUPS = ["america", "computer", "dora"];
+
+const argv = process.argv.slice(2);
+const cmd = argv[0] && !argv[0].startsWith("--") ? argv[0] : "all";
+const flags = {};
+for (let i = 0; i < argv.length; i++) {
+  const a = argv[i];
+  if (a.startsWith("--")) {
+    const k = a.slice(2), n = argv[i + 1];
+    if (n !== undefined && !n.startsWith("--")) { flags[k] = n; i++; } else flags[k] = true;
+  }
+}
+
+const melody = JSON.parse(readFileSync(join(ROOT, "melody.json"), "utf8"));
+
+// ── YIN-lite pitch detection (same as stitch.mjs) ───────────────────────
+function detectPitchHz(samples, sr) {
+  const n = samples.length;
+  const seg = samples.subarray(Math.floor(n * 0.2), Math.floor(n * 0.8));
+  const minLag = Math.floor(sr / 600);
+  const maxLag = Math.floor(sr / 80);
+  let bestLag = 0, bestScore = -Infinity;
+  for (let lag = minLag; lag <= maxLag; lag++) {
+    let r = 0, e0 = 0, e1 = 0;
+    for (let i = 0; i + lag < seg.length; i++) {
+      r += seg[i] * seg[i + lag];
+      e0 += seg[i] * seg[i];
+      e1 += seg[i + lag] * seg[i + lag];
+    }
+    const norm = Math.sqrt(e0 * e1) || 1;
+    const score = r / norm;
+    if (score > bestScore) { bestScore = score; bestLag = lag; }
+  }
+  return bestLag === 0 ? null : sr / bestLag;
+}
+const hzToMidi = (hz) => 69 + 12 * Math.log2(hz / 440);
+const midiName = (m) => {
+  const names = ["C", "C#", "D", "D#", "E", "F", "F#", "G", "G#", "A", "A#", "B"];
+  return names[m % 12] + (Math.floor(m / 12) - 1);
+};
+
+function chainAtempo(target) {
+  const stages = [];
+  let r = target;
+  while (r > 2.0) { stages.push(2.0); r /= 2.0; }
+  while (r < 0.5) { stages.push(0.5); r /= 0.5; }
+  stages.push(+r.toFixed(6));
+  return stages.map((s) => `atempo=${s}`).join(",");
+}
+
+// whisper = keep the magnitude spectrum, randomize all phase. the word's
+// formants survive but the pitch dissolves into breath.
+const WHISPER =
+  "highpass=f=250," +
+  "afftfilt=real='hypot(re,im)*cos(random(0)*2*PI)':imag='hypot(re,im)*sin(random(1)*2*PI)':win_size=512:overlap=0.75";
+
+// ── tiny ffmpeg job pool (8 GB machine: cap 4 concurrent) ──────────────
+function ffmpegAsync(args) {
+  return new Promise((res) => {
+    const p = spawn("ffmpeg", ["-hide_banner", "-y", "-loglevel", "error", ...args], {
+      stdio: ["ignore", "ignore", "inherit"],
+    });
+    p.on("close", (code) => res(code === 0));
+  });
+}
+
+// WORLD-vocoder hard tune (pop/bin/pitchsnap_world.py): replace the f0
+// curve with the target note so sung melisma actually SITS on the melody.
+// retain 0.85 keeps 15% of the original movement; light vibrato for life.
+// applied to the sung groups (america/dora) — TTS is already flat and the
+// whisper twins have no pitch to tune.
+const TUNE_GROUPS = new Set(["america", "dora"]);
+const PY = join(ROOT, "..", ".venv", "bin", "python3");
+const PITCHSNAP = join(ROOT, "..", "bin", "pitchsnap_world.py");
+function tuneAsync(wav, noteName) {
+  return new Promise((res) => {
+    const p = spawn(PY, [
+      PITCHSNAP, wav, wav, "--notes", noteName,
+      "--retain", "0.85", "--vibrato-hz", "5.2", "--vibrato-cents", "14",
+    ], { stdio: ["ignore", "ignore", "inherit"] });
+    p.on("close", (code) => res(code === 0));
+  });
+}
+async function pool(jobs, width = 4) {
+  let i = 0, done = 0, fail = 0;
+  const workers = Array.from({ length: width }, async () => {
+    while (i < jobs.length) {
+      const job = jobs[i++];
+      const ok = await job();
+      if (ok) done++; else fail++;
+      if ((done + fail) % 50 === 0) console.log(`  … ${done + fail}/${jobs.length}`);
+    }
+  });
+  await Promise.all(workers);
+  return { done, fail };
+}
+
+// what does each utterance actually SAY? cross-reference clips.json spans
+// against the sources' word-level transcripts (<src>-words.json, fromMs/toMs)
+// so the audition page can show "do" vs "Dora" at a glance.
+function transcripts() {
+  const clipsPath = join(ROOT, "clips.json");
+  if (!existsSync(clipsPath)) return {};
+  const byName = {};
+  for (const c of JSON.parse(readFileSync(clipsPath, "utf8"))) {
+    if (c.start == null || c.end == null) continue;
+    const srcBase = basename(c.source, ".mp3");
+    const wordsPath = join(ROOT, dirname(c.source), `${srcBase}-words.json`);
+    if (!existsSync(wordsPath)) continue;
+    const wl = JSON.parse(readFileSync(wordsPath, "utf8"));
+    const text = wl
+      .filter((w) => w.fromMs / 1000 < c.end && w.toMs / 1000 > c.start && w.text !== "♪")
+      .map((w) => w.text).join(" ");
+    const tag = c.tag.toLowerCase().replace(/[^a-z0-9]+/g, "-").replace(/^-|-$/g, "");
+    byName[`${srcBase}-${tag}`] = text || null;
+  }
+  return byName;
+}
+
+// ── build: snap every utterance to every target note (+ whisper twin) ──
+async function build() {
+  const saidBy = transcripts();
+  // each slot's needed notes come straight from the hook variants
+  const targets = {};
+  for (let w = 0; w < melody.hook.words.length; w++) {
+    targets[melody.hook.words[w]] = [...new Set(melody.hook.variants.map((v) => v.notes[w]))];
+  }
+  console.log("# snap targets per slot:");
+  for (const g of GROUPS) console.log(`  ${g}: ${targets[g].map(midiName).join(" ")}`);
+
+  const manifest = { sr: SR, groups: {} };
+  const jobs = [];
+  for (const g of GROUPS) {
+    const srcDir = join(ROOT, "utterances", g);
+    const outDir = join(ROOT, "snapped", g);
+    mkdirSync(outDir, { recursive: true });
+    manifest.groups[g] = [];
+    if (!existsSync(srcDir)) continue;
+    const files = readdirSync(srcDir).filter((f) => f.endsWith(".wav")).sort();
+    for (const f of files) {
+      const abs = join(srcDir, f);
+      const name = basename(f, ".wav");
+      let srcHz = null, srcMidi = null, dur = null;
+      try {
+        const { samples } = readWavMono(abs);
+        srcHz = detectPitchHz(samples, SR);
+        srcMidi = srcHz ? hzToMidi(srcHz) : null;
+        dur = +(samples.length / SR).toFixed(3);
+      } catch {}
+      const entry = {
+        name, src: `utterances/${g}/${f}`, srcHz, srcMidi, dur,
+        word: saidBy[name] ?? (g === "computer" ? "computer" : null),
+        notes: {}, whisper: {},
+      };
+      for (const t of targets[g]) {
+        const outRel = `snapped/${g}/${name}__t${t}.wav`;
+        const whRel = `snapped/${g}/${name}__t${t}__w.wav`;
+        entry.notes[t] = outRel;
+        entry.whisper[t] = whRel;
+        const outAbs = join(ROOT, outRel);
+        const whAbs = join(ROOT, whRel);
+        // fold the shift by octaves so we never stretch more than ±6 semis —
+        // an octave-equivalent landing keeps the voice human.
+        let semis = 0;
+        if (srcMidi != null) {
+          semis = t - srcMidi;
+          while (semis > 6) semis -= 12;
+          while (semis < -6) semis += 12;
+        }
+        const ratio = Math.pow(2, semis / 12);
+        const shift = Math.abs(semis) < 0.01
+          ? ""
+          : `asetrate=${SR}*${ratio},aresample=${SR},${chainAtempo(1 / ratio)},`;
+        if (!existsSync(outAbs)) {
+          const noteName = midiName(t);
+          jobs.push(() => ffmpegAsync([
+            "-i", abs, "-af", `${shift}loudnorm=I=-15:TP=-1.2`, "-ac", "1", "-ar", String(SR), outAbs,
+          ]).then((ok) => (ok && TUNE_GROUPS.has(g) ? tuneAsync(outAbs, noteName) : ok)));
+        }
+        if (!existsSync(whAbs)) {
+          jobs.push(() => ffmpegAsync([
+            "-i", abs, "-af", `${shift}${WHISPER},loudnorm=I=-16:TP=-1.5`, "-ac", "1", "-ar", String(SR), whAbs,
+          ]));
+        }
+      }
+      manifest.groups[g].push(entry);
+    }
+  }
+
+  const counts = GROUPS.map((g) => `${g} ${manifest.groups[g].length}`).join(" · ");
+  const comboCount = GROUPS.reduce((a, g) => a * (manifest.groups[g].length || 1), 1);
+  console.log(`\n# utterances: ${counts}`);
+  console.log(`# phrase combinations available: ${comboCount.toLocaleString()} (× ${melody.hook.variants.length} melody variants × whisper toggles)`);
+  console.log(`# rendering ${jobs.length} snapped wavs (cached files skipped)…`);
+  const { done, fail } = await pool(jobs);
+  console.log(`  ✓ ${done} rendered${fail ? `, ✗ ${fail} FAILED` : ""}`);
+
+  writeFileSync(join(ROOT, "hooks.json"), JSON.stringify(manifest, null, 2));
+  console.log("✓ hooks.json");
+}
+
+// ── page: hooks.html — every combination, instantly playable ───────────
+function page() {
+  const html = `<!doctype html>
+<meta charset="utf-8">
+<title>americomputadora · hooks</title>
+<style>
+  :root { color-scheme: dark; }
+  body { background:#0a0a12; color:#eee; font:14px/1.45 "Berkeley Mono", ui-monospace, monospace; margin:0; }
+  header { position:sticky; top:0; background:#0a0a12ee; border-bottom:1px solid #223; padding:10px 16px; z-index:5;
+           display:flex; gap:10px; align-items:center; flex-wrap:wrap; }
+  h1 { font-size:15px; margin:0 8px 0 0; color:#7df9ff; font-weight:normal; }
+  button { background:#16213e; color:#eee; border:1px solid #335; border-radius:6px; padding:6px 12px;
+           font:inherit; cursor:pointer; }
+  button:hover { background:#1f2d52; }
+  button.big { background:#e94560; border-color:#e94560; font-weight:bold; }
+  button.big:hover { background:#ff5d77; }
+  select { background:#16213e; color:#eee; border:1px solid #335; border-radius:6px; padding:5px 8px; font:inherit; }
+  label.tog { display:flex; gap:4px; align-items:center; color:#9af; cursor:pointer; }
+  main { display:grid; grid-template-columns:1fr 1fr 1fr; gap:0; }
+  .col { border-right:1px solid #181830; min-height:60vh; }
+  .col h2 { position:sticky; top:52px; margin:0; padding:8px 12px; background:#11112255; backdrop-filter:blur(6px);
+            font-size:13px; letter-spacing:2px; text-transform:uppercase; }
+  .col.america h2 { color:#ff6b6b; } .col.computer h2 { color:#7df9ff; } .col.dora h2 { color:#ffd93d; }
+  .clip { padding:4px 12px; cursor:pointer; display:flex; gap:8px; align-items:baseline; white-space:nowrap;
+          overflow:hidden; text-overflow:ellipsis; }
+  .clip:hover { background:#181830; }
+  .clip.sel { background:#23234d; outline:1px solid #447; }
+  .clip .hz { color:#667; font-size:11px; margin-left:auto; }
+  .clip .said { color:#9c8; font-size:12px; font-style:italic; }
+  .clip .pv { color:#557; }
+  .clip .pv:hover { color:#9af; }
+  footer { position:sticky; bottom:0; background:#0a0a12ee; border-top:1px solid #223; padding:10px 16px;
+           display:flex; gap:14px; align-items:center; flex-wrap:wrap; }
+  #now { color:#ffd93d; min-width:280px; }
+  #favs { padding:8px 16px 60px; }
+  #favs .fav { display:flex; gap:10px; padding:3px 0; align-items:baseline; }
+  #favs .fav button { padding:2px 8px; }
+  .keys { color:#556; font-size:12px; }
+</style>
+<header>
+  <h1>americomputadora · ${"${COMBOS}"} combinations</h1>
+  <button class="big" id="play">▶ play (space)</button>
+  <button id="surf">🎲 surf (s)</button>
+  <button id="fav">★ keep (f)</button>
+  <select id="variant"></select>
+  <label class="tog"><input type="checkbox" id="wa"> whisper america</label>
+  <label class="tog"><input type="checkbox" id="wc"> whisper computer</label>
+  <label class="tog"><input type="checkbox" id="wd"> whisper dora</label>
+  <label class="tog"><input type="checkbox" id="grid" checked> beat grid</label>
+  <span class="keys">↑↓ america · ←→ computer · ,/. dora</span>
+</header>
+<main>
+  <div class="col america"><h2>america</h2><div id="list-america"></div></div>
+  <div class="col computer"><h2>computer</h2><div id="list-computer"></div></div>
+  <div class="col dora"><h2>dora</h2><div id="list-dora"></div></div>
+</main>
+<footer>
+  <span id="now">pick clips, hit space.</span>
+  <button id="export">⇩ export favorites json</button>
+  <span class="keys" id="favcount"></span>
+</footer>
+<div id="favs"></div>
+<script>
+const GROUPS = ["america", "computer", "dora"];
+let M = null, H = null;            // melody.json, hooks.json
+const ctx = new (window.AudioContext || window.webkitAudioContext)();
+const cache = new Map();           // path → AudioBuffer
+const sel = { america: 0, computer: 0, dora: 0 };
+let favs = JSON.parse(localStorage.getItem("acd-hook-favs") || "[]");
+
+async function buf(path) {
+  if (cache.has(path)) return cache.get(path);
+  const ab = await (await fetch("/" + path)).arrayBuffer();
+  const b = await ctx.decodeAudioData(ab);
+  cache.set(path, b);
+  return b;
+}
+
+function whisperOn(g) {
+  return document.getElementById("w" + g[0]).checked;
+}
+function curVariant() {
+  return M.hook.variants[+document.getElementById("variant").value];
+}
+function comboDesc() {
+  const v = curVariant();
+  return GROUPS.map((g, i) =>
+    H.groups[g][sel[g]].name + (whisperOn(g) ? "·w" : "") ).join("  +  ") + "   [" + v.label + "]";
+}
+
+// play three paths as ONE merged phrase — each word crossfades into the
+// next on the beat grid ("america aaaaawwwmputerrrrr dora!"). off-grid =
+// plain back-to-back stitch.
+async function playPhrase(paths) {
+  await ctx.resume();
+  const beat = 60 / M.bpm;
+  const onGrid = document.getElementById("grid").checked;
+  const t0 = ctx.currentTime + 0.06;
+  const onsets = [0];
+  for (let i = 0; i < paths.length - 1; i++) onsets.push(onsets[i] + M.hook.beats_per_word[i] * beat);
+  const phraseEnd = onsets[paths.length - 1] + M.hook.beats_per_word[paths.length - 1] * beat;
+  let tight = t0;
+  for (let i = 0; i < paths.length; i++) {
+    const b = await buf(paths[i]);
+    const src = ctx.createBufferSource();
+    src.buffer = b;
+    if (!onGrid) {
+      src.connect(ctx.destination);
+      src.start(tight);
+      tight += b.duration;
+      continue;
+    }
+    // layered merge — every word finishes: it ducks (not dies) when the
+    // next word enters, and is only choked one word later. dora rings hot.
+    const gn = ctx.createGain();
+    src.connect(gn); gn.connect(ctx.destination);
+    const at = t0 + onsets[i];
+    const last = i === paths.length - 1;
+    if (i > 0) { gn.gain.setValueAtTime(0, at); gn.gain.linearRampToValueAtTime(last ? 1.15 : 1, at + (last ? 0.008 : 0.05)); }
+    else gn.gain.setValueAtTime(1, at);
+    if (last) {
+      const fadeAt = t0 + phraseEnd + 0.06;
+      gn.gain.setValueAtTime(1.15, fadeAt);
+      gn.gain.linearRampToValueAtTime(0, fadeAt + 0.22);
+      src.start(at); src.stop(fadeAt + 0.4);
+    } else {
+      const duckAt = t0 + onsets[i + 1] - 0.06;
+      const chokeAt = (i + 2 < paths.length ? t0 + onsets[i + 2] : t0 + phraseEnd) - 0.06;
+      gn.gain.setValueAtTime(1, Math.max(duckAt, at + 0.06));
+      gn.gain.linearRampToValueAtTime(i === 0 ? 0.38 : 0.30, duckAt + 0.20);
+      gn.gain.setValueAtTime(i === 0 ? 0.38 : 0.30, chokeAt);
+      gn.gain.linearRampToValueAtTime(0, chokeAt + 0.22);
+      src.start(at); src.stop(chokeAt + 0.4);
+    }
+  }
+}
+
+async function play() {
+  const v = curVariant();
+  await playPhrase(GROUPS.map((g, i) => {
+    const e = H.groups[g][sel[g]];
+    return whisperOn(g) ? e.whisper[v.notes[i]] : e.notes[v.notes[i]];
+  }));
+  document.getElementById("now").textContent = "▶ " + comboDesc();
+}
+
+function preview(g, i) {
+  const v = curVariant();
+  const e = H.groups[g][i];
+  const note = v.notes[GROUPS.indexOf(g)];
+  const path = whisperOn(g) ? e.whisper[note] : e.notes[note];
+  buf(path).then((b) => {
+    const src = ctx.createBufferSource();
+    src.buffer = b; src.connect(ctx.destination); src.start();
+  });
+}
+
+function renderLists() {
+  for (const g of GROUPS) {
+    const root = document.getElementById("list-" + g);
+    root.innerHTML = "";
+    H.groups[g].forEach((e, i) => {
+      const d = document.createElement("div");
+      d.className = "clip" + (sel[g] === i ? " sel" : "");
+      const said = e.word ? '“' + e.word + '” ' : "";
+      d.innerHTML = '<span class="pv">▶</span> ' + e.name + ' <span class="said">' + said + '</span>' +
+        '<span class="hz">' + (e.dur ? e.dur.toFixed(1) + "s · " : "") + (e.srcHz ? e.srcHz.toFixed(0) + "hz" : "—") + "</span>";
+      d.onclick = (ev) => {
+        sel[g] = i; renderLists();
+        if (ev.target.classList.contains("pv")) preview(g, i); else play();
+      };
+      root.appendChild(d);
+    });
+  }
+  document.getElementById("favcount").textContent = favs.length + " kept";
+}
+
+function surf() {
+  for (const g of GROUPS) sel[g] = Math.floor(Math.random() * H.groups[g].length);
+  document.getElementById("variant").value = Math.floor(Math.random() * M.hook.variants.length);
+  for (const g of GROUPS) document.getElementById("w" + g[0]).checked = Math.random() < 0.25;
+  renderLists();
+  document.querySelectorAll(".clip.sel").forEach((el) => el.scrollIntoView({ block: "nearest" }));
+  play();
+}
+
+function keep() {
+  const v = curVariant();
+  favs.push({
+    variant: +document.getElementById("variant").value,
+    label: v.label,
+    picks: Object.fromEntries(GROUPS.map((g, i) => [g, {
+      name: H.groups[g][sel[g]].name,
+      note: v.notes[i],
+      whisper: whisperOn(g),
+      path: whisperOn(g) ? H.groups[g][sel[g]].whisper[v.notes[i]] : H.groups[g][sel[g]].notes[v.notes[i]],
+    }])),
+  });
+  localStorage.setItem("acd-hook-favs", JSON.stringify(favs));
+  renderFavs(); renderLists();
+}
+
+function renderFavs() {
+  const root = document.getElementById("favs");
+  root.innerHTML = favs.length ? "<h3>★ kept</h3>" : "";
+  favs.forEach((f, i) => {
+    const d = document.createElement("div");
+    d.className = "fav";
+    const desc = GROUPS.map((g) => f.picks[g].name + (f.picks[g].whisper ? "·w" : "")).join(" + ") + " [" + f.label + "]";
+    d.innerHTML = "<button>▶</button><button>✕</button><span>" + desc + "</span>";
+    const [pb, xb] = d.querySelectorAll("button");
+    pb.onclick = () => playPhrase(GROUPS.map((g) => f.picks[g].path));
+    xb.onclick = () => { favs.splice(i, 1); localStorage.setItem("acd-hook-favs", JSON.stringify(favs)); renderFavs(); renderLists(); };
+    root.appendChild(d);
+  });
+}
+
+document.getElementById("play").onclick = play;
+document.getElementById("surf").onclick = surf;
+document.getElementById("fav").onclick = keep;
+document.getElementById("export").onclick = () => {
+  const a = document.createElement("a");
+  a.href = URL.createObjectURL(new Blob([JSON.stringify(favs, null, 2)], { type: "application/json" }));
+  a.download = "hooks-favorites.json";
+  a.click();
+};
+const CYCLE = { arrowup: ["america", -1], arrowdown: ["america", 1], arrowleft: ["computer", -1],
+                arrowright: ["computer", 1], ",": ["dora", -1], ".": ["dora", 1] };
+document.addEventListener("keydown", (e) => {
+  if (e.target.tagName === "INPUT" || e.target.tagName === "SELECT") return;
+  const k = e.key.toLowerCase();
+  if (k === " ") { e.preventDefault(); play(); }
+  else if (k === "s") surf();
+  else if (k === "f") keep();
+  else if (CYCLE[k]) {
+    e.preventDefault();
+    const [g, d] = CYCLE[k];
+    sel[g] = (sel[g] + d + H.groups[g].length) % H.groups[g].length;
+    renderLists();
+    document.querySelectorAll(".clip.sel").forEach((el) => el.scrollIntoView({ block: "nearest" }));
+    play();
+  }
+});
+
+Promise.all([fetch("/melody.json").then((r) => r.json()), fetch("/hooks.json").then((r) => r.json())])
+  .then(([m, h]) => {
+    M = m; H = h;
+    const vs = document.getElementById("variant");
+    M.hook.variants.forEach((v, i) => {
+      const o = document.createElement("option");
+      o.value = i; o.textContent = i + " · " + v.label;
+      vs.appendChild(o);
+    });
+    renderLists(); renderFavs();
+  });
+</script>
+`;
+  // bake the combo count into the title
+  let combos = "?";
+  const hooksPath = join(ROOT, "hooks.json");
+  if (existsSync(hooksPath)) {
+    const h = JSON.parse(readFileSync(hooksPath, "utf8"));
+    combos = GROUPS.reduce((a, g) => a * (h.groups[g]?.length || 1), 1).toLocaleString();
+  }
+  writeFileSync(join(ROOT, "hooks.html"), html.replace("${COMBOS}", combos));
+  console.log(`✓ hooks.html (${combos} combos) — node bin/serve.mjs, then open /hooks.html`);
+}
+
+// ── flight: stitch a batch of random combos to mp3 ──────────────────────
+function mulberry32(seed) {
+  let a = seed >>> 0;
+  return () => {
+    a |= 0; a = (a + 0x6d2b79f5) | 0;
+    let t = Math.imul(a ^ (a >>> 15), 1 | a);
+    t = (t + Math.imul(t ^ (t >>> 7), 61 | t)) ^ t;
+    return ((t ^ (t >>> 14)) >>> 0) / 4294967296;
+  };
+}
+
+function stitchCombo(picks, outAbs, { title }) {
+  // picks: [{path}, {path}, {path}] — already snapped to target notes.
+  // mixed as ONE merged phrase on the beat grid: each word crossfades into
+  // the next ("america aaaaawwwmputerrrrr dora!"), dora choked at the bar.
+  const beat = 60 / melody.bpm;
+  const lens = melody.hook.beats_per_word;
+  const onsets = [0];
+  for (let i = 0; i < picks.length - 1; i++) onsets.push(onsets[i] + lens[i] * beat);
+  const phraseEnd = onsets[picks.length - 1] + lens[picks.length - 1] * beat;
+  const N = Math.ceil((phraseEnd + 0.45) * SR);
+  const mix = new Float32Array(N);
+  picks.forEach((p, i) => {
+    const { samples } = readWavMono(join(ROOT, p.path));
+    const last = i === picks.length - 1;
+    const attack = i === 0 ? 0 : last ? 0.008 : 0.05;
+    const gain = last ? 1.15 : 1;
+    // layered merge (clip-relative): duck under the next word, choke one
+    // word later; dora rings hot past the phrase end.
+    const duckAt = last ? Infinity : onsets[i + 1] - 0.06 - onsets[i];
+    const duckTo = i === 0 ? 0.38 : 0.30;
+    const chokeAt = last
+      ? phraseEnd + 0.06 - onsets[i]
+      : (i + 2 < picks.length ? onsets[i + 2] : phraseEnd) - 0.06 - onsets[i];
+    const chokeOver = 0.22;
+    const s0 = Math.floor(onsets[i] * SR);
+    for (let j = 0; j < samples.length; j++) {
+      const tt = j / SR;
+      let lvl = attack > 0 && tt < attack ? tt / attack : 1;
+      if (tt >= duckAt) lvl *= Math.max(duckTo, 1 - ((tt - duckAt) / 0.20) * (1 - duckTo));
+      if (tt >= chokeAt) lvl *= Math.max(0, 1 - (tt - chokeAt) / chokeOver);
+      if (tt > chokeAt + chokeOver) break;
+      const k = s0 + j;
+      if (k < N) mix[k] += samples[j] * lvl * gain;
+    }
+  });
+  let peak = 0;
+  for (let i = 0; i < N; i++) { const a = Math.abs(mix[i]); if (a > peak) peak = a; }
+  if (peak > 1) for (let i = 0; i < N; i++) mix[i] /= peak;
+  const rawPath = join(tmpdir(), `acd-hooks-${process.pid}-${Math.random().toString(36).slice(2, 8)}.f32.raw`);
+  const b = Buffer.alloc(N * 4);
+  for (let i = 0; i < N; i++) b.writeFloatLE(mix[i], i * 4);
+  writeFileSync(rawPath, b);
+  const ok = spawnSync("ffmpeg", [
+    "-hide_banner", "-y", "-loglevel", "error",
+    "-f", "f32le", "-ar", String(SR), "-ac", "1", "-i", rawPath,
+    "-c:a", "libmp3lame", "-q:a", "2",
+    "-metadata", `title=${title}`,
+    "-metadata", "artist=jeffrey",
+    "-metadata", "album=pixsies",
+    outAbs,
+  ], { stdio: ["ignore", "ignore", "inherit"] }).status === 0;
+  try { unlinkSync(rawPath); } catch {}
+  return ok;
+}
+
+function flight() {
+  const H = JSON.parse(readFileSync(join(ROOT, "hooks.json"), "utf8"));
+  const count = Number(flags.count ?? 24);
+  const rand = mulberry32(Number(flags.seed ?? Date.now()) | 0);
+  const outDir = join(ROOT, "out", "hooks");
+  mkdirSync(outDir, { recursive: true });
+  console.log(`# flight — ${count} random combos → out/hooks/`);
+  const made = [];
+  for (let i = 0; i < count; i++) {
+    const vIdx = flags.variant !== undefined ? Number(flags.variant) : Math.floor(rand() * melody.hook.variants.length);
+    const v = melody.hook.variants[vIdx];
+    const picks = GROUPS.map((g, w) => {
+      const e = H.groups[g][Math.floor(rand() * H.groups[g].length)];
+      const whisper = flags.whisper ? true : rand() < 0.2;
+      return { name: e.name, whisper, path: whisper ? e.whisper[v.notes[w]] : e.notes[v.notes[w]] };
+    });
+    const slug = picks.map((p) => p.name + (p.whisper ? "w" : "")).join("__");
+    const out = join(outDir, `${String(i + 1).padStart(2, "0")}__v${vIdx}__${slug}.mp3`);
+    if (stitchCombo(picks, out, { title: `americomputadora hook ${i + 1} (${v.label})` })) {
+      made.push(out);
+      console.log(`  ✓ ${basename(out)}`);
+    }
+  }
+  // one contact-sheet mp3: every combo back-to-back with a breath between
+  if (made.length) {
+    const listPath = join(tmpdir(), `acd-flight-${process.pid}.txt`);
+    const silence = join(tmpdir(), `acd-flight-sil-${process.pid}.mp3`);
+    spawnSync("ffmpeg", ["-hide_banner", "-y", "-loglevel", "error",
+      "-f", "lavfi", "-i", `anullsrc=r=${SR}:cl=mono`, "-t", "0.7",
+      "-c:a", "libmp3lame", "-q:a", "2", silence], { stdio: "ignore" });
+    writeFileSync(listPath, made.flatMap((m) => [`file '${m}'`, `file '${silence}'`]).join("\n") + "\n");
+    const all = join(outDir, "_flight-all.mp3");
+    spawnSync("ffmpeg", ["-hide_banner", "-y", "-loglevel", "error",
+      "-f", "concat", "-safe", "0", "-i", listPath, "-ac", "1", "-ar", String(SR),
+      "-c:a", "libmp3lame", "-q:a", "2", all], { stdio: ["ignore", "ignore", "inherit"] });
+    try { unlinkSync(listPath); unlinkSync(silence); } catch {}
+    console.log(`\n✓ ${all}  (all ${made.length} in one listen)`);
+  }
+}
+
+// ── render favorites exported from hooks.html ───────────────────────────
+function renderFavs() {
+  const favPath = resolve(flags.fav ?? join(ROOT, "hooks-favorites.json"));
+  if (!existsSync(favPath)) {
+    console.error(`✗ no favorites file at ${favPath} — export from hooks.html first`);
+    process.exit(1);
+  }
+  const favs = JSON.parse(readFileSync(favPath, "utf8"));
+  const outDir = join(ROOT, "out", "hooks");
+  mkdirSync(outDir, { recursive: true });
+  favs.forEach((f, i) => {
+    const picks = GROUPS.map((g) => f.picks[g]);
+    const slug = picks.map((p) => p.name + (p.whisper ? "w" : "")).join("__");
+    const out = join(outDir, `fav-${String(i + 1).padStart(2, "0")}__${f.label}__${slug}.mp3`);
+    if (stitchCombo(picks, out, { title: `americomputadora fav ${i + 1} (${f.label})` })) {
+      console.log(`  ✓ ${basename(out)}`);
+    }
+  });
+}
+
+// ── main ────────────────────────────────────────────────────────────────
+if (cmd === "build") await build();
+else if (cmd === "page") page();
+else if (cmd === "flight") flight();
+else if (cmd === "render") renderFavs();
+else { await build(); page(); }
diff --git a/pop/americomputadora/c/americomputadora.c b/pop/americomputadora/c/americomputadora.c
new file mode 100644
index 000000000..b178e18b5
--- /dev/null
+++ b/pop/americomputadora/c/americomputadora.c
@@ -0,0 +1,869 @@
+// americomputadora.c — C engine for the americomputadora track, following
+// the hellsine pattern (pop/hellsine/c): JS bakes vocals + score.h, this
+// renders the full song to a float32 WAV; acdsp masters it; ffmpeg only
+// encodes mp3 at the very end.
+//
+// Faithful port of bin/render.mjs (rock-ballad / ramp era, 2026-06-09):
+// phase-increment synths, layered-merge vocal envelopes with the 0.3 s
+// america↔computer blend, percussion intensity ramp, sidechain duck,
+// dotted-8th vocal echo, Schroeder reverb, tanh master.
+//
+// Build:  ./build.sh         Run:  ./americomputadora --out out/c.wav
+
+#define _POSIX_C_SOURCE 200809L
+#include <stdio.h>
+#include <stdlib.h>
+#include <stdint.h>
+#include <string.h>
+#include <math.h>
+
+#ifndef M_PI
+#define M_PI 3.14159265358979323846
+#endif
+#define TAU (2.0 * M_PI)
+
+#include "score.h"
+
+static const int SR = 48000;
+static double BEAT, BAR;
+
+// ── deterministic RNG (xorshift32) — noise voices stay reproducible ────
+static uint32_t rng_s = 0x41435f5f; // "AC__"
+static inline double rng(void) {
+    rng_s ^= rng_s << 13; rng_s ^= rng_s >> 17; rng_s ^= rng_s << 5;
+    return (double)rng_s / 4294967296.0;
+}
+static inline double rnd2(void) { return rng() * 2.0 - 1.0; } // -1..1
+
+static inline double midi_hz(double m) { return 440.0 * pow(2.0, (m - 69.0) / 12.0); }
+
+// ── buffers ─────────────────────────────────────────────────────────────
+static long N;
+static float *drm, *kik, *snr, *bel, *sqr, *sb, *toy, *arp, *pds, *cho, *voc;
+
+static inline void addb(float *buf, long i, double v) {
+    if (i >= 0 && i < N) buf[i] += (float)v;
+}
+
+// ── wav io ──────────────────────────────────────────────────────────────
+// reads mono PCM16 or float32 wav (the baked vocals are float32 48k mono).
+static float *load_wav_mono(const char *path, long *out_n) {
+    FILE *f = fopen(path, "rb");
+    if (!f) { fprintf(stderr, "  ! missing %s\n", path); return NULL; }
+    uint8_t hdr[12];
+    if (fread(hdr, 1, 12, f) != 12 || memcmp(hdr, "RIFF", 4) || memcmp(hdr + 8, "WAVE", 4)) {
+        fclose(f); return NULL;
+    }
+    uint16_t fmt = 0, ch = 1, bits = 16;
+    float *out = NULL; long n = 0;
+    for (;;) {
+        uint8_t ck[8];
+        if (fread(ck, 1, 8, f) != 8) break;
+        uint32_t sz = ck[4] | (ck[5] << 8) | (ck[6] << 16) | ((uint32_t)ck[7] << 24);
+        if (!memcmp(ck, "fmt ", 4)) {
+            uint8_t b[16];
+            fread(b, 1, 16, f);
+            fmt = b[0] | (b[1] << 8); ch = b[2] | (b[3] << 8); bits = b[14] | (b[15] << 8);
+            if (sz > 16) fseek(f, sz - 16, SEEK_CUR);
+        } else if (!memcmp(ck, "data", 4)) {
+            long frames = sz / (bits / 8) / ch;
+            out = malloc(sizeof(float) * frames);
+            n = frames;
+            for (long i = 0; i < frames; i++) {
+                double acc = 0;
+                for (int c = 0; c < ch; c++) {
+                    if (fmt == 3 && bits == 32) {
+                        float v; fread(&v, 4, 1, f); acc += v;
+                    } else {
+                        int16_t v; fread(&v, 2, 1, f); acc += v / 32768.0;
+                    }
+                }
+                out[i] = (float)(acc / ch);
+            }
+            break;
+        } else {
+            fseek(f, sz + (sz & 1), SEEK_CUR);
+        }
+    }
+    fclose(f);
+    *out_n = n;
+    return out;
+}
+
+static int write_wav_f32(const char *path, const float *s, long n) {
+    FILE *f = fopen(path, "wb");
+    if (!f) return 0;
+    uint32_t dsz = (uint32_t)(n * 4), riff = 36 + dsz, sr = SR, br = SR * 4;
+    uint16_t fmt = 3, ch = 1, ba = 4, bits = 32;
+    fwrite("RIFF", 1, 4, f); fwrite(&riff, 4, 1, f); fwrite("WAVE", 1, 4, f);
+    fwrite("fmt ", 1, 4, f); uint32_t fsz = 16; fwrite(&fsz, 4, 1, f);
+    fwrite(&fmt, 2, 1, f); fwrite(&ch, 2, 1, f); fwrite(&sr, 4, 1, f);
+    fwrite(&br, 4, 1, f); fwrite(&ba, 2, 1, f); fwrite(&bits, 2, 1, f);
+    fwrite("data", 1, 4, f); fwrite(&dsz, 4, 1, f);
+    fwrite(s, 4, n, f);
+    fclose(f);
+    return 1;
+}
+
+// ── vocal cache: load each baked wav once. three treatment tiers ramp
+// with the song: 0 = raw stitch, 1 = autotuned, 2 = full character.
+typedef struct { float *s; long n; } Clip;
+static Clip clips[3][N_WORDS][MAX_ROSTER][N_VARIANTS];
+static const char *voc_base = "";
+
+static Clip syl_cache[2][N_SYL ? N_SYL : 1][N_SYLT];
+static Clip *get_syl(int voice, int si, int ti) {
+#if N_SYL > 0
+    Clip *c = &syl_cache[voice][si][ti];
+    if (!c->s) {
+        char path[512];
+        const char *rel = voice ? SYL_PATHS_C[si][ti] : SYL_PATHS[si][ti];
+        snprintf(path, sizeof path, "%s%s", voc_base, rel);
+        c->s = load_wav_mono(path, &c->n);
+    }
+    return c->s ? c : NULL;
+#else
+    (void)voice; (void)si; (void)ti; return NULL;
+#endif
+}
+
+static Clip *get_clip(int tier, int w, int r, int v) {
+    if (tier == 0) v = 0; // raw tier is variant-independent
+    Clip *c = &clips[tier][w][r][v];
+    if (!c->s) {
+        const char *rel = tier == 0 ? VOC_RAW[w][r]
+                       : tier == 1 ? VOC_PLAIN[w][r][v]
+                       : VOC_FULL[w][r][v];
+        char path[512];
+        snprintf(path, sizeof path, "%s%s", voc_base, rel);
+        c->s = load_wav_mono(path, &c->n);
+    }
+    return c->s ? c : NULL;
+}
+
+// ── synth voices (ports of render.mjs, same constants) ─────────────────
+static void kick(float *buf, double t, double g) {
+    int n = (int)(0.18 * SR); long s0 = (long)(t * SR);
+    double ph = 0;
+    for (int i = 0; i < n; i++) {
+        double tt = (double)i / SR;
+        double f = 55 + (140 - 55) * exp(-tt * 38);
+        ph += TAU * f / SR;
+        double body = sin(ph) * exp(-tt * 11);
+        double click = i < SR * 0.002 ? rnd2() * 0.4 * (1 - i / (SR * 0.002)) : 0;
+        addb(buf, s0 + i, (body + click) * g);
+    }
+}
+
+static void kick_serious(float *buf, double t, double g) {
+    int n = (int)(0.32 * SR); long s0 = (long)(t * SR);
+    double ph = 0;
+    for (int i = 0; i < n; i++) {
+        double tt = (double)i / SR;
+        double f = 42 + (190 - 42) * exp(-tt * 30);
+        ph += TAU * f / SR;
+        double body = tanh(sin(ph) * 2.4) * exp(-tt * 7.5);
+        double click = i < SR * 0.003 ? rnd2() * 0.6 * (1 - i / (SR * 0.003)) : 0;
+        addb(buf, s0 + i, (body + click) * g);
+    }
+}
+
+static void snare_hit(float *buf, double t, double g) {
+    int n = (int)(0.22 * SR); long s0 = (long)(t * SR);
+    double prev = 0, ph = 0;
+    for (int i = 0; i < n; i++) {
+        double tt = (double)i / SR;
+        double nz = rnd2();
+        double hp = nz - prev; prev = nz;
+        ph += TAU * 190 / SR;
+        double body = sin(ph) * exp(-tt * 30) * 0.7;
+        addb(buf, s0 + i, (hp * exp(-tt * 24) + body) * g);
+    }
+}
+
+static void clap(float *buf, double t, double g) {
+    for (int b = 0; b < 4; b++) {
+        double bt = t + b * 0.007;
+        long s0 = (long)(bt * SR); int n = (int)(0.012 * SR);
+        double prev = 0;
+        for (int i = 0; i < n; i++) {
+            double nz = rnd2();
+            double hp = nz - prev; prev = nz;
+            addb(buf, s0 + i, hp * exp(-((double)i / SR) * 120) * g * (b == 3 ? 1.0 : 0.55));
+        }
+    }
+    long s0 = (long)(t * SR); int tail = (int)(0.13 * SR);
+    double prev = 0;
+    for (int i = 0; i < tail; i++) {
+        double nz = rnd2();
+        double hp = nz - prev; prev = nz;
+        addb(buf, s0 + i, hp * exp(-((double)i / SR) * 22) * g * 0.18);
+    }
+}
+
+static void tamb(float *buf, double t, double g) {
+    int n = (int)(0.05 * SR); long s0 = (long)(t * SR);
+    double prev = 0;
+    for (int i = 0; i < n; i++) {
+        double nz = rnd2();
+        double hp = nz - prev; prev = nz;
+        addb(buf, s0 + i, hp * exp(-((double)i / SR) * 80) * g);
+    }
+}
+
+static void crash(float *buf, double t, double g) {
+    int n = (int)(1.4 * SR); long s0 = (long)(t * SR);
+    double prev = 0;
+    for (int i = 0; i < n; i++) {
+        double nz = rnd2();
+        double hp = nz - prev; prev = nz;
+        addb(buf, s0 + i, hp * exp(-((double)i / SR) * 3.2) * g);
+    }
+}
+
+static void bell(float *buf, double t, double midi, double dur, double g) {
+    double fc = midi_hz(midi), fm = fc * 3.5;
+    int n = (int)(dur * SR); long s0 = (long)(t * SR);
+    double phc = 0, phm = 0;
+    for (int i = 0; i < n; i++) {
+        double tt = (double)i / SR;
+        double env = exp(-tt * 5.5);
+        double mi = 4.5 * exp(-tt * 9);
+        phm += TAU * fm / SR;
+        phc += TAU * fc / SR + sin(phm) * mi / SR;
+        addb(buf, s0 + i, sin(phc) * env * g);
+    }
+}
+
+static void sine_lead(float *buf, double t, double midi, double dur, double g) {
+    double f = midi_hz(midi);
+    int n = (int)(dur * SR); long s0 = (long)(t * SR);
+    int att = (int)(0.05 * SR), rel = (int)(0.12 * SR);
+    double ph = 0;
+    for (int i = 0; i < n; i++) {
+        double tt = (double)i / SR;
+        double vib = tt > 0.25 ? sin(TAU * 5.2 * tt) * 0.004 * fmin(1, (tt - 0.25) * 3) : 0;
+        ph += TAU * f * (1 + vib) / SR;
+        double env = 1;
+        if (i < att) env = (double)i / att;
+        else if (i > n - rel) env = fmax(0, (double)(n - i) / rel);
+        addb(buf, s0 + i, sin(ph) * env * g);
+    }
+}
+
+static void sub_bass(float *buf, double t, double midi, double dur, double g) {
+    double f = midi_hz(midi - 12);
+    int n = (int)(dur * SR); long s0 = (long)(t * SR);
+    int att = (int)(0.012 * SR), rel = (int)(0.04 * SR);
+    double ph = 0;
+    for (int i = 0; i < n; i++) {
+        ph += TAU * f / SR;
+        double env = 1;
+        if (i < att) env = (double)i / att;
+        else if (i > n - rel) env = fmax(0, (double)(n - i) / rel);
+        addb(buf, s0 + i, tanh(sin(ph) * 1.4) * env * g);
+    }
+}
+
+static void toy_piano(float *buf, double t, double midi, double dur, double g) {
+    double f = midi_hz(midi);
+    int n = (int)(dur * SR); long s0 = (long)(t * SR);
+    double p1 = 0, p2 = 0, p3 = 0;
+    for (int i = 0; i < n; i++) {
+        double tt = (double)i / SR;
+        p1 += TAU * f / SR;
+        p2 += TAU * f * 2.01 / SR;
+        p3 += TAU * f * 3.04 / SR;
+        double env = exp(-tt * 4.5);
+        addb(buf, s0 + i, (sin(p1) * 0.55 + sin(p2) * 0.30 + sin(p3) * 0.18) * env * g);
+    }
+}
+
+static void pluck(float *buf, double t, double midi, double dur, double g) {
+    double f = midi_hz(midi);
+    int n = (int)(dur * SR); long s0 = (long)(t * SR);
+    double ph = 0, lp = 0;
+    for (int i = 0; i < n; i++) {
+        double tt = (double)i / SR;
+        ph += TAU * f / SR;
+        double saw = 2.0 * fmod(ph / TAU, 1.0) - 1.0;
+        double raw = saw * 0.55 + sin(ph) * 0.45;
+        double a = 0.12 + 0.55 * exp(-tt * 14);
+        lp += a * (raw - lp);
+        addb(buf, s0 + i, lp * exp(-tt * 7) * g);
+    }
+}
+
+static void bach_arp(float *buf, double bar_start, int root, int minor,
+                     int density, int octave, double g) {
+    int T = minor ? 3 : 4;
+    int s16[16] = {0, T, 7, 12, 7, T, 0, T, 7, 12, 14, 12, 7, T, 7, 12};
+    int s8[8]   = {0, 7, T, 12, 14, 12, 7, T};
+    int *steps = density == 16 ? s16 : s8;
+    int ns = density == 16 ? 16 : 8;
+    double step_len = BAR / ns;
+    for (int i = 0; i < ns; i++) {
+        pluck(buf, bar_start + i * step_len, root + octave + steps[i],
+              step_len * 1.6, g * (i % 4 == 0 ? 1.15 : 0.85));
+    }
+}
+
+// choir — soft sustained harmony: detuned sines on the chord tones with
+// slow vibrato. always present, every bar of the song, no matter what.
+static void choir(float *buf, double t, int root, int third, int fifth, double g) {
+    int tones[3] = {root + 12, third + 12, fifth + 12};
+    int n = (int)(BAR * 1.04 * SR); long s0 = (long)(t * SR);
+    int att = (int)(0.30 * SR), rel = (int)(0.25 * SR);
+    for (int m = 0; m < 3; m++) {
+        double f0 = midi_hz(tones[m]);
+        for (int d = 0; d < 2; d++) {
+            double f = f0 * (1 + (d ? 0.004 : -0.004));
+            double ph = rng() * TAU;
+            for (int i = 0; i < n; i++) {
+                double tt = (double)i / SR;
+                double vib = sin(TAU * 4.6 * tt + m) * 0.003;
+                ph += TAU * f * (1 + vib) / SR;
+                double env = 1;
+                if (i < att) env = (double)i / att;
+                else if (i > n - rel) env = fmax(0, (double)(n - i) / rel);
+                addb(buf, s0 + i, sin(ph) * env * g);
+            }
+        }
+    }
+}
+
+static void pad(float *buf, double t, const int *midis, int nm, double dur, double g) {
+    int n = (int)(dur * SR); long s0 = (long)(t * SR);
+    int att = (int)(0.06 * SR), rel = (int)(0.12 * SR);
+    static const double DET[3] = {-0.006, 0, 0.007};
+    for (int m = 0; m < nm; m++) {
+        double f0 = midi_hz(midis[m]);
+        for (int d = 0; d < 3; d++) {
+            double f = f0 * (1 + DET[d]);
+            double ph = rng() * TAU, lp = 0;
+            for (int i = 0; i < n; i++) {
+                ph += TAU * f / SR;
+                double saw = 2.0 * fmod(ph / TAU, 1.0) - 1.0;
+                lp += 0.10 * (saw - lp);
+                double env = 1;
+                if (i < att) env = (double)i / att;
+                else if (i > n - rel) env = fmax(0, (double)(n - i) / rel);
+                addb(buf, s0 + i, lp * env * g);
+            }
+        }
+    }
+}
+
+// ── paintShaped: piecewise gain envelope, the layered word merge ────────
+typedef struct { double at, to, over; } Break;
+
+static void paint_shaped(float *buf, const float *s, long sn, double start_sec,
+                         double g, const Break *breaks, int nb, double attack) {
+    long s0 = (long)(start_sec * SR);
+    double level = attack > 0 ? 0 : 1;
+    double from = level, ramp_start = 0, ramp_len = attack, target = 1;
+    int bi = 0;
+    for (long i = 0; i < sn; i++) {
+        double tt = (double)i / SR;
+        if (bi < nb && tt >= breaks[bi].at) {
+            from = level; target = breaks[bi].to;
+            ramp_start = tt;
+            ramp_len = breaks[bi].over > 1e-4 ? breaks[bi].over : 1e-4;
+            bi++;
+        }
+        if (level != target) {
+            double w = (tt - ramp_start) / ramp_len;
+            if (w > 1) w = 1;
+            level = from + (target - from) * (0.5 - 0.5 * cos(M_PI * w));
+            if (w >= 1) level = target;
+        }
+        if (level == 0 && bi >= nb) break;
+        addb(buf, s0 + i, s[i] * g * level);
+    }
+}
+
+// ── main ────────────────────────────────────────────────────────────────
+typedef struct { double t; int serious; } KickT;
+static KickT kick_times[4096];
+static int n_kicks = 0;
+static void push_kick(double t, int serious) {
+    if (n_kicks < 4096) { kick_times[n_kicks].t = t; kick_times[n_kicks].serious = serious; n_kicks++; }
+}
+
+static const ChordDef *chord_at_bar(int bar_idx) {
+    int b = bar_idx % PROG_BARS;
+    for (int i = 0; i < N_PROG; i++) {
+        if (b < PROG[i].bars) return &PROG[i];
+        b -= PROG[i].bars;
+    }
+    return &PROG[0];
+}
+
+static int vocals_only = 0;
+static int stem_voc = 0;
+
+int main(int argc, char **argv) {
+    const char *out_path = "out/americomputadora-c.wav";
+    for (int i = 1; i < argc; i++) {
+        if (!strcmp(argv[i], "--out") && i + 1 < argc) out_path = argv[++i];
+        else if (!strcmp(argv[i], "--vocals") && i + 1 < argc) voc_base = argv[++i];
+        else if (!strcmp(argv[i], "--vocals-only")) vocals_only = 1;
+        else if (!strcmp(argv[i], "--stem-voc")) stem_voc = 1;
+    }
+
+    BEAT = 60.0 / SCORE_BPM;
+    BAR = BEAT * 4;
+
+    int total_bars = 0;
+    for (int s = 0; s < N_SECS; s++) total_bars += STRUCTURE[s].bars * STRUCTURE[s].reps;
+    double total_sec = total_bars * BAR + 0.5;
+    N = (long)ceil(total_sec * SR);
+
+    drm = calloc(N, 4); kik = calloc(N, 4); snr = calloc(N, 4); bel = calloc(N, 4);
+    sqr = calloc(N, 4); sb  = calloc(N, 4); toy = calloc(N, 4);
+    arp = calloc(N, 4); pds = calloc(N, 4); cho = calloc(N, 4); voc = calloc(N, 4);
+
+    int total_hook_reps = 0;
+    for (int s = 0; s < N_SECS; s++)
+        if (!strcmp(STRUCTURE[s].section, "hook")) total_hook_reps += STRUCTURE[s].reps;
+
+    fprintf(stderr, "# americomputadora.c · %g BPM · %d bars · %.1fs\n",
+            (double)SCORE_BPM, total_bars, total_sec);
+
+    int bar_cursor = 0, hook_count = 0, phrase_counter = 0;
+    int verse_beat = 0;  // drives the verse-2 jeffrey syllable chant
+    int intro_beat = 0;  // drives the quiet intro chant
+
+    for (int si = 0; si < N_SECS; si++) {
+        const Sec *sec = &STRUCTURE[si];
+        for (int r = 0; r < sec->reps; r++) {
+            for (int b = 0; b < sec->bars; b++) {
+                double bt = (bar_cursor + b) * BAR;
+                const ChordDef *ch = chord_at_bar(bar_cursor + b);
+                int root = ch->root, third = root + (ch->minor ? 3 : 4), fifth = root + 7;
+
+                // very faint harmony bed — every bar, no matter what
+                choir(cho, bt, root, third, fifth, 0.022);
+
+                if (strcmp(sec->feel, "claps-only") && strcmp(sec->feel, "fade")) {
+                    double sg = (!strcmp(sec->feel, "thin") || !strcmp(sec->feel, "sparse")) ? 0.22 : 0.35;
+                    if (!strcmp(sec->section, "intro")) sg = 0.10; // hushed under the hats
+                    sub_bass(sb, bt, root, BAR * 0.95, sg);
+                }
+
+                if (!strcmp(sec->section, "stop") || !strcmp(sec->feel, "claps-only")) {
+                    clap(drm, bt + BEAT, 1.05);
+                    clap(drm, bt + BEAT * 3, 1.05);
+                } else if (!strcmp(sec->section, "intro")) {
+                    // the opener: soft hats + the toy-piano melody (the same
+                    // every-other-beat figure from verse 2) + a very quiet,
+                    // smooth jeffrey syllable chant. spare and pretty.
+                    for (int i = 0; i < 8; i++) tamb(drm, bt + i * (BEAT / 2), 0.08);
+                    // toy piano — fuller now: a soft chord on 1 and 3 (triad
+                    // + inversion) under a stepping melody line on every beat.
+                    toy_piano(toy, bt,            root,      BEAT * 1.9, 0.06);
+                    toy_piano(toy, bt,            third,     BEAT * 1.9, 0.055);
+                    toy_piano(toy, bt,            fifth,     BEAT * 1.9, 0.05);
+                    toy_piano(toy, bt + BEAT * 2, fifth,     BEAT * 1.9, 0.055);
+                    toy_piano(toy, bt + BEAT * 2, root + 12, BEAT * 1.9, 0.055);
+                    toy_piano(toy, bt + BEAT * 2, third + 12, BEAT * 1.9, 0.045);
+                    // melody line on top — gives it motion / complexity
+                    toy_piano(toy, bt,            third + 12, BEAT * 0.85, 0.07);
+                    toy_piano(toy, bt + BEAT,     fifth + 12, BEAT * 0.85, 0.06);
+                    toy_piano(toy, bt + BEAT * 2, root + 24, BEAT * 0.85, 0.06);
+                    toy_piano(toy, bt + BEAT * 3, fifth + 12, BEAT * 0.85, 0.06);
+#if N_SYL > 0
+                    // HARMONIC opener: both voices chant together on chord
+                    // tones — jeffrey on one degree, the computer voice a
+                    // harmony above. four beats, a moving little chorale.
+                    {
+                        // (jeffrey degree, computer degree) per beat — thirds
+                        // and fifths apart so they harmonize.
+                        // two computer-voice lines a third/fifth apart —
+                        // harmony with itself (jeffrey's wizard takes removed).
+                        const int loDeg[4] = {root, third, fifth, third};
+                        const int hiDeg[4] = {third, fifth, root + 12, fifth};
+                        for (int k = 0; k < 4; k++) {
+                            long s0 = (long)((bt + k * BEAT) * SR);
+                            long slot = (long)(BEAT * 1.7 * SR);
+                            int af = (int)(0.05 * SR), rf = (int)(0.30 * SR);
+                            for (int ln = 0; ln < 2; ln++) {
+                                int deg = ln == 0 ? loDeg[k] : hiDeg[k];
+                                int ti = -1;
+                                for (int q = 0; q < N_SYLT; q++) if (SYL_NOTES[q] == deg) { ti = q; break; }
+                                if (ti < 0) continue;
+                                Clip *sc = get_syl(1, intro_beat % N_SYL, ti); // computer voice
+                                if (!sc) continue;
+                                long lim = sc->n < slot ? sc->n : slot;
+                                double g = ln == 0 ? 0.55 : 0.42;
+                                for (long i = 0; i < lim; i++) {
+                                    double env = 1;
+                                    if (i < af) env = (double)i / af;
+                                    else if (i > lim - rf) env = (double)(lim - i) / rf;
+                                    addb(voc, s0 + i, sc->s[i] * g * env);
+                                }
+                            }
+                            intro_beat++;
+                        }
+                    }
+#endif
+                } else if (!strcmp(sec->feel, "fade")) {
+                    if (!(b & 1)) kick(kik, bt, 0.55);
+                    for (int i = 0; i < 8; i++) tamb(drm, bt + i * (BEAT / 2), 0.05);
+                } else if (!strcmp(sec->section, "verse")) {
+                    // no kick under the vowel stitch: computer enters on the
+                    // odd bar's downbeat, leave that one out.
+                    if (!(b & 1)) { kick(kik, bt, 0.75); push_kick(bt, 0); }
+                    kick(kik, bt + BEAT * 2, 0.75); push_kick(bt + BEAT * 2, 0);
+                    snare_hit(snr, bt + BEAT, 0.5);
+                    snare_hit(snr, bt + BEAT * 3, 0.5);
+#if N_SYL > 0
+                    // jeffrey chant — verse 2 only (the sparse every-other-
+                    // beat melody at ~1:40): one syllable per beat, pitched
+                    // to the tones that melody walks (third → octave), on
+                    // top of the normal verse vocal.
+                    if (!strcmp(sec->feel, "sparse"))
+                    for (int k = 0; k < 4; k++) {
+                        int deg = k < 2 ? third : root + 12;
+                        int ti = -1;
+                        for (int q = 0; q < N_SYLT; q++) if (SYL_NOTES[q] == deg) { ti = q; break; }
+                        if (ti >= 0) {
+                            int si = verse_beat % N_SYL;
+                            long s0 = (long)((bt + k * BEAT) * SR);
+                            long slot = (long)(BEAT * 0.98 * SR);
+                            // computer voice only (jeffrey's wizard takes removed)
+                            Clip *sc = get_syl(1, si, ti);
+                            if (sc) {
+                                long lim = sc->n < slot ? sc->n : slot;
+                                for (long i = 0; i < lim; i++) {
+                                    double env = i > lim - 480 ? (double)(lim - i) / 480 : 1.0;
+                                    addb(voc, s0 + i, sc->s[i] * 0.5 * env);
+                                }
+                            }
+                        }
+                        verse_beat++;
+                    }
+#endif
+                    if (!strcmp(sec->feel, "thin")) {
+                        toy_piano(toy, bt,            third,     BEAT * 0.9, 0.16);
+                        toy_piano(toy, bt + BEAT,     fifth,     BEAT * 0.9, 0.13);
+                        toy_piano(toy, bt + BEAT * 2, root + 12, BEAT * 0.9, 0.13);
+                        toy_piano(toy, bt + BEAT * 3, fifth,     BEAT * 0.9, 0.13);
+                    } else {
+                        toy_piano(toy, bt,            third,     BEAT * 1.5, 0.14);
+                        toy_piano(toy, bt + BEAT * 2, root + 12, BEAT * 1.5, 0.14);
+                    }
+                } else if (!strcmp(sec->section, "bridge")) {
+                    kick_serious(kik, bt, 0.9); push_kick(bt, 1);
+                    bach_arp(arp, bt, root, ch->minor, 8, 0, 0.15);
+                } else {
+                    // hook — the percussion RAMP (see render.mjs)
+                    double tins = total_hook_reps > 1
+                        ? (double)hook_count / (total_hook_reps - 1) : 1;
+                    if (tins < 0.34) {
+                        if (!(b & 1)) { kick(kik, bt, 0.8); push_kick(bt, 0); }
+                        kick(kik, bt + BEAT * 2, 0.8); push_kick(bt + BEAT * 2, 0);
+                        snare_hit(snr, bt + BEAT, 0.55);
+                        snare_hit(snr, bt + BEAT * 3, 0.55);
+                    } else if (tins < 0.67) {
+                        if (!(b & 1)) { kick_serious(kik, bt, 0.95); push_kick(bt, 1); }
+                        kick_serious(kik, bt + BEAT * 2, 0.95); push_kick(bt + BEAT * 2, 1);
+                        snare_hit(snr, bt + BEAT, 0.8);
+                        snare_hit(snr, bt + BEAT * 3, 0.8);
+                        for (int i = 0; i < 8; i++) tamb(drm, bt + i * (BEAT / 2), 0.04);
+                    } else {
+                        int floor4 = tins > 0.95;
+                        for (int i = 0; i < 4; i++) {
+                            if ((b & 1) && i == 0) continue; // vowel stitch
+                            if (i % 2 == 0 || floor4) {
+                                kick_serious(kik, bt + BEAT * i, floor4 ? 1.1 : 1.05);
+                                push_kick(bt + BEAT * i, 1);
+                            }
+                        }
+                        snare_hit(snr, bt + BEAT, 0.95);
+                        snare_hit(snr, bt + BEAT * 3, 0.95);
+                        for (int i = 0; i < 8; i++) tamb(drm, bt + i * (BEAT / 2), 0.055);
+                    }
+                    bell(bel, bt, root + 12, BAR * 0.95, 0.10 + 0.05 * tins);
+                    bach_arp(arp, bt, root, ch->minor, 16, 12, 0.07 + 0.04 * tins);
+                    int chord4[4] = {root - 12, root, third, fifth};
+                    pad(pds, bt, chord4, 4, BAR * 1.02, 0.05 + 0.02 * tins);
+                }
+            }
+
+            // vocal phrases run through the WHOLE song — no silence in
+            // vocals, ever. the phrase starts at bar 0 (intro included),
+            // each section sets its own vocal level, and the treatment
+            // tier ramps raw → autotuned → full with the song.
+            // the opener is toy piano + the quiet chant ONLY — the lead
+            // vocal stays out of the intro and enters with the first hook
+            // (~21s). everything except intro+stop carries the lead.
+            if (strcmp(sec->section, "stop") && strcmp(sec->section, "intro")) {
+                int is_hook = !strcmp(sec->section, "hook");
+                double sec_gain = is_hook ? 1.0
+                    : !strcmp(sec->section, "intro") ? 0.65
+                    : !strcmp(sec->section, "bridge") ? 0.5
+                    : !strcmp(sec->feel, "fade") ? 0.7
+                    : 0.55; // verses — soft, present
+                const int *notes = VARIANT_NOTES[hook_count % N_VARIANTS];
+                int vi = hook_count % N_VARIANTS;
+                int phrase_beats = 0;
+                for (int w = 0; w < N_WORDS; w++) phrase_beats += BPW[w];
+                int phrase_bars = phrase_beats / 4 > 0 ? phrase_beats / 4 : 1;
+                double phrase_len = phrase_beats * BEAT;
+
+                int tier;
+                if (is_hook) {
+                    double tins_v = total_hook_reps > 1
+                        ? (double)hook_count / (total_hook_reps - 1) : 1;
+                    tier = tins_v < 0.34 ? 0 : tins_v < 0.67 ? 1 : 2;
+                } else {
+                    // off-hook sections follow the song's position coarsely
+                    tier = hook_count == 0 ? 0 : hook_count <= total_hook_reps / 2 ? 1 : 2;
+                }
+
+                for (int p = 0; p + phrase_bars <= sec->bars; p += phrase_bars) {
+                    double phrase_start = (bar_cursor + p) * BAR;
+                    int phrase_idx = phrase_counter++;
+                    if (is_hook) crash(drm, phrase_start, p == 0 ? 0.26 : 0.16);
+
+                    double onsets[N_WORDS];
+                    onsets[0] = 0;
+                    for (int w = 0; w < N_WORDS - 1; w++) onsets[w + 1] = onsets[w] + BPW[w] * BEAT;
+
+                    int max_w = N_WORDS - 1;
+                    if (!strcmp(sec->section, "intro")) max_w = p / phrase_bars; // one sample per phrase
+                    for (int w = 0; w < N_WORDS; w++) {
+                        if (w > max_w) break;
+                        double note_len = BPW[w] * BEAT;
+                        int target = notes[w];
+                        int last = w == N_WORDS - 1;
+                        // vowel stitch: the aaa→ooo crossfade COMPLETES
+                        // before the barline so the kick never lands inside
+                        // the morph. the incoming word blooms over BLEND and
+                        // is at full PRE seconds before its grid onset; the
+                        // outgoing vowel eases to 0.55 across exactly that
+                        // window (near equal-power), then chokes later.
+                        const double BLEND = tier == 0 ? 0.18 : tier == 1 ? 0.25 : 0.45;
+                        const double PRE = 0.12;
+                        double lead = (!last && w > 0) ? BLEND + PRE : 0;
+
+                        Clip *c = get_clip(tier, w, phrase_idx % ROSTER_N[w], vi);
+                        if (c) {
+                            Break breaks[2]; int nb; double attack, gain;
+                            if (last) {
+                                breaks[0] = (Break){phrase_len - onsets[w] + 0.06, 0, 0.22};
+                                nb = 1; attack = 0.008; gain = 1.22 * sec_gain; /* dora! */
+                            } else {
+                                double duck_at = onsets[w + 1] - onsets[w] + lead;
+                                double choke_at = (w + 2 < N_WORDS ? onsets[w + 2] : phrase_len) - onsets[w] + lead;
+                                if (w == 0) {
+                                    // ease down in lockstep with the next
+                                    // word's bloom window, then a long
+                                    // gentle fade-out of the aaaa into dora
+                                    breaks[0] = (Break){duck_at - BLEND - PRE, 0.68, BLEND};
+                                    breaks[1] = (Break){choke_at - 0.45, 0, 0.50};
+                                } else {
+                                    breaks[0] = (Break){duck_at - 0.06, 0.30, 0.20};
+                                    breaks[1] = (Break){choke_at - 0.06, 0, 0.22};
+                                }
+                                nb = 2;
+                                attack = w == 0 ? 0 : BLEND;
+                                gain = 0.95 * sec_gain;
+                            }
+                            paint_shaped(voc, c->s, c->n, phrase_start + onsets[w] - lead,
+                                         gain, breaks, nb, attack);
+                        }
+                        if (is_hook)
+                            sine_lead(sqr, phrase_start + onsets[w], target + 12, note_len * 0.95, 0.10);
+                    }
+
+                    // FINALE (last third of choruses): arpeggiate the
+                    // america sample into a stacked harmony — pitched
+                    // americas on a D-major arpeggio (the plain-tier clips
+                    // are already tuned to those notes), each entering a
+                    // beat apart and ringing together under the lead.
+                    if (is_hook) {
+                        double tinsH = total_hook_reps > 1
+                            ? (double)hook_count / (total_hook_reps - 1) : 1;
+                        if (tinsH > 0.62) {
+                            const int ARP_VI[4] = {0, 2, 6, 5}; // D4 F#4 A4 D5
+                            double swell = (tinsH - 0.62) / 0.38; // 0..1 into the finale
+                            for (int a = 0; a < 4; a++) {
+                                Clip *hc = get_clip(1, 0, 0, ARP_VI[a]); // plain america
+                                if (!hc) continue;
+                                double at = phrase_start + a * BEAT; // arpeggiated entry
+                                double g = 0.16 * swell;
+                                long s0 = (long)(at * SR);
+                                long lim = hc->n;
+                                int afin = (int)(0.04 * SR), rfin = (int)(0.5 * SR);
+                                for (long i = 0; i < lim; i++) {
+                                    double env = 1;
+                                    if (i < afin) env = (double)i / afin;
+                                    else if (i > lim - rfin) env = (double)(lim - i) / rfin;
+                                    addb(voc, s0 + i, hc->s[i] * g * env);
+                                }
+                            }
+                        }
+                    }
+                }
+                if (is_hook) hook_count++;
+            }
+            bar_cursor += sec->bars;
+        }
+    }
+
+    // ── sidechain duck ────────────────────────────────────────────────
+    float *duck = malloc(N * 4);
+    for (long i = 0; i < N; i++) duck[i] = 1;
+    for (int k = 0; k < n_kicks; k++) {
+        double depth = kick_times[k].serious ? 0.32 : 0.78;
+        long len = (long)((kick_times[k].serious ? BEAT * 0.85 : 0.10) * SR);
+        long s0 = (long)(kick_times[k].t * SR);
+        for (long i = 0; i < len && s0 + i < N; i++) {
+            double w = (double)i / len;
+            double d = depth + (1 - depth) * (0.5 - 0.5 * cos(M_PI * w));
+            if (d < duck[s0 + i]) duck[s0 + i] = (float)d;
+        }
+    }
+
+    // ── fade-out across the outro (last 8 bars) ───────────────────────
+    long fade_s = (long)((total_bars - 8) * BAR * SR);
+    // ── vocals start at bar 0 — fade in across the intro, but from a
+    // 0.35 floor so every syllable of the first "america" is heard ──────
+    // the opener chant stays up front (just a tiny declick at sample 0).
+    // it's the LEAD vocal that fades in — over the first 2 bars of the
+    // first hook, where voc holds only the lead (no chant overlaps there).
+    {
+        long dc = (long)(0.02 * SR);
+        for (long i = 0; i < dc && i < N; i++) voc[i] *= (float)i / dc;
+    }
+    {
+        int hb = 0;
+        for (int si = 0; si < N_SECS; si++) {
+            if (!strcmp(STRUCTURE[si].section, "hook")) break;
+            hb += STRUCTURE[si].bars * STRUCTURE[si].reps;
+        }
+        long lead0 = (long)(hb * BAR * SR);
+        long lfin = (long)(2 * BAR * SR);
+        for (long i = 0; i < lfin && lead0 + i < N; i++)
+            voc[lead0 + i] *= (float)(0.5 - 0.5 * cos(M_PI * (double)i / lfin));
+    }
+
+    // ── FX one-shots: gong + record scratches (freesound, c/fx/) ──────
+    // scratches sprinkle the first 30s and cluster around ~2:15; the gong
+    // marks the top of the finale. mixed into the drum bus.
+    {
+        long gn = 0, s1n = 0, s2n = 0;
+        char fp[512];
+        snprintf(fp, sizeof fp, "%sfx/gong.wav", voc_base);   float *gong = load_wav_mono(fp, &gn);
+        snprintf(fp, sizeof fp, "%sfx/scratch1.wav", voc_base); float *sc1 = load_wav_mono(fp, &s1n);
+        snprintf(fp, sizeof fp, "%sfx/scratch2.wav", voc_base); float *sc2 = load_wav_mono(fp, &s2n);
+        // place a clip into drm at time t with gain
+        #define PLACE(CLIP, CN, T, G) do { \
+            if (CLIP) { long _s0 = (long)((T) * SR); \
+                for (long _i = 0; _i < (CN); _i++) addb(drm, _s0 + _i, (CLIP)[_i] * (G)); } } while (0)
+        // scratches arrive WITH the main vocal (first chorus, after the
+        // quiet intro) — not over the opener.
+        double choir_in = (!strcmp(STRUCTURE[0].section, "intro")
+            ? STRUCTURE[0].bars * STRUCTURE[0].reps : 0) * BAR;
+        PLACE(sc1, s1n, choir_in + 0.0, 0.5);
+        PLACE(sc2, s2n, choir_in + 4 * BAR, 0.45);
+        PLACE(sc1, s1n, choir_in + 8 * BAR + 2.5 * BEAT, 0.5);
+        // ~2:15 cluster
+        PLACE(sc2, s2n, 133.0, 0.6);
+        PLACE(sc1, s1n, 135.0, 0.55);
+        PLACE(sc2, s2n, 136.5, 0.5);
+        // gong marks the lift OUT of the intro into the first chorus, and
+        // the finale push (~2:18). a soft swell, not a hit at bar 0.
+        PLACE(gong, gn, choir_in - 0.4, 0.55);
+        PLACE(gong, gn, 138.0, 0.7);
+        #undef PLACE
+        free(gong); free(sc1); free(sc2);
+    }
+
+    if (stem_voc) {
+        // pure vocal bus, pre-everything — for c/analyze.mjs shape checks
+        if (!write_wav_f32(out_path, voc, N)) { fprintf(stderr, "write failed\n"); return 1; }
+        fprintf(stderr, "stem-voc %s\n", out_path);
+        return 0;
+    }
+
+    // ── reverb send → schroeder ───────────────────────────────────────
+    float *send = malloc(N * 4);
+    for (long i = 0; i < N; i++)
+        send[i] = voc[i] * 0.85f + snr[i] * 0.65f + bel[i] * 0.55f + sqr[i] * 0.5f + arp[i] * 0.3f;
+    float *room = calloc(N, 4);
+    {
+        static const double CDEL[4] = {0.0297, 0.0371, 0.0411, 0.0437};
+        float *cb[4]; long cl[4], ci[4] = {0, 0, 0, 0};
+        for (int c = 0; c < 4; c++) { cl[c] = (long)(CDEL[c] * SR); cb[c] = calloc(cl[c], 4); }
+        for (long i = 0; i < N; i++) {
+            double s = 0;
+            for (int c = 0; c < 4; c++) {
+                double y = cb[c][ci[c]];
+                cb[c][ci[c]] = send[i] + (float)(y * 0.62);
+                ci[c] = (ci[c] + 1) % cl[c];
+                s += y;
+            }
+            room[i] = (float)(s * 0.25);
+        }
+        for (int c = 0; c < 4; c++) free(cb[c]);
+        static const double ADEL[2] = {0.005, 0.0017};
+        for (int a = 0; a < 2; a++) {
+            long al = (long)(ADEL[a] * SR), ai = 0;
+            float *ab = calloc(al, 4);
+            for (long i = 0; i < N; i++) {
+                double y = ab[ai], x = room[i];
+                ab[ai] = (float)(x + y * 0.5);
+                room[i] = (float)(y - x * 0.5);
+                ai = (ai + 1) % al;
+            }
+            free(ab);
+        }
+    }
+
+    // ── dotted-8th vocal echo ─────────────────────────────────────────
+    long dsamp = (long)(BEAT * 0.75 * SR);
+    float *echo = calloc(N, 4);
+    for (long i = 0; i < N; i++)
+        echo[i] = voc[i] + (i >= dsamp ? echo[i - dsamp] * 0.40f : 0);
+
+    // ── master ────────────────────────────────────────────────────────
+    float *mix = malloc(N * 4);
+    double peak = 0;
+    for (long i = 0; i < N; i++) {
+        double dk = duck[i];
+        double s;
+        if (vocals_only) {
+            // isolated vocal mix: words + echo tail + room share, plus
+            // the kick (pumping the words) and the faint harmony bed.
+            double tail0 = (echo[i] - voc[i]) * 0.28;
+            s = kik[i] + voc[i] * (0.75 + 0.25 * dk) + tail0 * dk
+              + cho[i] * 0.7 + room[i] * 0.35;
+        } else {
+            double drums = (drm[i] + kik[i] + snr[i]) * 0.92;
+            double melodic = (bel[i] + sqr[i] + toy[i] + arp[i] + pds[i] + cho[i]) * dk;
+            double subb = sb[i] * (0.55 + 0.45 * dk);
+            double tail = (echo[i] - voc[i]) * 0.28;
+            double vocal = voc[i] * (0.75 + 0.25 * dk) + tail * dk;
+            double rm = room[i] * 0.55 * (0.7 + 0.3 * dk);
+            s = drums + melodic + subb + vocal * 0.78 + rm;
+        }
+        double fade = i >= fade_s ? fmax(0, 1.0 - (double)(i - fade_s) / (N - fade_s)) : 1.0;
+        double v = tanh(s * 0.95) * fade;
+        mix[i] = (float)v;
+        double a = fabs(v); if (a > peak) peak = a;
+    }
+    if (peak > 0) {
+        double g = 0.85 / peak;
+        for (long i = 0; i < N; i++) mix[i] *= (float)g;
+    }
+
+    if (!write_wav_f32(out_path, mix, N)) {
+        fprintf(stderr, "✗ write failed: %s\n", out_path);
+        return 1;
+    }
+    fprintf(stderr, "✓ %s\n", out_path);
+    return 0;
+}
diff --git a/pop/americomputadora/c/analyze.mjs b/pop/americomputadora/c/analyze.mjs
new file mode 100644
index 000000000..0825d8268
--- /dev/null
+++ b/pop/americomputadora/c/analyze.mjs
@@ -0,0 +1,117 @@
+#!/usr/bin/env node
+// analyze.mjs — look at the SHAPE of the vocal stitch instead of guessing.
+//
+//   node c/analyze.mjs --clip c/vocals/dora-0-v0.wav     # onset shape of one clip
+//   node c/analyze.mjs --stem c/out/c-voc-stem.wav       # junction shapes per phrase
+//
+// stem mode knows the phrase grid (melody.json) and reports, for each of the
+// first few phrases: the america→computer junction dip, whether computer is
+// at full level BEFORE the barline (the kick spot), and dora's attack slope.
+
+import { readFileSync } from "node:fs";
+import { dirname, join } from "node:path";
+import { fileURLToPath } from "node:url";
+import { readWavMono } from "../../lib/wav.mjs";
+
+const SR = 48_000;
+const HERE = dirname(fileURLToPath(import.meta.url));
+const ROOT = dirname(HERE);
+const melody = JSON.parse(readFileSync(join(ROOT, "melody.json"), "utf8"));
+const BEAT = 60 / melody.bpm;
+
+const argv = process.argv.slice(2);
+const flags = {};
+for (let i = 0; i < argv.length; i++) {
+  if (argv[i].startsWith("--")) flags[argv[i].slice(2)] = argv[i + 1];
+}
+
+function envelope(samples, win = 0.01) {
+  const W = Math.floor(win * SR);
+  const out = [];
+  for (let i = 0; i + W <= samples.length; i += W) {
+    let e = 0;
+    for (let j = i; j < i + W; j++) e += samples[j] * samples[j];
+    out.push(Math.sqrt(e / W));
+  }
+  return out;
+}
+
+function spark(env, hi = null) {
+  const blocks = " ▁▂▃▄▅▆▇█";
+  const mx = hi ?? Math.max(...env, 1e-9);
+  return env.map((v) => blocks[Math.min(8, Math.floor((v / mx) * 8.999))]).join("");
+}
+
+if (flags.clip) {
+  const { samples } = readWavMono(flags.clip);
+  const env = envelope(samples);
+  const peak = Math.max(...env);
+  console.log(`# ${flags.clip}  (${(samples.length / SR).toFixed(2)}s, env peak ${peak.toFixed(3)})`);
+  console.log(`  first 400ms : ${spark(env.slice(0, 40), peak)}`);
+  console.log(`  whole clip  : ${spark(env)}`);
+  // attack: ms to reach 50% of peak
+  const half = env.findIndex((v) => v > peak * 0.5);
+  console.log(`  attack→50% peak: ${half * 10}ms`);
+  process.exit(0);
+}
+
+const stemPath = flags.stem ?? join(HERE, "out", "c-voc-stem.wav");
+const { samples } = readWavMono(stemPath);
+const env = envelope(samples);
+const E = (sec) => env[Math.floor(sec / 0.01)] ?? 0;
+
+// phrase grid: phrases run back-to-back from bar 0, 2 bars each
+const lens = melody.hook.beats_per_word;
+const onsets = [0];
+for (let i = 0; i < lens.length - 1; i++) onsets.push(onsets[i] + lens[i] * BEAT);
+const phraseLen = lens.reduce((a, c) => a + c, 0) * BEAT;
+
+console.log(`# vocal stem ${stemPath}`);
+console.log(`# phrase ${phraseLen.toFixed(2)}s · computer @ +${onsets[1].toFixed(2)}s · dora @ +${onsets[2].toFixed(2)}s\n`);
+
+const nPhrases = Number(flags.phrases ?? 6);
+for (let p = 0; p < nPhrases; p++) {
+  const t0 = p * phraseLen;
+  if ((t0 + phraseLen) * SR > samples.length) break;
+  const cAt = t0 + onsets[1], dAt = t0 + onsets[2];
+
+  // junction window: ±0.6s around computer onset
+  const jEnv = [];
+  for (let t = cAt - 0.6; t < cAt + 0.4; t += 0.01) jEnv.push(E(t));
+  const before = Math.max(...jEnv.slice(0, 30));      // america vowel level
+  const after = Math.max(...jEnv.slice(70));          // computer settled level
+  const floor = Math.min(before, after);
+  // a HOLE is a continuous run of near-silence in the splice zone — natural
+  // intra-word dips are brief; a stitch gap is long.
+  let hole = 0, run = 0;
+  for (const v of jEnv.slice(30, 70)) {
+    if (v < floor * 0.18) { run++; hole = Math.max(hole, run); } else run = 0;
+  }
+  const holeMs = hole * 10;
+  // bloom: computer must be audibly arriving before the barline
+  let bloom = 0;
+  for (let t = cAt - 0.35; t < cAt - 0.08; t += 0.01) bloom = Math.max(bloom, E(t));
+  const bloomPct = after > 0 ? (bloom / after) * 100 : 0;
+
+  // dora attack: rise over the first 40ms vs its peak in 300ms
+  const dPeak = Math.max(...envelope(samples.subarray(Math.floor(dAt * SR), Math.floor((dAt + 0.3) * SR))));
+  const d40 = E(dAt + 0.03);
+  const dAtk = dPeak > 0 ? (d40 / dPeak) * 100 : 0;
+
+  // syllable pulses in the america region: local maxima ≥45% of the
+  // region peak, ≥120ms apart. "a-ME-ri-ca" should give ≥3.
+  const aEnv = [];
+  for (let t = t0; t < t0 + 1.9; t += 0.01) aEnv.push(E(t));
+  const aPeak = Math.max(...aEnv);
+  let syl = 0, lastP = -99;
+  for (let i = 2; i < aEnv.length - 2; i++) {
+    if (aEnv[i] > aPeak * 0.45 && aEnv[i] >= aEnv[i - 1] && aEnv[i] >= aEnv[i + 1]
+        && aEnv[i - 2] < aEnv[i] && i - lastP >= 12) { syl++; lastP = i; }
+  }
+
+  console.log(`phrase ${p} @ ${t0.toFixed(1)}s · america pulses: ${syl}`);
+  console.log(`  junction  : ${spark(jEnv)}`);
+  console.log(`  hole ${holeMs}ms · computer bloom ${bloomPct.toFixed(0)}% of settled before barline · dora 30ms attack ${dAtk.toFixed(0)}% of peak`);
+  const ok = holeMs <= 60 && bloomPct > 25 && dAtk > 35;
+  console.log(`  ${ok ? "✓ stitch reads continuous" : "✗ NEEDS WORK" + (holeMs > 60 ? " [hole in junction]" : "") + (bloomPct <= 25 ? " [computer late]" : "") + (dAtk <= 35 ? " [dora attack soft]" : "")}\n`);
+}
diff --git a/pop/americomputadora/c/bake.mjs b/pop/americomputadora/c/bake.mjs
new file mode 100644
index 000000000..88eb5464d
--- /dev/null
+++ b/pop/americomputadora/c/bake.mjs
@@ -0,0 +1,547 @@
+#!/usr/bin/env node
+// bake.mjs — prepare everything americomputadora.c needs (the hellsine
+// pattern: JS bakes the score + samples, C renders the song).
+//
+//   1. vocal prep: for every (word, roster clip, melody variant) pull the
+//      snapped wav (whisper twin where the recipe says so), time-stretch,
+//      decap, RMS-match — the same chain render.mjs runs — and write a
+//      float32 mono 48k wav into c/vocals/.
+//   2. score: melody.json structure / chords / variants + the vocal file
+//      table → score.h.
+//
+// usage: node c/bake.mjs        (canonical recipe is the default)
+
+import { spawnSync } from "node:child_process";
+import { existsSync, mkdirSync, readFileSync, writeFileSync, unlinkSync } from "node:fs";
+import { dirname, join } from "node:path";
+import { fileURLToPath } from "node:url";
+import { tmpdir } from "node:os";
+
+import { readWavMono } from "../../lib/wav.mjs";
+
+const SR = 48_000;
+const HERE = dirname(fileURLToPath(import.meta.url));
+const ROOT = dirname(HERE);
+const melody = JSON.parse(readFileSync(join(ROOT, "melody.json"), "utf8"));
+
+// ── the canonical recipe (mirror of the render.mjs invocation) ─────────
+// one sample per word — the three choices. (rosters still rotate per
+// phrase if you list more than one, but jeffrey prefers the fixed trio.)
+// hold: loop the post-decap "um" region so the word says "ummputer".
+const RECIPE = {
+  america: {
+    roster: ["whitney-houston-w1"],
+    stretch: 1.35, whisper: false, decap: false, hold: false,
+    // the FULL sample, no trims, no loops — the engine's envelope just
+    // fades the aaaa out into dora. (firstPhrase/sustainVowel retired for
+    // america by jeffrey's call: "i want the full americaaaaa".)
+  },
+  computer: {
+    roster: ["samantha-slow"],
+    stretch: 1.4, whisper: true, decap: false, hold: true, sustainEnd: true,
+    // decap off: the /k/ stays — "KAHM-puter". the hold loops the vowel
+    // after the /k/ ("kaaahm"). sustainEnd loops the FINAL vowel ("errrr")
+    // so the word rings continuously up to dora — no vocal gap.
+  },
+  dora: {
+    roster: ["theme-song-w1"],
+    stretch: 1, whisper: false, decap: false, hold: false, graftHead: true,
+  },
+};
+
+// granular hold: repeat the [aSec, bSec] region with short crossfades —
+// duration grows, pitch and formants don't. "omputer" → "ummmputer".
+function holdUm(s, aSec = 0.03, bSec = 0.13, reps = 2, fadeSec = 0.012) {
+  const a = Math.floor(aSec * SR), b = Math.floor(bSec * SR), F = Math.floor(fadeSec * SR);
+  if (s.length < b + F || a < F) return s;
+  const seg = s.subarray(a, b);
+  const chunks = [s.subarray(0, b)];
+  for (let r = 0; r < reps; r++) chunks.push(seg);
+  chunks.push(s.subarray(b));
+  const total = chunks.reduce((n, c) => n + c.length, 0) - F * (chunks.length - 1);
+  const out = new Float32Array(total);
+  let pos = 0;
+  chunks.forEach((c, idx) => {
+    if (idx === 0) { out.set(c, 0); pos = c.length; return; }
+    for (let i = 0; i < F; i++) {
+      const w = i / F;
+      out[pos - F + i] = out[pos - F + i] * (1 - w) + c[i] * w;
+    }
+    out.set(c.subarray(F), pos);
+    pos += c.length - F;
+  });
+  return out;
+}
+
+// graft the raw clip's head onto a tuned clip — WORLD smears plosive
+// transients (dora's /d/ took 100ms to rise instead of 20ms), so the
+// first ~70ms come straight from the untouched sample.
+function graftHead(tuned, raw, headSec = 0.07, fadeSec = 0.015) {
+  const H = Math.floor(headSec * SR), F = Math.floor(fadeSec * SR);
+  if (raw.length < H + F || tuned.length < H + F) return tuned;
+  const out = Float32Array.from(tuned);
+  for (let i = 0; i < H; i++) out[i] = raw[i];
+  for (let i = 0; i < F; i++) {
+    const w = i / F;
+    out[H + i] = raw[H + i] * (1 - w) + tuned[H + i] * w;
+  }
+  return out;
+}
+
+// sustain the final vowel: loop the region just before the sung word's
+// energy dies until the clip reaches targetSec, then let the natural tail
+// decay. fixes the hole the waveform analysis found — whitney's "aaa"
+// ended ~1.9s but computer doesn't bloom until ~2.1s.
+function sustainVowel(s, targetSec, loopSec = 0.14, fadeSec = 0.015) {
+  const target = Math.floor(targetSec * SR);
+  if (s.length >= target) {
+    // long enough on paper — but check the ENERGY reaches the junction
+  }
+  const W = Math.floor(0.01 * SR);
+  const nF = Math.floor(s.length / W);
+  const rms = [];
+  let peak = 0;
+  for (let f = 0; f < nF; f++) {
+    let e = 0;
+    for (let i = f * W; i < (f + 1) * W; i++) e += s[i] * s[i];
+    const v = Math.sqrt(e / W);
+    rms.push(v); peak = Math.max(peak, v);
+  }
+  let endF = nF - 1;
+  while (endF > 0 && rms[endF] < peak * 0.3) endF--;
+  const vowelEnd = endF * W;
+  if (vowelEnd >= target) return s; // energy already covers the slot
+  const L = Math.floor(loopSec * SR), F = Math.floor(fadeSec * SR);
+  if (vowelEnd < L + F) return s;
+  const segA = vowelEnd - L, segB = vowelEnd;
+  const seg = s.subarray(segA, segB);
+  const chunks = [s.subarray(0, segB)];
+  let have = segB;
+  const tail = s.length - segB; // the word's natural ending ("...ca") rides AFTER the loops
+  while (have < target - tail) { chunks.push(seg); have += seg.length - F; }
+  chunks.push(s.subarray(segB)); // natural decay tail — the ca lands before dora
+  const total = chunks.reduce((n, c) => n + c.length, 0) - F * (chunks.length - 1);
+  const out = new Float32Array(total);
+  let pos = 0;
+  chunks.forEach((c, idx) => {
+    if (idx === 0) { out.set(c, 0); pos = c.length; return; }
+    for (let i = 0; i < F; i++) {
+      const w = i / F;
+      out[pos - F + i] = out[pos - F + i] * (1 - w) + c[i] * w;
+    }
+    out.set(c.subarray(F), pos);
+    pos += c.length - F;
+  });
+  return out;
+}
+
+// keep only the first sung phrase: find the first sustained internal
+// silence (>=120ms under 12% of peak, after minSec) and cut there with a
+// 30ms fade. whitney-w1 sings the word twice; we want one.
+function firstPhrase(s, minSec = 0.8, gapSec = 0.10, thresh = 0.22) {
+  const W = Math.floor(0.01 * SR);
+  const nF = Math.floor(s.length / W);
+  const rms = []; let peak = 0;
+  for (let f = 0; f < nF; f++) {
+    let e = 0;
+    for (let i = f * W; i < (f + 1) * W; i++) e += s[i] * s[i];
+    const v = Math.sqrt(e / W);
+    rms.push(v); peak = Math.max(peak, v);
+  }
+  const need = Math.round(gapSec / 0.01);
+  let run = 0;
+  for (let f = Math.floor(minSec / 0.01); f < nF; f++) {
+    if (rms[f] < peak * thresh) {
+      if (++run >= need) {
+        const cut = (f - run + 1) * W;
+        const out = Float32Array.from(s.subarray(0, cut));
+        const F = Math.floor(0.03 * SR);
+        for (let i = 0; i < F && cut - 1 - i >= 0; i++) out[cut - 1 - i] *= i / F;
+        return out;
+      }
+    } else run = 0;
+  }
+  return s;
+}
+
+// "putaa": locate the final /t/ closure (last >=30ms energy gap in the
+// back 45% of the word), keep the fresh vowel right after it, loop it with
+// decaying gain, fade — the rhotic "er" tail never happens.
+function kahmTail(s) {
+  const W = Math.floor(0.01 * SR);
+  const nF = Math.floor(s.length / W);
+  const rms = []; let peak = 0;
+  for (let f = 0; f < nF; f++) {
+    let e = 0;
+    for (let i = f * W; i < (f + 1) * W; i++) e += s[i] * s[i];
+    const v = Math.sqrt(e / W);
+    rms.push(v); peak = Math.max(peak, v);
+  }
+  let closureEnd = -1, run = 0;
+  for (let f = Math.floor(nF * 0.55); f < nF; f++) {
+    if (rms[f] < peak * 0.22) run++;
+    else { if (run >= 3) closureEnd = f; run = 0; }
+  }
+  if (closureEnd < 0) return s;
+  const vStart = closureEnd * W;
+  const keep = Math.min(s.length, vStart + Math.floor(0.10 * SR));
+  const F = Math.floor(0.012 * SR);
+  const segA = Math.min(vStart + Math.floor(0.015 * SR), keep - F - 1);
+  if (segA <= 0 || keep - segA < F * 2) return s;
+  const seg = s.subarray(segA, keep);
+  const reps = 1, gains = [0.85]; // single short "a" — "kahmputa", crisp
+  const total = keep + (seg.length - F) * reps;
+  const out = new Float32Array(total);
+  out.set(s.subarray(0, keep), 0);
+  let pos = keep;
+  for (let r = 0; r < reps; r++) {
+    const g = gains[r];
+    for (let i = 0; i < F; i++) {
+      const w = i / F;
+      out[pos - F + i] = out[pos - F + i] * (1 - w) + seg[i] * g * w;
+    }
+    for (let i = F; i < seg.length; i++) out[pos + i - F] = seg[i] * g;
+    pos += seg.length - F;
+  }
+  const FF = Math.floor(0.10 * SR);
+  for (let i = 0; i < FF && i < pos; i++) out[pos - 1 - i] *= i / FF;
+  return out.subarray(0, pos);
+}
+
+// ── processing helpers (same math as render.mjs) ────────────────────────
+function chainAtempo(target) {
+  const stages = [];
+  let r = target;
+  while (r > 2.0) { stages.push(2.0); r /= 2.0; }
+  while (r < 0.5) { stages.push(0.5); r /= 0.5; }
+  stages.push(+r.toFixed(6));
+  return stages.map((s) => `atempo=${s}`).join(",");
+}
+function stretchWav(absIn, factor) {
+  const tmp = join(tmpdir(), `acd-bake-${process.pid}-${Math.random().toString(36).slice(2, 8)}.wav`);
+  const res = spawnSync("ffmpeg", ["-hide_banner", "-y", "-loglevel", "error",
+    "-i", absIn, "-af", chainAtempo(1 / factor), "-ac", "1", "-ar", String(SR), tmp],
+    { stdio: ["ignore", "ignore", "inherit"] });
+  if (res.status !== 0) throw new Error(`stretch failed: ${absIn}`);
+  const { samples } = readWavMono(tmp);
+  try { unlinkSync(tmp); } catch {}
+  return samples;
+}
+function vowelOnset(samples) {
+  const frame = Math.floor(0.01 * SR);
+  const nF = Math.floor(samples.length / frame);
+  let peakE = 0;
+  const E = new Array(nF), Z = new Array(nF);
+  for (let f = 0; f < nF; f++) {
+    let e = 0, z = 0;
+    for (let i = f * frame + 1; i < (f + 1) * frame; i++) {
+      e += samples[i] * samples[i];
+      if ((samples[i] >= 0) !== (samples[i - 1] >= 0)) z++;
+    }
+    E[f] = e / frame; Z[f] = z / frame;
+    if (E[f] > peakE) peakE = E[f];
+  }
+  for (let f = 0; f < Math.floor(nF * 0.4); f++) {
+    if (E[f] > peakE * 0.22 && Z[f] < 0.14) return f * frame;
+  }
+  return 0;
+}
+function detectPitchHz(samples) {
+  const n = samples.length;
+  const seg = samples.subarray(Math.floor(n * 0.2), Math.floor(n * 0.8));
+  const minLag = Math.floor(SR / 600), maxLag = Math.floor(SR / 80);
+  let bestLag = 0, bestScore = -Infinity;
+  for (let lag = minLag; lag <= maxLag; lag++) {
+    let r = 0, e0 = 0, e1 = 0;
+    for (let i = 0; i + lag < seg.length; i++) {
+      r += seg[i] * seg[i + lag];
+      e0 += seg[i] * seg[i];
+      e1 += seg[i + lag] * seg[i + lag];
+    }
+    const score = r / (Math.sqrt(e0 * e1) || 1);
+    if (score > bestScore) { bestScore = score; bestLag = lag; }
+  }
+  return bestLag ? SR / bestLag : null;
+}
+
+function normalizeRms(s, target = 0.12) {
+  let sum = 0, n = 0, peak = 0;
+  for (let i = 0; i < s.length; i++) {
+    const a = Math.abs(s[i]);
+    if (a > peak) peak = a;
+    if (a > 0.02) { sum += s[i] * s[i]; n++; }
+  }
+  if (!n) return s;
+  let g = target / Math.sqrt(sum / n);
+  if (peak * g > 0.95) g = 0.95 / peak;
+  for (let i = 0; i < s.length; i++) s[i] *= g;
+  return s;
+}
+function writeWavF32(path, samples) {
+  const n = samples.length;
+  const b = Buffer.alloc(44 + n * 4);
+  b.write("RIFF", 0); b.writeUInt32LE(36 + n * 4, 4); b.write("WAVE", 8);
+  b.write("fmt ", 12); b.writeUInt32LE(16, 16);
+  b.writeUInt16LE(3, 20);            // IEEE float
+  b.writeUInt16LE(1, 22);            // mono
+  b.writeUInt32LE(SR, 24);
+  b.writeUInt32LE(SR * 4, 28);
+  b.writeUInt16LE(4, 32); b.writeUInt16LE(32, 34);
+  b.write("data", 36); b.writeUInt32LE(n * 4, 40);
+  for (let i = 0; i < n; i++) b.writeFloatLE(samples[i], 44 + i * 4);
+  writeFileSync(path, b);
+}
+
+// ── bake vocals — three treatment tiers, ramping with the song ─────────
+//   raw   (chorus 1): the utterance itself, RMS-matched only. "by the
+//                     book" — no pitch-snap, no stretch, no whisper.
+//   plain (chorus 2): autotuned to the variant note (snapped lib, voiced),
+//                     still unstretched and un-whispered.
+//   full  (finale):   the whole canonical treatment.
+const vocDir = join(HERE, "vocals");
+mkdirSync(vocDir, { recursive: true });
+const words = melody.hook.words;
+const variants = melody.hook.variants;
+const rawTable = [];   // [word][roster] → path
+const plainTable = []; // [word][roster][variant] → path
+const fullTable = [];  // [word][roster][variant] → path
+
+console.log("# baking vocals → c/vocals/ (raw / plain / full tiers)");
+words.forEach((word, w) => {
+  const r = RECIPE[word];
+  rawTable[w] = []; plainTable[w] = []; fullTable[w] = [];
+  r.roster.forEach((name, ri) => {
+    // decap applies on EVERY tier — never "computer". cut 25 ms INTO the
+    // voiced onset so no burst residue survives, then hold the "um".
+    const decapped = (s, voicedSamples, scale = 1) => {
+      if (!r.decap) return s;
+      let cut = vowelOnset(voicedSamples);
+      if (cut > 0) cut += Math.floor(0.025 * SR);
+      cut = Math.floor(cut * scale);
+      if (cut > 0 && cut < s.length) {
+        s = s.slice(cut);
+        const fadeN = Math.floor(0.008 * SR);
+        for (let i = 0; i < fadeN && i < s.length; i++) s[i] *= i / fadeN;
+      }
+      return s;
+    };
+    // hold the vowel after whatever consonant survives: locate the voiced
+    // onset (scaled into stretched time) and loop just past it.
+    const held = (s, voicedSamples, scale = 1) => {
+      if (!r.hold) return s;
+      const on = r.decap ? 0 : (vowelOnset(voicedSamples) * scale) / SR;
+      return holdUm(s, on + 0.02, on + 0.12);
+    };
+
+    // sustain targets (seconds):
+    //  - sustainTo "junction": america rings until computer (slot+next slot)
+    //  - sustainEnd: computer's final vowel rings to dora's onset — its own
+    //    slot plus a small overlap so there's NO gap before dora.
+    const beat = 60 / melody.bpm;
+    const sustainTarget = r.sustainTo === "junction"
+      ? (melody.hook.beats_per_word[w] + melody.hook.beats_per_word[w + 1]) * beat - 0.05
+      : r.sustainEnd
+      ? melody.hook.beats_per_word[w] * beat + 0.22
+      : 0;
+    const sustained = (s) => {
+      if (r.firstWordOnly) s = firstPhrase(s);
+      return sustainTarget ? sustainVowel(s, sustainTarget) : s;
+    };
+
+    // raw tier — straight from utterances/ (plus decap)
+    const utt = join(ROOT, "utterances", word, `${name}.wav`);
+    if (!existsSync(utt)) throw new Error(`missing utterance: ${utt}`);
+    const uttS = Float32Array.from(readWavMono(utt).samples);
+    let rawS = held(decapped(uttS, uttS), uttS);
+    if (r.tailAa) rawS = kahmTail(rawS);
+    const raw = normalizeRms(sustained(rawS));
+    rawTable[w][ri] = `vocals/${word}-${ri}-raw.wav`;
+    writeWavF32(join(HERE, rawTable[w][ri]), raw);
+
+    plainTable[w][ri] = []; fullTable[w][ri] = [];
+    variants.forEach((v, vi) => {
+      const t = v.notes[w];
+      const voiced = join(ROOT, "snapped", word, `${name}__t${t}.wav`);
+      const snap = join(ROOT, "snapped", word, `${name}__t${t}${r.whisper ? "__w" : ""}.wav`);
+      if (!existsSync(snap) || !existsSync(voiced)) throw new Error(`missing snap: ${snap}`);
+
+      // plain tier — tuned + decap (+ raw transient graft), nothing else
+      const voicedS = Float32Array.from(readWavMono(voiced).samples);
+      let plainS = held(decapped(Float32Array.from(voicedS), voicedS), voicedS);
+      if (r.tailAa) plainS = kahmTail(plainS);
+      if (r.graftHead) plainS = graftHead(plainS, uttS);
+      const plain = normalizeRms(sustained(plainS));
+      plainTable[w][ri][vi] = `vocals/${word}-${ri}-v${vi}-plain.wav`;
+      writeWavF32(join(HERE, plainTable[w][ri][vi]), plain);
+
+      // full tier — stretch + decap + whisper, the canonical character
+      let s = r.stretch !== 1 ? stretchWav(snap, r.stretch) : Float32Array.from(readWavMono(snap).samples);
+      const sc = r.stretch !== 1 ? r.stretch : 1;
+      s = held(decapped(s, voicedS, sc), voicedS, sc);
+      if (r.tailAa) s = kahmTail(s);
+      if (r.graftHead && r.stretch === 1) s = graftHead(s, uttS);
+      s = sustained(s);
+      normalizeRms(s);
+      fullTable[w][ri][vi] = `vocals/${word}-${ri}-v${vi}.wav`;
+      writeWavF32(join(HERE, fullTable[w][ri][vi]), s);
+    });
+    console.log(`  ✓ ${word}/${name}  raw + ${variants.length}×2 variants`);
+  });
+});
+
+// ── syllable chant: 'ah mer ick ahmp uter do rah' (dora split do+rah),
+// two voices (jeffrey + a computer voice), pitched to every verse-melody
+// degree. KEY: we analyze each syllable's ACTUAL base pitch and choose the
+// octave of the target note NEAREST that base — so jeffrey is nudged only
+// a few semitones, never hauled across an octave. retain<1 keeps his
+// natural inflection. each syllable is stretched a touch for legato.
+const SYL_NAMES = ["ah", "mer", "ick", "ahmp", "uter", "do", "rah"];
+const sylDir = join(HERE, "syl-cache");
+let sylNotes = [], sylPaths = [], sylPathsC = [];
+const NOTE_NAMES = ["C", "C#", "D", "D#", "E", "F", "F#", "G", "G#", "A", "A#", "B"];
+const midiNameOf = (m) => NOTE_NAMES[m % 12] + (Math.floor(m / 12) - 1);
+const SYL_STRETCH = 1.18; // a bit longer — legato chant
+
+// LIVE jeffrey takes from the wave-wizard win over the ElevenLabs clips:
+// wave-wizard/samples/americomputadora/takes/americomputadora-chant-note-N.wav
+// (N = 0..6, same order as SYL_NAMES). copy any present take into syl-cache
+// as the jeffrey source so the rest of the pipeline is unchanged.
+// wave-wizard live takes are DISABLED (jeffrey's recorded vocals removed).
+// flip USE_WIZARD back to true to bring them in again.
+const USE_WIZARD = false;
+const wizTakes = join(ROOT, "..", "..", "wave-wizard", "samples", "americomputadora", "takes");
+let nWiz = 0;
+if (USE_WIZARD) {
+  SYL_NAMES.forEach((n, si) => {
+    const take = join(wizTakes, `americomputadora-chant-note-${si}.wav`);
+    if (existsSync(take)) {
+      spawnSync("ffmpeg", ["-hide_banner", "-y", "-loglevel", "error", "-i", take,
+        "-ac", "1", "-ar", String(SR), join(sylDir, n + ".wav")],
+        { stdio: ["ignore", "ignore", "inherit"] });
+      nWiz++;
+    }
+  });
+  if (nWiz) console.log(`# wave-wizard: ${nWiz}/${SYL_NAMES.length} live jeffrey takes → syl-cache`);
+}
+
+if (SYL_NAMES.every((n) => existsSync(join(sylDir, n + ".wav")))) {
+  const degrees = new Set();
+  for (const c of melody.bed.chord_progression) {
+    const root = c.root_midi, min = c.quality === "min";
+    degrees.add(root);                 // the harmonic opener chants the root too
+    degrees.add(root + (min ? 3 : 4)); // third
+    degrees.add(root + 7);             // fifth
+    degrees.add(root + 12);            // octave
+  }
+  sylNotes = [...degrees].sort((a, b) => a - b);
+  const PY = join(ROOT, "..", ".venv", "bin", "python3");
+  const PITCHSNAP = join(ROOT, "..", "bin", "pitchsnap_world.py");
+
+  // tune one voice's syllable to the octave of `t` nearest its base pitch.
+  const tuneOne = (src, rel, t, baseMidi) => {
+    const outAbs = join(HERE, rel);
+    // stretch first (atempo, pitch unchanged), then loudnorm
+    spawnSync("ffmpeg", ["-hide_banner", "-y", "-loglevel", "error",
+      "-i", src, "-af", `${chainAtempo(1 / SYL_STRETCH)},loudnorm=I=-15:TP=-1.2`,
+      "-ac", "1", "-ar", String(SR), outAbs], { stdio: ["ignore", "ignore", "inherit"] });
+    // nearest octave of the target pitch-class to his actual base
+    let tEff = t;
+    if (baseMidi != null) {
+      while (tEff - baseMidi > 6) tEff -= 12;
+      while (tEff - baseMidi < -6) tEff += 12;
+    } else { while (tEff > 60) tEff -= 12; while (tEff < 48) tEff += 12; }
+    // retain 0.7 — lands on the tone but keeps jeffrey's own movement
+    const tune = spawnSync(PY, [PITCHSNAP, outAbs, outAbs, "--notes", midiNameOf(tEff),
+      "--retain", "0.7", "--xfade-ms", "20"], { stdio: ["ignore", "ignore", "inherit"] });
+    if (tune.status !== 0) console.warn(`  ! WORLD tune failed: ${rel} → ${midiNameOf(tEff)}`);
+  };
+
+  SYL_NAMES.forEach((n, si) => {
+    const jSrc = join(sylDir, n + ".wav");
+    const cSrc = join(sylDir, `c-${n}.wav`);
+    const jBase = (() => { const hz = detectPitchHz(readWavMono(jSrc).samples); return hz ? 69 + 12 * Math.log2(hz / 440) : null; })();
+    const cBase = existsSync(cSrc) ? (() => { const hz = detectPitchHz(readWavMono(cSrc).samples); return hz ? 69 + 12 * Math.log2(hz / 440) : null; })() : null;
+    sylPaths[si] = []; sylPathsC[si] = [];
+    sylNotes.forEach((t, ti) => {
+      const jRel = `vocals/syl-${n}-t${t}.wav`;
+      tuneOne(jSrc, jRel, t, jBase);
+      sylPaths[si][ti] = jRel;
+      if (existsSync(cSrc)) {
+        const cRel = `vocals/sylc-${n}-t${t}.wav`;
+        tuneOne(cSrc, cRel, t, cBase);
+        sylPathsC[si][ti] = cRel;
+      } else sylPathsC[si][ti] = jRel;
+    });
+    console.log(`  · syl ${n}: jeffrey base ${jBase ? midiNameOf(Math.round(jBase)) : "?"}${cBase ? ` · computer base ${midiNameOf(Math.round(cBase))}` : ""}`);
+  });
+  console.log(`✓ syllable chant: ${SYL_NAMES.length} syls × ${sylNotes.length} notes × 2 voices`);
+} else {
+  console.log("· no syl-cache — run node c/syllables.mjs for the chant layer");
+}
+
+// ── score.h ──────────────────────────────────────────────────────────────
+const prog = melody.bed.chord_progression;
+const h = `// score.h — generated by c/bake.mjs from melody.json. do not hand-edit.
+#define SCORE_BPM ${melody.bpm}
+#define N_WORDS ${words.length}
+#define N_VARIANTS ${variants.length}
+#define MAX_ROSTER ${Math.max(...words.map((w) => RECIPE[w].roster.length))}
+
+static const int BPW[N_WORDS] = {${melody.hook.beats_per_word.join(", ")}};
+static const int VARIANT_NOTES[N_VARIANTS][N_WORDS] = {
+${variants.map((v) => `  {${v.notes.join(", ")}}, // ${v.label}`).join("\n")}
+};
+
+typedef struct { const char *section; int bars; int reps; const char *feel; } Sec;
+static const Sec STRUCTURE[] = {
+${melody.structure.map((s) => `  {"${s.section}", ${s.bars}, ${s.reps || 1}, "${s.feel}"},`).join("\n")}
+};
+#define N_SECS ${melody.structure.length}
+
+typedef struct { int bars; int root; int minor; } ChordDef;
+static const ChordDef PROG[] = {
+${prog.map((c) => `  {${c.bars}, ${c.root_midi}, ${c.quality === "min" ? 1 : 0}},`).join("\n")}
+};
+#define N_PROG ${prog.length}
+#define PROG_BARS ${prog.reduce((a, c) => a + c.bars, 0)}
+
+static const int ROSTER_N[N_WORDS] = {${words.map((w) => RECIPE[w].roster.length).join(", ")}};
+// raw tier — the utterance itself, untouched ("by the book" stitch)
+static const char *VOC_RAW[N_WORDS][MAX_ROSTER] = {
+${rawTable.map((byRoster) => "  {" + byRoster.map((p) => `"${p}"`).join(", ") + "},").join("\n")}
+};
+// plain tier — autotuned to the variant note, nothing else
+static const char *VOC_PLAIN[N_WORDS][MAX_ROSTER][N_VARIANTS] = {
+${plainTable.map((byRoster) =>
+  "  {\n" + byRoster.map((byVar) =>
+    "    {" + byVar.map((p) => `"${p}"`).join(", ") + "},"
+  ).join("\n") + "\n  },"
+).join("\n")}
+};
+// full tier — stretch + decap + whisper, the canonical character
+static const char *VOC_FULL[N_WORDS][MAX_ROSTER][N_VARIANTS] = {
+${fullTable.map((byRoster) =>
+  "  {\n" + byRoster.map((byVar) =>
+    "    {" + byVar.map((p) => `"${p}"`).join(", ") + "},"
+  ).join("\n") + "\n  },"
+).join("\n")}
+};
+
+// jeffrey syllable chant (verse layer)
+#define N_SYL ${sylPaths.length}
+#define N_SYLT ${Math.max(1, sylNotes.length)}
+static const int SYL_NOTES[N_SYLT] = {${sylNotes.length ? sylNotes.join(", ") : 0}};
+static const char *SYL_PATHS[N_SYL ? N_SYL : 1][N_SYLT] = {
+${sylPaths.length
+  ? sylPaths.map((row) => "  {" + row.map((p) => `"${p}"`).join(", ") + "},").join("\n")
+  : '  {""},'}
+};
+// second voice (computer) chanting the same syllables, same notes
+static const char *SYL_PATHS_C[N_SYL ? N_SYL : 1][N_SYLT] = {
+${sylPathsC.length
+  ? sylPathsC.map((row) => "  {" + row.map((p) => `"${p}"`).join(", ") + "},").join("\n")
+  : '  {""},'}
+};
+`;
+writeFileSync(join(HERE, "score.h"), h);
+console.log(`✓ c/score.h (${variants.length} variants · structure ${melody.structure.length} sections)`);
diff --git a/pop/americomputadora/c/build.sh b/pop/americomputadora/c/build.sh
new file mode 100755
index 000000000..e9254df1c
--- /dev/null
+++ b/pop/americomputadora/c/build.sh
@@ -0,0 +1,4 @@
+#!/bin/sh
+# build americomputadora.c (needs score.h — run `node c/bake.mjs` first)
+cd "$(dirname "$0")"
+exec cc -O2 -Wall -Wextra -Wno-unused-parameter -o americomputadora americomputadora.c -lm
diff --git a/pop/americomputadora/c/fx.mjs b/pop/americomputadora/c/fx.mjs
new file mode 100644
index 000000000..c7953c0d3
--- /dev/null
+++ b/pop/americomputadora/c/fx.mjs
@@ -0,0 +1,34 @@
+#!/usr/bin/env node
+// fx.mjs — fetch one-shot FX (gong, record scratches) from Freesound into
+// c/fx/, decoded to mono 48k wav. cached by file existence.
+
+import { mkdirSync, existsSync, copyFileSync } from "node:fs";
+import { dirname, join, basename } from "node:path";
+import { fileURLToPath } from "node:url";
+import { spawnSync } from "node:child_process";
+import { searchSounds, downloadPreview } from "../../lib/freesound.mjs";
+
+const HERE = dirname(fileURLToPath(import.meta.url));
+const SR = 48_000;
+const fxDir = join(HERE, "fx");
+mkdirSync(fxDir, { recursive: true });
+
+const WANT = [
+  { name: "gong", query: "gong hit", filter: "duration:[1.5 TO 8]" },
+  { name: "scratch1", query: "record scratch vinyl", filter: "duration:[0.3 TO 2]" },
+  { name: "scratch2", query: "turntable scratch dj", filter: "duration:[0.3 TO 2.5]" },
+];
+
+for (const w of WANT) {
+  const wav = join(fxDir, `${w.name}.wav`);
+  if (existsSync(wav)) { console.log(`✓ ${w.name} cached`); continue; }
+  const data = await searchSounds({ query: w.query, filter: w.filter, pageSize: 5, sort: "rating_desc" });
+  const hit = (data.results || [])[0];
+  if (!hit) { console.warn(`! no result for "${w.query}"`); continue; }
+  const mp3 = await downloadPreview(hit);
+  const ok = spawnSync("ffmpeg", ["-hide_banner", "-y", "-loglevel", "error", "-i", mp3,
+    "-af", "loudnorm=I=-15:TP=-1.2", "-ac", "1", "-ar", String(SR), wav],
+    { stdio: ["ignore", "ignore", "inherit"] }).status === 0;
+  console.log(`${ok ? "✓" : "✗"} ${w.name} ← ${hit.name} (#${hit.id}, ${hit.username})`);
+}
+console.log("# fx ready in c/fx/");
diff --git a/pop/americomputadora/c/render-c.mjs b/pop/americomputadora/c/render-c.mjs
new file mode 100644
index 000000000..45af0260d
--- /dev/null
+++ b/pop/americomputadora/c/render-c.mjs
@@ -0,0 +1,66 @@
+#!/usr/bin/env node
+// render-c.mjs — the C-backend render flow (hellsine pattern):
+//   bake (JS preps vocals + score.h) → cc → ./americomputadora (C renders
+//   the song to f32 WAV) → acdsp (C mastering: 1176 + EQ) → ffmpeg mp3.
+//
+// usage: node c/render-c.mjs [--no-bake] [--out ../out/americomputadora-bach-whisperz.mp3]
+
+import { spawnSync } from "node:child_process";
+import { existsSync, mkdirSync } from "node:fs";
+import { dirname, join, resolve } from "node:path";
+import { fileURLToPath } from "node:url";
+
+const HERE = dirname(fileURLToPath(import.meta.url));
+const ROOT = dirname(HERE);
+const POP = dirname(ROOT);
+
+const argv = process.argv.slice(2);
+const flags = {};
+for (let i = 0; i < argv.length; i++) {
+  const a = argv[i];
+  if (a.startsWith("--")) {
+    const k = a.slice(2), n = argv[i + 1];
+    if (n !== undefined && !n.startsWith("--")) { flags[k] = n; i++; } else flags[k] = true;
+  }
+}
+const outMp3 = resolve(flags.out ?? join(ROOT, "out", "americomputadora-bach-whisperz.mp3"));
+mkdirSync(dirname(outMp3), { recursive: true });
+mkdirSync(join(HERE, "out"), { recursive: true });
+
+function run(label, cmd, args, opts = {}) {
+  console.log(`# ${label}`);
+  const res = spawnSync(cmd, args, { stdio: "inherit", ...opts });
+  if (res.status !== 0) { console.error(`✗ ${label} failed`); process.exit(1); }
+}
+
+if (!flags["no-bake"]) run("bake (vocals + score.h)", "node", [join(HERE, "bake.mjs")]);
+run("cc", "sh", [join(HERE, "build.sh")]);
+
+const rawWav = join(HERE, "out", "c-raw.wav");
+run("render (C engine)", join(HERE, "americomputadora"),
+    ["--out", rawWav, "--vocals", HERE + "/"]);
+
+// master through acdsp — the C 1176 + EQ chain, not ffmpeg loudnorm.
+const mastered = join(HERE, "out", "c-mastered.wav");
+const acdsp = join(POP, "dsp", "c", "acdsp");
+if (existsSync(acdsp)) {
+  run("master (acdsp 1176 + eq)", acdsp, [
+    rawWav, mastered, "--chain",
+    "1176:ratio=4:in=-8:out=+9:attack=4:release=4 eq:warmth=+1 eq:air=+1.5",
+    "--bits", "24",
+  ]);
+} else {
+  console.warn("! acdsp not built (pop/dsp/c) — skipping mastering stage");
+}
+
+const src = existsSync(mastered) ? mastered : rawWav;
+run("encode mp3 (ffmpeg, io only)", "ffmpeg", [
+  "-hide_banner", "-y", "-loglevel", "error",
+  "-i", src,
+  "-c:a", "libmp3lame", "-q:a", "2",
+  "-metadata", "title=americomputadora",
+  "-metadata", "artist=jeffrey",
+  "-metadata", "album=pixsies",
+  outMp3,
+]);
+console.log(`✓ ${outMp3}`);
diff --git a/pop/americomputadora/c/score.h b/pop/americomputadora/c/score.h
new file mode 100644
index 000000000..8ce9a2fc0
--- /dev/null
+++ b/pop/americomputadora/c/score.h
@@ -0,0 +1,96 @@
+// score.h — generated by c/bake.mjs from melody.json. do not hand-edit.
+#define SCORE_BPM 112
+#define N_WORDS 3
+#define N_VARIANTS 7
+#define MAX_ROSTER 1
+
+static const int BPW[N_WORDS] = {4, 2, 2};
+static const int VARIANT_NOTES[N_VARIANTS][N_WORDS] = {
+  {62, 69, 66}, // rise-rest
+  {64, 69, 62}, // step-home
+  {66, 71, 69}, // lift
+  {71, 69, 66}, // bach-circle
+  {66, 69, 74}, // bach-arc
+  {74, 71, 62}, // bach-fall
+  {69, 74, 71}, // climax
+};
+
+typedef struct { const char *section; int bars; int reps; const char *feel; } Sec;
+static const Sec STRUCTURE[] = {
+  {"intro", 10, 1, "soft"},
+  {"hook", 4, 4, "full"},
+  {"verse", 8, 1, "thin"},
+  {"hook", 4, 4, "full"},
+  {"verse", 8, 1, "sparse"},
+  {"bridge", 4, 1, "breakdown"},
+  {"stop", 1, 1, "claps-only"},
+  {"hook", 4, 4, "full"},
+  {"outro", 8, 1, "fade"},
+};
+#define N_SECS 9
+
+typedef struct { int bars; int root; int minor; } ChordDef;
+static const ChordDef PROG[] = {
+  {2, 62, 0},
+  {2, 69, 0},
+  {2, 71, 1},
+  {2, 67, 0},
+};
+#define N_PROG 4
+#define PROG_BARS 8
+
+static const int ROSTER_N[N_WORDS] = {1, 1, 1};
+// raw tier — the utterance itself, untouched ("by the book" stitch)
+static const char *VOC_RAW[N_WORDS][MAX_ROSTER] = {
+  {"vocals/america-0-raw.wav"},
+  {"vocals/computer-0-raw.wav"},
+  {"vocals/dora-0-raw.wav"},
+};
+// plain tier — autotuned to the variant note, nothing else
+static const char *VOC_PLAIN[N_WORDS][MAX_ROSTER][N_VARIANTS] = {
+  {
+    {"vocals/america-0-v0-plain.wav", "vocals/america-0-v1-plain.wav", "vocals/america-0-v2-plain.wav", "vocals/america-0-v3-plain.wav", "vocals/america-0-v4-plain.wav", "vocals/america-0-v5-plain.wav", "vocals/america-0-v6-plain.wav"},
+  },
+  {
+    {"vocals/computer-0-v0-plain.wav", "vocals/computer-0-v1-plain.wav", "vocals/computer-0-v2-plain.wav", "vocals/computer-0-v3-plain.wav", "vocals/computer-0-v4-plain.wav", "vocals/computer-0-v5-plain.wav", "vocals/computer-0-v6-plain.wav"},
+  },
+  {
+    {"vocals/dora-0-v0-plain.wav", "vocals/dora-0-v1-plain.wav", "vocals/dora-0-v2-plain.wav", "vocals/dora-0-v3-plain.wav", "vocals/dora-0-v4-plain.wav", "vocals/dora-0-v5-plain.wav", "vocals/dora-0-v6-plain.wav"},
+  },
+};
+// full tier — stretch + decap + whisper, the canonical character
+static const char *VOC_FULL[N_WORDS][MAX_ROSTER][N_VARIANTS] = {
+  {
+    {"vocals/america-0-v0.wav", "vocals/america-0-v1.wav", "vocals/america-0-v2.wav", "vocals/america-0-v3.wav", "vocals/america-0-v4.wav", "vocals/america-0-v5.wav", "vocals/america-0-v6.wav"},
+  },
+  {
+    {"vocals/computer-0-v0.wav", "vocals/computer-0-v1.wav", "vocals/computer-0-v2.wav", "vocals/computer-0-v3.wav", "vocals/computer-0-v4.wav", "vocals/computer-0-v5.wav", "vocals/computer-0-v6.wav"},
+  },
+  {
+    {"vocals/dora-0-v0.wav", "vocals/dora-0-v1.wav", "vocals/dora-0-v2.wav", "vocals/dora-0-v3.wav", "vocals/dora-0-v4.wav", "vocals/dora-0-v5.wav", "vocals/dora-0-v6.wav"},
+  },
+};
+
+// jeffrey syllable chant (verse layer)
+#define N_SYL 7
+#define N_SYLT 12
+static const int SYL_NOTES[N_SYLT] = {62, 66, 67, 69, 71, 73, 74, 76, 78, 79, 81, 83};
+static const char *SYL_PATHS[N_SYL ? N_SYL : 1][N_SYLT] = {
+  {"vocals/syl-ah-t62.wav", "vocals/syl-ah-t66.wav", "vocals/syl-ah-t67.wav", "vocals/syl-ah-t69.wav", "vocals/syl-ah-t71.wav", "vocals/syl-ah-t73.wav", "vocals/syl-ah-t74.wav", "vocals/syl-ah-t76.wav", "vocals/syl-ah-t78.wav", "vocals/syl-ah-t79.wav", "vocals/syl-ah-t81.wav", "vocals/syl-ah-t83.wav"},
+  {"vocals/syl-mer-t62.wav", "vocals/syl-mer-t66.wav", "vocals/syl-mer-t67.wav", "vocals/syl-mer-t69.wav", "vocals/syl-mer-t71.wav", "vocals/syl-mer-t73.wav", "vocals/syl-mer-t74.wav", "vocals/syl-mer-t76.wav", "vocals/syl-mer-t78.wav", "vocals/syl-mer-t79.wav", "vocals/syl-mer-t81.wav", "vocals/syl-mer-t83.wav"},
+  {"vocals/syl-ick-t62.wav", "vocals/syl-ick-t66.wav", "vocals/syl-ick-t67.wav", "vocals/syl-ick-t69.wav", "vocals/syl-ick-t71.wav", "vocals/syl-ick-t73.wav", "vocals/syl-ick-t74.wav", "vocals/syl-ick-t76.wav", "vocals/syl-ick-t78.wav", "vocals/syl-ick-t79.wav", "vocals/syl-ick-t81.wav", "vocals/syl-ick-t83.wav"},
+  {"vocals/syl-ahmp-t62.wav", "vocals/syl-ahmp-t66.wav", "vocals/syl-ahmp-t67.wav", "vocals/syl-ahmp-t69.wav", "vocals/syl-ahmp-t71.wav", "vocals/syl-ahmp-t73.wav", "vocals/syl-ahmp-t74.wav", "vocals/syl-ahmp-t76.wav", "vocals/syl-ahmp-t78.wav", "vocals/syl-ahmp-t79.wav", "vocals/syl-ahmp-t81.wav", "vocals/syl-ahmp-t83.wav"},
+  {"vocals/syl-uter-t62.wav", "vocals/syl-uter-t66.wav", "vocals/syl-uter-t67.wav", "vocals/syl-uter-t69.wav", "vocals/syl-uter-t71.wav", "vocals/syl-uter-t73.wav", "vocals/syl-uter-t74.wav", "vocals/syl-uter-t76.wav", "vocals/syl-uter-t78.wav", "vocals/syl-uter-t79.wav", "vocals/syl-uter-t81.wav", "vocals/syl-uter-t83.wav"},
+  {"vocals/syl-do-t62.wav", "vocals/syl-do-t66.wav", "vocals/syl-do-t67.wav", "vocals/syl-do-t69.wav", "vocals/syl-do-t71.wav", "vocals/syl-do-t73.wav", "vocals/syl-do-t74.wav", "vocals/syl-do-t76.wav", "vocals/syl-do-t78.wav", "vocals/syl-do-t79.wav", "vocals/syl-do-t81.wav", "vocals/syl-do-t83.wav"},
+  {"vocals/syl-rah-t62.wav", "vocals/syl-rah-t66.wav", "vocals/syl-rah-t67.wav", "vocals/syl-rah-t69.wav", "vocals/syl-rah-t71.wav", "vocals/syl-rah-t73.wav", "vocals/syl-rah-t74.wav", "vocals/syl-rah-t76.wav", "vocals/syl-rah-t78.wav", "vocals/syl-rah-t79.wav", "vocals/syl-rah-t81.wav", "vocals/syl-rah-t83.wav"},
+};
+// second voice (computer) chanting the same syllables, same notes
+static const char *SYL_PATHS_C[N_SYL ? N_SYL : 1][N_SYLT] = {
+  {"vocals/sylc-ah-t62.wav", "vocals/sylc-ah-t66.wav", "vocals/sylc-ah-t67.wav", "vocals/sylc-ah-t69.wav", "vocals/sylc-ah-t71.wav", "vocals/sylc-ah-t73.wav", "vocals/sylc-ah-t74.wav", "vocals/sylc-ah-t76.wav", "vocals/sylc-ah-t78.wav", "vocals/sylc-ah-t79.wav", "vocals/sylc-ah-t81.wav", "vocals/sylc-ah-t83.wav"},
+  {"vocals/sylc-mer-t62.wav", "vocals/sylc-mer-t66.wav", "vocals/sylc-mer-t67.wav", "vocals/sylc-mer-t69.wav", "vocals/sylc-mer-t71.wav", "vocals/sylc-mer-t73.wav", "vocals/sylc-mer-t74.wav", "vocals/sylc-mer-t76.wav", "vocals/sylc-mer-t78.wav", "vocals/sylc-mer-t79.wav", "vocals/sylc-mer-t81.wav", "vocals/sylc-mer-t83.wav"},
+  {"vocals/sylc-ick-t62.wav", "vocals/sylc-ick-t66.wav", "vocals/sylc-ick-t67.wav", "vocals/sylc-ick-t69.wav", "vocals/sylc-ick-t71.wav", "vocals/sylc-ick-t73.wav", "vocals/sylc-ick-t74.wav", "vocals/sylc-ick-t76.wav", "vocals/sylc-ick-t78.wav", "vocals/sylc-ick-t79.wav", "vocals/sylc-ick-t81.wav", "vocals/sylc-ick-t83.wav"},
+  {"vocals/sylc-ahmp-t62.wav", "vocals/sylc-ahmp-t66.wav", "vocals/sylc-ahmp-t67.wav", "vocals/sylc-ahmp-t69.wav", "vocals/sylc-ahmp-t71.wav", "vocals/sylc-ahmp-t73.wav", "vocals/sylc-ahmp-t74.wav", "vocals/sylc-ahmp-t76.wav", "vocals/sylc-ahmp-t78.wav", "vocals/sylc-ahmp-t79.wav", "vocals/sylc-ahmp-t81.wav", "vocals/sylc-ahmp-t83.wav"},
+  {"vocals/sylc-uter-t62.wav", "vocals/sylc-uter-t66.wav", "vocals/sylc-uter-t67.wav", "vocals/sylc-uter-t69.wav", "vocals/sylc-uter-t71.wav", "vocals/sylc-uter-t73.wav", "vocals/sylc-uter-t74.wav", "vocals/sylc-uter-t76.wav", "vocals/sylc-uter-t78.wav", "vocals/sylc-uter-t79.wav", "vocals/sylc-uter-t81.wav", "vocals/sylc-uter-t83.wav"},
+  {"vocals/sylc-do-t62.wav", "vocals/sylc-do-t66.wav", "vocals/sylc-do-t67.wav", "vocals/sylc-do-t69.wav", "vocals/sylc-do-t71.wav", "vocals/sylc-do-t73.wav", "vocals/sylc-do-t74.wav", "vocals/sylc-do-t76.wav", "vocals/sylc-do-t78.wav", "vocals/sylc-do-t79.wav", "vocals/sylc-do-t81.wav", "vocals/sylc-do-t83.wav"},
+  {"vocals/sylc-rah-t62.wav", "vocals/sylc-rah-t66.wav", "vocals/sylc-rah-t67.wav", "vocals/sylc-rah-t69.wav", "vocals/sylc-rah-t71.wav", "vocals/sylc-rah-t73.wav", "vocals/sylc-rah-t74.wav", "vocals/sylc-rah-t76.wav", "vocals/sylc-rah-t78.wav", "vocals/sylc-rah-t79.wav", "vocals/sylc-rah-t81.wav", "vocals/sylc-rah-t83.wav"},
+};
diff --git a/pop/americomputadora/c/syl-cache/ah.mp3 b/pop/americomputadora/c/syl-cache/ah.mp3
new file mode 100644
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diff --git a/pop/americomputadora/c/syl-cache/rah.mp3 b/pop/americomputadora/c/syl-cache/rah.mp3
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diff --git a/pop/americomputadora/c/syllables.mjs b/pop/americomputadora/c/syllables.mjs
new file mode 100644
index 000000000..0a599d86c
--- /dev/null
+++ b/pop/americomputadora/c/syllables.mjs
@@ -0,0 +1,115 @@
+#!/usr/bin/env node
+// syllables.mjs — fetch the jeffrey syllable chant via /api/say (ElevenLabs
+// jeffrey-pvc proxy, same provider as pop/bin/say.mjs) and trim to tight
+// per-syllable wavs. cached by file existence — each syllable costs once.
+//
+//   'ah' 'mer' 'ick' 'ahmp' 'uter' 'dora' — one per beat in the verses,
+//   pitched (by bake.mjs) to follow the toy-piano melody tones.
+//
+// usage: node c/syllables.mjs [--force]
+
+import { writeFileSync, mkdirSync, existsSync, rmSync } from "node:fs";
+import { dirname, join } from "node:path";
+import { fileURLToPath } from "node:url";
+import { spawnSync } from "node:child_process";
+
+const HERE = dirname(fileURLToPath(import.meta.url));
+const SR = 48_000;
+const cacheDir = join(HERE, "syl-cache");
+mkdirSync(cacheDir, { recursive: true });
+
+const force = process.argv.includes("--force");
+const SAY_URL = process.env.SAY_ENDPOINT || "https://aesthetic.computer/api/say";
+
+// name → what jeffrey actually says (punctuation shapes the delivery).
+// dora is split into do + rah so the chant lands it across two beats.
+const SYLS = [
+  ["ah", "ah"],
+  ["mer", "mer"],
+  ["ick", "ick"],
+  ["ahmp", "ahmp"],
+  ["uter", "ooter"],
+  ["do", "doe"],
+  ["rah", "rah"],
+];
+
+// a second voice — a macOS "computer" — chants the SAME syllables in
+// parallel (c-<name>.wav). cheap, local, no API.
+const COMPUTER_VOICE = "Samantha";
+for (const [name, text] of SYLS) {
+  const cwav = join(cacheDir, `c-${name}.wav`);
+  if (!existsSync(cwav) || force) {
+    const aiff = cwav.replace(/\.wav$/, ".aiff");
+    spawnSync("say", ["-v", COMPUTER_VOICE, "-r", "140", "-o", aiff, text], { stdio: "ignore" });
+    spawnSync("ffmpeg", ["-hide_banner", "-y", "-loglevel", "error", "-i", aiff,
+      "-af",
+      "silenceremove=start_periods=1:start_threshold=-40dB:start_silence=0.01," +
+      "areverse,silenceremove=start_periods=1:start_threshold=-40dB:start_silence=0.02,areverse," +
+      "afade=t=in:d=0.005,loudnorm=I=-15:TP=-1.2",
+      "-ac", "1", "-ar", String(SR), cwav], { stdio: "ignore" });
+    rmSync(aiff, { force: true });
+    console.log(`✓ c-${name} (${COMPUTER_VOICE})`);
+  }
+}
+
+for (const [name, text] of SYLS) {
+  const mp3 = join(cacheDir, `${name}.mp3`);
+  const wav = join(cacheDir, `${name}.wav`);
+  if (!existsSync(mp3) || force) {
+    console.log(`→ /api/say jeffrey: "${text}"`);
+    const res = await fetch(SAY_URL, {
+      method: "POST",
+      headers: { "content-type": "application/json" },
+      body: JSON.stringify({ from: text, provider: "jeffrey", voice: "neutral:0" }),
+    }).catch(() => null);
+    if (res && res.ok) {
+      writeFileSync(mp3, Buffer.from(await res.arrayBuffer()));
+    } else if (process.env.ELEVENLABS_API_KEY) {
+      // proxy down but a key is in the env — go straight to ElevenLabs
+      // with the jeffrey-pvc voice (same id as system/netlify/functions/say.js).
+      console.warn(`  ! /api/say down — direct ElevenLabs (jeffrey-pvc)`);
+      const el = await fetch("https://api.elevenlabs.io/v1/text-to-speech/ZXoQQp5X0PKHGwyZpVIT", {
+        method: "POST",
+        headers: {
+          "xi-api-key": process.env.ELEVENLABS_API_KEY,
+          "content-type": "application/json",
+        },
+        body: JSON.stringify({
+          text,
+          model_id: "eleven_multilingual_v2",
+          voice_settings: { stability: 0.5, similarity_boost: 0.75 },
+        }),
+      });
+      if (!el.ok) { console.error(`✗ ElevenLabs ${el.status}: ${await el.text()}`); process.exit(1); }
+      writeFileSync(mp3, Buffer.from(await el.arrayBuffer()));
+    } else {
+      // PLACEHOLDER: /api/say's ElevenLabs key is currently invalid (401
+      // upstream). macOS Reed stands in for jeffrey until the lith key is
+      // fixed — then: node c/syllables.mjs --force
+      if (res) console.warn(`  ! /api/say ${res.status} — using macOS placeholder voice`);
+      const aiff = mp3.replace(/\.mp3$/, ".aiff");
+      const ok = spawnSync("say", ["-v", "Reed (English (US))", "-r", "150", "-o", aiff, text],
+        { stdio: ["ignore", "ignore", "inherit"] }).status === 0;
+      if (!ok) { console.error("✗ say fallback failed"); process.exit(1); }
+      spawnSync("ffmpeg", ["-hide_banner", "-y", "-loglevel", "error", "-i", aiff,
+        "-c:a", "libmp3lame", "-q:a", "2", mp3], { stdio: "ignore" });
+      rmSync(aiff, { force: true });
+    }
+  }
+  if (!existsSync(wav) || force) {
+    rmSync(wav, { force: true });
+    const ok = spawnSync("ffmpeg", [
+      "-hide_banner", "-y", "-loglevel", "error", "-i", mp3,
+      "-af",
+      "silenceremove=start_periods=1:start_threshold=-40dB:start_silence=0.01," +
+      "areverse,silenceremove=start_periods=1:start_threshold=-40dB:start_silence=0.02,areverse," +
+      "afade=t=in:d=0.005,loudnorm=I=-15:TP=-1.2",
+      "-ac", "1", "-ar", String(SR), wav,
+    ], { stdio: ["ignore", "ignore", "inherit"] }).status === 0;
+    console.log(`${ok ? "✓" : "✗"} ${wav}`);
+    if (!ok) process.exit(1);
+  } else {
+    console.log(`✓ ${name} cached`);
+  }
+}
+console.log("# all syllables ready — run node c/bake.mjs to pitch + table them");
diff --git a/pop/marimba/bin/chrome-reel.mjs b/pop/marimba/bin/chrome-reel.mjs
new file mode 100644
index 000000000..04ee8c3e9
--- /dev/null
+++ b/pop/marimba/bin/chrome-reel.mjs
@@ -0,0 +1,305 @@
+#!/usr/bin/env node
+// marimba/bin/chrome-reel.mjs — the marimbaba REEL's side-stamp chrome:
+// a port of momboba/bin/chrome-reel.mjs (itself a port of twofa's
+// chrome.mjs / amaythingra's drawWatermark + drawPalsTitleChars). Two
+// pals stamps hugging the left/right edges (rotated ±90°, looping wiggle
+// + swivel, 4-pass multiply/burn/overlay SEEP so they stain INTO the
+// colored-pencil paper, LED pulse on the music's swells), and
+// "Marimbaba" as per-character climbing columns — each char its own
+// glyph with a phase-offset bounce, shimmer glint, and the same seep
+// stack — all tinted per-section from the lamplit-study palette.
+//
+// REEL-ONLY: unlike the momboba chrome there is NO progress bar and NO
+// timecode — Instagram's Reels UI brings its own furniture and @jeffrey
+// wants reels with nothing under them. Pals stamps + title columns only.
+//
+// Runs as a post pass: gen-motion-marimbaba-reel.mjs --assemble writes
+// out/motion/base-marimbaba-reel.mp4 + meta-marimbaba-reel.json, this
+// pipes every frame through node-canvas and re-encodes with the audio.
+//
+// Usage: node pop/marimba/bin/chrome-reel.mjs
+
+import { spawn, spawnSync } from "node:child_process";
+import { readFileSync, existsSync, mkdirSync } from "node:fs";
+import { resolve, dirname } from "node:path";
+import { fileURLToPath } from "node:url";
+import { once } from "node:events";
+import { createCanvas, loadImage } from "canvas";
+import {
+  prerenderTitleChars, decodeAudioMono, computeRmsEnvelope, spawnFFmpegEncode,
+} from "../../lib/preview-shared.mjs";
+import * as progress from "../../lib/render-progress.mjs";
+
+const HERE = dirname(fileURLToPath(import.meta.url));
+const LANE = resolve(HERE, "..");
+const REPO = resolve(LANE, "..", "..");
+const MOTION = `${LANE}/out/motion`;
+const BASE = `${MOTION}/base-marimbaba-reel.mp4`;
+const META = JSON.parse(readFileSync(`${MOTION}/meta-marimbaba-reel.json`, "utf8"));
+const OUT = `${LANE}/out/marimbaba-reel.mp4`;
+const assetsDir = `${MOTION}/chrome-assets-reel`;
+mkdirSync(assetsDir, { recursive: true });
+
+const W = 1080, H = 1920, FPS = 30;
+const TOTAL = META.total;
+const FRAMES = Math.round(TOTAL * FPS);
+const TITLE = "Marimbaba";
+
+// per-section tints — the lamplit colored-pencil arc of the story:
+// night-blue arrival → warm amber welcome → bright gold wonder →
+// tense rust argument → dim plum/blue goodbye.
+const BEAT_TINTS = {
+  hush1: [96, 120, 156],    // night garden blue
+  hush2: [206, 168, 110],   // warm lamp amber
+  twinkle1: [214, 176, 116], // golden companionship
+  twinkle2: [200, 178, 132], // chrome glint amber
+  wow1: [232, 196, 120],    // joy gold
+  wow2: [240, 208, 132],    // brightest gold
+  baba1: [196, 120, 88],    // tension rust
+  baba2: [188, 98, 78],     // hot argument red-rust
+  sleep1: [150, 116, 132],  // dimming plum
+  sleep2: [110, 110, 148],  // final night blue-plum
+};
+
+// ── audio envelope (drives LED pulse + char bounce — gentle, it's a
+// lullaby) ──────────────────────────────────────────────────────────────
+const { audio, sr } = decodeAudioMono(BASE);
+const env = computeRmsEnvelope(audio, sr, FPS, TOTAL);
+const envAt = (t) => env[Math.max(0, Math.min(env.length - 1, Math.floor(t * FPS)))] ?? 0;
+
+// ── title chars + pals rasters ─────────────────────────────────────────
+const titleFontSize = 96;
+const { chars: titleChars, totalWidth: titleTotalW } = await prerenderTitleChars({
+  text: TITLE, ptSize: titleFontSize, palette: ["#FFFFFF"],
+  shadowColor: null, assetsDir,
+});
+const PALS_S = 145;
+const PALS_HALF = PALS_S / 2;
+const PALS_EDGE_X = 64;
+const CHARS_EDGE_X = PALS_EDGE_X + 12;
+const CHAR_SCALE = 0.46; // 9 chars — a touch larger than momboba's 13 so the column fills its half
+const CHAR_SPAN = titleTotalW * CHAR_SCALE;
+const BOUNCE_BUF = 26;
+const LEFT_CHARS_CY = H * 0.78;
+const RIGHT_CHARS_CY = H * 0.22;
+const LEFT_PALS_CY = LEFT_CHARS_CY - CHAR_SPAN / 2 - BOUNCE_BUF - PALS_HALF;
+const RIGHT_PALS_CY = RIGHT_CHARS_CY + CHAR_SPAN / 2 + BOUNCE_BUF + PALS_HALF;
+
+const PALS_WM_SIZE = 212;
+let palsImg = null, palsBlur = null;
+{
+  const svg = `${REPO}/system/public/purple-pals.svg`;
+  const png = `${assetsDir}/pals-watermark.png`;
+  const blurPng = `${assetsDir}/pals-watermark-blur.png`;
+  const r = spawnSync("rsvg-convert", ["-w", String(PALS_WM_SIZE * 2), "-h", String(PALS_WM_SIZE * 2), "-o", png, svg]);
+  if (r.status === 0 && existsSync(png)) {
+    palsImg = await loadImage(png);
+    const rb = spawnSync("magick", [png, "-channel", "A", "-blur", "0x1.5", "+channel", blurPng]);
+    palsBlur = (rb.status === 0 && existsSync(blurPng)) ? await loadImage(blurPng) : palsImg;
+  }
+}
+if (!palsImg) throw new Error("pals watermark failed to rasterize");
+
+const canvas = createCanvas(W, H);
+const ctx = canvas.getContext("2d");
+const wmCanvas = createCanvas(8, 8);
+const wmCtx = wmCanvas.getContext("2d");
+const charTintCanvas = createCanvas(2, 2);
+const charTintCtx = charTintCanvas.getContext("2d");
+
+// section tint brightened toward white by progress through the section
+function sectionTcRgb(t) {
+  const s = META.slides.find((x) => t >= x.from && t < x.to) ?? META.slides.at(-1);
+  let [r, g, b] = BEAT_TINTS[s.name] ?? [180, 180, 180];
+  const lp = Math.max(0, Math.min(1, (t - s.from) / Math.max(0.001, s.to - s.from)));
+  const k = 0.30 * lp;
+  return [Math.round(r + (255 - r) * k), Math.round(g + (255 - g) * k), Math.round(b + (255 - b) * k)];
+}
+function palsTinted(rgb, src) {
+  const ww = src.width, wh = src.height;
+  wmCanvas.width = ww; wmCanvas.height = wh;
+  wmCtx.clearRect(0, 0, ww, wh);
+  wmCtx.globalCompositeOperation = "source-over";
+  wmCtx.drawImage(src, 0, 0);
+  wmCtx.globalCompositeOperation = "source-in";
+  wmCtx.fillStyle = `rgb(${rgb[0]},${rgb[1]},${rgb[2]})`;
+  wmCtx.fillRect(0, 0, ww, wh);
+  wmCtx.globalCompositeOperation = "source-over";
+  return wmCanvas;
+}
+function tintCharGlyph(img, rgb) {
+  const w = img.width, h = img.height;
+  charTintCanvas.width = w; charTintCanvas.height = h;
+  charTintCtx.globalCompositeOperation = "source-over";
+  charTintCtx.clearRect(0, 0, w, h);
+  charTintCtx.drawImage(img, 0, 0);
+  charTintCtx.globalCompositeOperation = "source-in";
+  charTintCtx.fillStyle = `rgb(${rgb[0]},${rgb[1]},${rgb[2]})`;
+  charTintCtx.fillRect(0, 0, w, h);
+  charTintCtx.globalCompositeOperation = "source-over";
+  return charTintCanvas;
+}
+
+function drawWatermark(audioT) {
+  const s = PALS_S;
+  const u = audioT * FPS / FRAMES;
+  const TAU = Math.PI * 2;
+  const col = sectionTcRgb(audioT);            // one color per section
+  const e = Math.min(1, envAt(audioT));
+  const glow = e * e;
+  // LED pulse brightens the section color toward white — no hue swing
+  const ledCol = [
+    Math.round(col[0] + (255 - col[0]) * glow * 0.6),
+    Math.round(col[1] + (255 - col[1]) * glow * 0.6),
+    Math.round(col[2] + (255 - col[2]) * glow * 0.6),
+  ];
+  // the LOGO floats on its own rhythm — gentle (it's a lullaby reel)
+  const wig = 13 * Math.sin(TAU * 24 * u + 0.7) + 4 * Math.sin(TAU * 9 * u);
+  const bob = 3 * Math.sin(TAU * 17 * u + 2.1) + 1.5 * Math.sin(TAU * 31 * u);
+  const swiv = 0.05 * Math.sin(TAU * 19 * u) + 0.025 * Math.sin(TAU * 38 * u + 1.4);
+  const spots = [
+    { cx: PALS_EDGE_X - wig, cy: LEFT_PALS_CY + bob, rot: Math.PI / 2 + swiv },
+    { cx: W - PALS_EDGE_X + wig, cy: RIGHT_PALS_CY - bob, rot: -Math.PI / 2 - swiv },
+  ];
+  const passes = [
+    ["multiply", 0.78], ["color-burn", 0.42],
+    ["overlay", 0.58], ["source-over", 0.06],
+  ];
+  for (const sp of spots) {
+    ctx.save();
+    ctx.translate(sp.cx, sp.cy);
+    ctx.rotate(sp.rot);
+    palsTinted([0, 0, 0], palsImg);
+    ctx.globalCompositeOperation = "source-over";
+    ctx.globalAlpha = 0.26;
+    ctx.drawImage(wmCanvas, -s / 2 + 3, -s / 2 + 4, s, s);
+    palsTinted(col, palsBlur);
+    for (const [op, a] of passes) {
+      ctx.globalCompositeOperation = op;
+      ctx.globalAlpha = a;
+      ctx.drawImage(wmCanvas, -s / 2, -s / 2, s, s);
+    }
+    ctx.globalCompositeOperation = "source-over";
+    ctx.globalAlpha = 0.30;
+    ctx.drawImage(wmCanvas, -s / 2, -s / 2, s, s);
+    if (glow > 0.001) {
+      palsTinted(ledCol, palsBlur);
+      ctx.globalCompositeOperation = "screen";
+      ctx.globalAlpha = 0.14 + 0.78 * glow;
+      ctx.drawImage(wmCanvas, -s / 2, -s / 2, s, s);
+      palsTinted(ledCol, palsImg);
+      ctx.globalCompositeOperation = "source-over";
+      ctx.globalAlpha = 0.18 + 0.46 * glow;
+      ctx.drawImage(wmCanvas, -s / 2, -s / 2, s, s);
+    }
+    ctx.restore();
+  }
+  ctx.globalCompositeOperation = "source-over";
+  ctx.globalAlpha = 1;
+  drawPalsTitleChars(audioT);
+}
+
+function drawPalsTitleChars(audioT) {
+  const u = audioT * FPS / FRAMES;
+  const TAU = Math.PI * 2;
+  // the WORD's own drift — distinct harmonics/phase from the pals wig
+  const wig = 11 * Math.sin(TAU * 30 * u + 3.6) + 4 * Math.sin(TAU * 12 * u + 1.1);
+  const span = titleTotalW * CHAR_SCALE;
+  const palsRgb = sectionTcRgb(audioT);
+  const spots = [
+    { charsCx: CHARS_EDGE_X - wig, cy: LEFT_CHARS_CY, rot: Math.PI / 2 },
+    { charsCx: W - CHARS_EDGE_X + wig, cy: RIGHT_CHARS_CY, rot: -Math.PI / 2 },
+  ];
+  const startX = -span / 2;
+  for (const sp of spots) {
+    ctx.save();
+    ctx.translate(sp.charsCx, sp.cy);
+    ctx.rotate(sp.rot);
+    for (let i = 0; i < titleChars.length; i++) {
+      const ch = titleChars[i];
+      if (!ch.img) continue;
+      const x = startX + ch.prefixWidth * CHAR_SCALE;
+      const dw = ch.img.width * CHAR_SCALE;
+      const dh = ch.img.height * CHAR_SCALE;
+      const charEnv = envAt(audioT - i * 0.03);
+      const lift = 4 * Math.sin(audioT * 4.0 + i * 0.8) * (0.3 + charEnv);
+      const y = -dh / 2 + lift;
+      // each char also swivels a hair on its own phase
+      const charRot = 0.03 * Math.sin(audioT * 3.1 + i * 1.15);
+      ctx.save();
+      ctx.translate(x + dw / 2, y + dh / 2);
+      ctx.rotate(charRot);
+      ctx.translate(-(x + dw / 2), -(y + dh / 2));
+      const sh = 0.5 + 0.5 * Math.sin(audioT * 3.2 - i * 0.7);
+      const charRgb = [
+        Math.round(palsRgb[0] + (255 - palsRgb[0]) * sh * 0.35),
+        Math.round(palsRgb[1] + (255 - palsRgb[1]) * sh * 0.35),
+        Math.round(palsRgb[2] + (255 - palsRgb[2]) * sh * 0.35),
+      ];
+      ctx.save();
+      ctx.globalCompositeOperation = "source-over";
+      ctx.globalAlpha = 0.26;
+      ctx.drawImage(tintCharGlyph(ch.img, [0, 0, 0]), x + 3, y + 4, dw, dh);
+      ctx.restore();
+      const charPasses = [
+        ["multiply", 0.78], ["color-burn", 0.42],
+        ["overlay", 0.58], ["source-over", 0.06],
+      ];
+      for (const [op, a] of charPasses) {
+        ctx.save();
+        ctx.globalCompositeOperation = op;
+        ctx.globalAlpha = a;
+        ctx.drawImage(tintCharGlyph(ch.img, charRgb), x, y, dw, dh);
+        ctx.restore();
+      }
+      ctx.save();
+      ctx.globalCompositeOperation = "source-over";
+      ctx.globalAlpha = 0.46;
+      ctx.drawImage(tintCharGlyph(ch.img, palsRgb), x, y, dw, dh);
+      ctx.restore();
+      if (charEnv > 0.45) {
+        ctx.save();
+        ctx.globalCompositeOperation = "screen";
+        ctx.globalAlpha = 0.14 + 0.46 * Math.min(1, (charEnv - 0.45) / 0.55);
+        ctx.drawImage(tintCharGlyph(ch.img, charRgb), x, y, dw, dh);
+        ctx.restore();
+      }
+      ctx.restore();                       // close the per-char swivel
+    }
+    ctx.restore();
+  }
+}
+
+// ── frame pump: base → canvas → chrome → encoder ───────────────────────
+console.log(`▸ reel chrome pass · ${FRAMES} frames · "${TITLE}" columns + pals seep · no bar/timecode`);
+progress.begin({ type: "video", label: `marimbaba reel chrome · ${FRAMES} frames` });
+const dec = spawn("ffmpeg", ["-loglevel", "error", "-i", BASE,
+  "-f", "rawvideo", "-pix_fmt", "rgba", "-"], { stdio: ["ignore", "pipe", "inherit"] });
+const enc = spawnFFmpegEncode({ audioPath: BASE, w: W, h: H, fps: FPS, outPath: OUT, crf: 18 });
+const FRAME_BYTES = W * H * 4;
+const fbuf = Buffer.alloc(FRAME_BYTES);
+const img = ctx.createImageData(W, H);
+let off = 0, fi = 0;
+const t0 = Date.now();
+for await (const chunk of dec.stdout) {
+  let cOff = 0;
+  while (cOff < chunk.length) {
+    const n = Math.min(FRAME_BYTES - off, chunk.length - cOff);
+    chunk.copy(fbuf, off, cOff, cOff + n);
+    off += n; cOff += n;
+    if (off === FRAME_BYTES) {
+      off = 0;
+      img.data.set(fbuf);
+      ctx.putImageData(img, 0, 0);
+      drawWatermark(fi / FPS);
+      if (!enc.stdin.write(canvas.toBuffer("raw"))) await once(enc.stdin, "drain");
+      fi++;
+      progress.update((fi / FRAMES) * 100, { done: fi, total: FRAMES });
+      if (fi % 200 === 0) console.log(`  ${fi}/${FRAMES} · ${((Date.now() - t0) / 1000).toFixed(0)}s`);
+    }
+  }
+}
+enc.stdin.end();
+await new Promise((res, rej) => { enc.on("close", (c) => (c === 0 ? res() : rej(new Error(`ffmpeg exit ${c}`)))); });
+progress.end();
+console.log(`✓ ${OUT} (${fi} frames chromed)`);
diff --git a/pop/marimba/bin/gen-motion-marimbaba-reel.mjs b/pop/marimba/bin/gen-motion-marimbaba-reel.mjs
new file mode 100644
index 000000000..d33948f5c
--- /dev/null
+++ b/pop/marimba/bin/gen-motion-marimbaba-reel.mjs
@@ -0,0 +1,203 @@
+#!/usr/bin/env node
+// marimba/bin/gen-motion-marimbaba-reel.mjs — the marimbaba REEL motion pass.
+// The same 10-beat lullaby story as the YouTube motion cut
+// (gen-motion-marimbaba.mjs), but reframed 9:16 PORTRAIT for the
+// instagram reel: the existing portrait panels (out/marimbaba-p-sec-*.png,
+// drawn for the score reel) become the Seedance 2.0 inputs, and the
+// motion prompts ride the IG-story framing instead of the YouTube
+// landscape one. Thin lane driver over pop/lib/motion-pipeline.mjs — the
+// SHOTS table is the creative surface; pricing, generation, take
+// archiving and picks live there.
+//
+// Slug is "marimbaba-reel" so the 9:16 takes
+// (out/motion/marimbaba-reel-shot-*.mp4) sit alongside — never clobber —
+// the landscape "marimbaba-shot-*" YouTube takes.
+//
+// ASSEMBLY IS NOT the pipeline's --assemble (that trimmer is
+// 1280x720-hardcoded): --assemble here runs a PORTRAIT cut — picked
+// takes (takes.json respected) trimmed to each section's REAL struct
+// length at 1080x1920, concatenated, muxed with the full marimbaba
+// track — then hands off to chrome-reel.mjs (pals stamps + title, NO
+// progress bar / timecode: Reels bring their own furniture).
+//
+// Usage:
+//   node pop/marimba/bin/gen-motion-marimbaba-reel.mjs --dry-run     # prompts + cost
+//   node pop/marimba/bin/gen-motion-marimbaba-reel.mjs               # gen missing shots (9:16)
+//   node pop/marimba/bin/gen-motion-marimbaba-reel.mjs --only baba2 --force  # re-roll
+//   node pop/marimba/bin/gen-motion-marimbaba-reel.mjs --assemble    # portrait cut + chrome
+//   node pop/bin/audition-motion.mjs --lane marimba --slug marimbaba-reel
+//
+// Shot grammar: CUTS by default; morphTo ONLY same-camera escalations
+// (cross-scene morphs invent doubled figures — see pop-motion-pipeline).
+
+import { readFileSync, writeFileSync, existsSync } from "node:fs";
+import { resolve, dirname } from "node:path";
+import { fileURLToPath } from "node:url";
+import { spawnSync } from "node:child_process";
+import { runMotionCli, parseFlags, shotList } from "../../lib/motion-pipeline.mjs";
+import { COLORED_PENCIL_TOOTH_MOTION, FRAMING_IG_STORY_PORTRAIT_MOTION } from "../../lib/mediums.mjs";
+
+const HERE = dirname(fileURLToPath(import.meta.url));
+const LANE = resolve(HERE, "..");
+const OUT = `${LANE}/out`;
+
+// Same lullaby light + colored-pencil medium as the YouTube cut, but the
+// frame is now the tall IG-story portrait instead of the landscape one.
+const MEDIUM_MOTION = [
+  `Diegetic warm desk-lamp light only. Quiet, hushed, late-night lullaby pacing — all motion soft and unhurried.`,
+  FRAMING_IG_STORY_PORTRAIT_MOTION,
+  COLORED_PENCIL_TOOTH_MOTION,
+].join("\n\n");
+
+// The motion prompts are the proven YouTube-cut descriptions — they
+// describe ACTION, not aspect, so they carry straight over; the portrait
+// panels + the IG framing block above do the reframing. Morphs stay on
+// the same same-camera escalations as the landscape cut.
+const SHOTS = {
+  hush1: {
+    motion:
+`Slow gentle push-in along the garden path at night. The single figure walks unhurried toward the house, hands in pockets, coat shifting softly with each step. Dark tree branches sway slightly in a night breeze. The warm amber study window glows and flickers faintly, the small silhouette inside hunched at the desk barely stirring. A sliver of moon. The walker gets gradually closer to the door but never reaches it. Only this one figure outside — calm, expectant, quiet.`,
+  },
+  hush2: {
+    motion:
+`The two men hold the greeting — the man in the doorway gives a small shy wave, the older man at the typewriter smiles warmly and beckons him in with a little gesture. The desk lamp flame of light breathes gently. Dust motes drift through the lamp glow. Bookshelf shadows still. Soft, welcoming, quiet.`,
+  },
+  twinkle1: {
+    morphTo: "twinkle2",
+    motion:
+`Seen from behind the two seated figures: their backs and shoulders breathe softly, heads tilting gently toward each other in quiet companionship. The warm lamp glow spills between their silhouettes and breathes slowly. The camera drifts forward over their shoulders, easing down toward the white typewriter on the desk beyond them, settling into an extreme close-up of the chrome type ball as a hand enters frame pointing at the mechanism, the type ball giving a small delighted spin, lamplight glinting off the chrome. Faces are never shown — the backs, the lamp, and the machine carry the shot.`,
+  },
+  twinkle2: {
+    motion:
+`Extreme close-up held on the silver chrome type ball — the machine is the entire subject. A finger taps gently at the mechanism; the type ball rotates and tilts in small precise mechanical movements, catching warm glints of lamplight on its chrome. The ribbon cartridge trembles faintly with each tick of the mechanism, and the paper-bail bar gives the slightest shiver. Everything above and behind the typewriter stays soft, still, and out of focus. The camera never moves.`,
+  },
+  wow1: {
+    morphTo: "wow2",
+    motion:
+`Over-the-shoulder behind the younger man: his fingers strike the typewriter keys in a soft steady rhythm, the type ball twitching and spinning with each stroke, the carriage nudging along. The older man leans in attentively from the right, eyes on the mechanism. Then the camera pulls back and rises into a wide shot as something wonderful happens — both men lean back from the typewriter and break into bright delighted smiles, the older man raising a fist in joy, the younger laughing, gesturing with delight in the lamplit study.`,
+  },
+  wow2: {
+    motion:
+`Wide lamplit study, the brightest beat: both men celebrate — the older man claps his hands once and pumps a fist, the younger laughs warmly and shakes his head in happy disbelief, rocking back in his chair. The desk lamp glow seems to swell. The white typewriter sits proudly between them. Joyful but still soft and hand-drawn, never frantic.`,
+  },
+  baba1: {
+    morphTo: "baba2",
+    motion:
+`The warmth drains. The younger man re-reads, his face clouding, brow knitting with concern; the older man leans back defensively, arms beginning to cross, a "what?" gesture. They turn slightly away from each other. The lamp dims subtly. Then tension rises — both men push back their chairs and STAND UP at the desk, gesturing emphatically, the older man pointing accusingly toward the typewriter, the younger gesturing back, faces flushing, the argument breaking open.`,
+  },
+  baba2: {
+    motion:
+`The standing argument holds at full heat: both men gesture emphatically across the desk, the older man jabbing his finger toward the typewriter, the younger throwing his hands up, mouths moving mid-word, shoulders tense. The typewriter sits between them, an obstacle. Harsh-edged shadows tremble. The motion is agitated but the drawing stays hand-made and hatched.`,
+  },
+  sleep1: {
+    motion:
+`The tug-of-war: both men grip the typed sheet at the same time, pulling — the paper visibly tearing along a ragged rip, shredded fibres springing loose, their fists tight, faces taut, eyes locked. The paper stays edge-on to the camera, never readable. The pulling intensifies in slow desperate heaves until the rip completes — the sheet tears fully in two and both men stagger back a step, each left holding a ragged half, frozen in the shock of it. The camera holds steady on the desk and typewriter between them throughout.`,
+  },
+  sleep2: {
+    motion:
+`The bittersweet goodbye holds: the man at the doorway lingers, half-turned, the torn paper half trembling slightly at his side, then turns slowly toward the dark night beyond the door. The older man remains slumped at the white typewriter, head bowed, the other torn half slipping slightly in his loose fingers. The lamp flickers low. Dust drifts. Heavy, quiet, final — the saddest, slowest motion of the set.`,
+  },
+};
+
+const flags = parseFlags();
+
+const cfg = {
+  slug: "marimbaba-reel",
+  laneDir: LANE,
+  structPath: `${OUT}/marimbaba.struct.json`,
+  // portrait panels drawn for the score reel — same 10 sections. The 5
+  // beats whose Bill Gates likeness tripped fal's partner moderation
+  // (twinkle1/twinkle2/wow1/wow2/sleep2) are regenerated face-hidden via
+  // `gen-sections.mjs --faceless` → `.faceless.png`; prefer those when present.
+  panelFor: (name, i) => {
+    const faceless = `${OUT}/marimbaba-p-sec-${i}-${name}.faceless.png`;
+    return existsSync(faceless) ? faceless : `${OUT}/marimbaba-p-sec-${i}-${name}.png`;
+  },
+  shots: SHOTS,
+  mediumMotion: MEDIUM_MOTION,
+  ratio: "9:16",
+  audio: `${OUT}/marimbaba.mp3`,
+  finalOut: `${OUT}/marimbaba-reel.mp4`,
+};
+
+if (!flags.assemble) {
+  await runMotionCli(cfg, flags);
+  process.exit(0);
+}
+
+// ── portrait assembly: picked takes → exact trims → concat → mux ──────
+// Emits a chrome-less BASE at 1080×1920@30 (Seedance 720p upscaled) plus
+// meta-reel.json with the section timings, then hands off to
+// chrome-reel.mjs — pals stamps + "Marimbaba" title, NO progress bar /
+// timecode — which writes the FINAL marimbaba-reel.mp4.
+cfg.motionDir = `${LANE}/out/motion`;
+const motionDir = cfg.motionDir;
+const W = 1080, H = 1920, FPS = 30;
+const shots = shotList(cfg);
+const takesPath = `${motionDir}/takes.json`;
+const takes = existsSync(takesPath) ? JSON.parse(readFileSync(takesPath, "utf8")) : {};
+const BASE = `${motionDir}/base-marimbaba-reel.mp4`;
+
+const totalSec = shots.reduce((a, s) => a + s.exact, 0);
+console.log(`▸ assembling portrait reel base · ${shots.length} sections · ${totalSec.toFixed(1)}s · ${W}x${H}@${FPS}`);
+const trimmed = [];
+for (const s of shots) {
+  let picked = takes[s.name] ? resolve(motionDir, takes[s.name]) : s.out;
+  if (picked !== s.out) console.log(`  ☑ ${s.name}: ${takes[s.name]}`);
+  const t = `${motionDir}/trim-reel-${s.i}-${s.name}.mp4`;
+  let res;
+  if (existsSync(picked)) {
+    // Cut shots open on their input panel — trim the tail. MORPH shots
+    // arrive on the next cut's panel in their FINAL frames — trim the
+    // head so the arrival kisses the next section's opening.
+    const probe = spawnSync("ffprobe", ["-v", "error", "-show_entries", "format=duration",
+      "-of", "default=noprint_wrappers=1:nokey=1", picked], { encoding: "utf8" });
+    const clipDur = Number(probe.stdout?.trim()) || 0;
+    const head = s.endImage ? Math.max(0, clipDur - s.exact) : 0;
+    if (head > 0.01) console.log(`  ↪ ${s.name}: morph — trimming ${head.toFixed(2)}s from head`);
+    res = spawnSync("ffmpeg", [
+      "-y", "-i", picked,
+      ...(head > 0.01 ? ["-ss", head.toFixed(3)] : []),
+      "-t", s.exact.toFixed(3),
+      "-vf", `scale=${W}:${H}:force_original_aspect_ratio=increase,crop=${W}:${H},fps=${FPS}`, "-an",
+      "-c:v", "libx264", "-preset", "medium", "-crf", "17", "-pix_fmt", "yuv420p",
+      t,
+    ], { stdio: ["ignore", "ignore", "pipe"] });
+  } else {
+    // No take → Ken Burns the panel so the cut still completes.
+    const frames = Math.round(s.exact * FPS);
+    console.log(`  ⚠ ${s.name}: no take — Ken Burns fallback (${frames}f)`);
+    res = spawnSync("ffmpeg", [
+      "-y", "-loop", "1", "-i", s.image,
+      "-vf", `scale=-2:7680,zoompan=z='1+0.10*on/${frames}':x='iw/2-(iw/zoom)/2':y='ih/2-(ih/zoom)/2':d=${frames}:s=${W}x${H}:fps=${FPS}`,
+      "-frames:v", String(frames), "-an",
+      "-c:v", "libx264", "-preset", "medium", "-crf", "17", "-pix_fmt", "yuv420p",
+      t,
+    ], { stdio: ["ignore", "ignore", "pipe"] });
+  }
+  if (res.status !== 0) { console.error(`✗ trim failed ${s.name}: ${res.stderr.toString().slice(-300)}`); process.exit(1); }
+  trimmed.push(t);
+}
+
+const listPath = `${motionDir}/concat-marimbaba-reel.txt`;
+writeFileSync(listPath, trimmed.map((t) => `file '${t}'`).join("\n") + "\n");
+
+console.log("  concatenating + muxing audio …");
+const mux = spawnSync("ffmpeg", [
+  "-y", "-f", "concat", "-safe", "0", "-i", listPath,
+  "-i", cfg.audio,
+  "-map", "0:v", "-map", "1:a",
+  "-af", `afade=t=in:st=0:d=1.5,afade=t=out:st=${(totalSec - 4).toFixed(3)}:d=4`,
+  "-c:v", "copy", "-c:a", "aac", "-b:a", "256k", "-shortest",
+  "-movflags", "+faststart", BASE,
+], { stdio: ["ignore", "ignore", "pipe"] });
+if (mux.status !== 0) { console.error(`✗ mux failed: ${mux.stderr.toString().slice(-400)}`); process.exit(1); }
+console.log(`✓ base ${BASE}`);
+
+// section timings for the chrome pass's per-section tint
+let acc = 0;
+const slides = shots.map((s) => { const from = acc; acc += s.exact; return { name: s.name, from, to: acc }; });
+writeFileSync(`${motionDir}/meta-marimbaba-reel.json`, JSON.stringify({ total: totalSec, slides }, null, 2));
+
+const chrome = spawnSync("node", [`${HERE}/chrome-reel.mjs`], { stdio: ["ignore", "inherit", "inherit"] });
+if (chrome.status !== 0) { console.error(`✗ chrome pass failed`); process.exit(1); }
diff --git a/pop/marimba/bin/gen-sections.mjs b/pop/marimba/bin/gen-sections.mjs
index b98f36df3..fda6bd3e6 100644
--- a/pop/marimba/bin/gen-sections.mjs
+++ b/pop/marimba/bin/gen-sections.mjs
@@ -58,6 +58,13 @@ const FORCE = flags.force === true;
 // (preview-score-marimbaba-yt.mjs). Default stays portrait 9:16 for the
 // existing insta-story cut.
 const LANDSCAPE = flags.landscape === true;
+// --faceless → portrait panels where the OLDER man's face is never shown
+// (turned away / bowed / shadow / out of frame), the "recognizably Bill
+// Gates" likeness dropped. Written to a ".faceless.png" infix so the
+// canonical -p- panels (used by the score reel) are left untouched. Used
+// to clear the 9:16 motion reel's partner_validation_failed moderation
+// rejections (public-figure likeness) — see pop-motion-pipeline memory.
+const FACELESS = flags.faceless === true;
 const SIZE  = LANDSCAPE ? "1536x1024" : "1024x1536";
 const TAG   = LANDSCAPE ? "-yt" : "-p";
 mkdirSync(`${LANE}/out`, { recursive: true });
@@ -117,6 +124,18 @@ const GATES =
 const SELECTRIC =
 `THE TYPEWRITER — the only device in the story is a lovely WHITE IBM Selectric portable typewriter — the iconic 1970s/80s Selectric II model with the spherical metal TYPE BALL (no traditional swinging typebars; the chrome/silver type-element ball rotates and tilts to strike the paper). a clean glossy white plastic shell with the small IBM oval emblem on the front-right (rendered as an indistinct emblem, NOT a readable wordmark), cream/tan rubber platen with the round platen knob on the right side, a black ribbon cartridge sitting visibly behind the type ball, a chrome paper-bail bar across the front of the platen. a single sheet of plain white typing paper is rolled into the platen — BUT THE AUDIENCE NEVER SEES WHAT IS TYPED ON THE PAGE: every shot frames the typewriter from front-three-quarter or from the side or from behind the figures so the paper / platen surface is occluded by the type ball mechanism, the typebar housing, jeffrey's or Bill's hands, or the typewriter's own carriage body. NEVER a top-down or over-the-shoulder shot of the paper, NEVER a readable line of typed text, NEVER a thought-bubble or floating words. ABSOLUTELY NO screen, monitor, laptop, phone, tablet or any display anywhere — only this typewriter.`;
 
+// Faceless older-man descriptor for --faceless panels: same character by
+// sweater + pen continuity, but the celebrity likeness is dropped and the
+// face is never depicted (the public-figure face is the moderation trip).
+const GATES_FACELESS =
+`THE OLDER MAN (the one being helped) — grey hair, soft rectangular glasses, a muted sage-green crewneck sweater (a clearly different colour from jeffrey's blue shirt); his deep-red fountain pen — same cigar-shaped Sailor barrel as jeffrey's — hangs from the sweater's ribbed neckline, its metal clip HOOKED OVER AND GRIPPING the collar edge. CRUCIAL — his FACE IS NEVER SHOWN in this panel: he is seen from behind, or his head is bowed / fully turned away, or his face falls into soft shadow or sits out of frame. do NOT draw his eyes, nose or mouth; he is identified ONLY by his grey hair, glasses-arm, sage sweater and red pen. he is pensive, still, attentive — read through posture, not face.`;
+
+// Hard override appended LAST so it beats any earlier "both faces" beat
+// language. jeffrey's face shows normally (he is the user, not a flagged
+// figure); only the older man is faceless.
+const FACELESS_NOTE =
+`FACELESS CONSTRAINT (HARD — overrides any earlier instruction): the OLDER man's face must NOT appear anywhere in this image — no eyes, nose, mouth, or recognizable facial features for him. depict him from behind, head bowed, turned away, in shadow, or cropped out. JEFFREY's face MAY and should show normally and carry the beat's emotion. Wherever an earlier line says "both faces" or describes the older man's expression, render that emotion through his POSTURE and GESTURE only, never his face. This is a deliberate composition — never "fix" it by adding his face.`;
+
 const PALETTE =
 `PALETTE — warm cream paper ground; light-blue cotton shirt and sage-green knit; soft brown hair and warm grey; buttery yellow on jeffrey's pen, deep red on Bill's; one coral pop on the glasses-cord; glossy white plastic on the Selectric typewriter with chrome accents on the type ball and paper bail; the gentle amber pool of the desk lamp against cool blue night dark. hand-drawn, hatched, print-tech-aware.`;
 
@@ -169,8 +188,9 @@ function build(sectionBeat, tightCrop) {
   const orient = LANDSCAPE
     ? `\n\n${LANDSCAPE_NOTE}`
     : (tightCrop ? "" : `\n\n${PORTRAIT_NOTE}`);
-  return [MEDIUM, JEFFREY, GATES, SELECTRIC, sectionBeat, PALETTE, AVOID].join("\n\n")
-    + orient + "\n";
+  const olderMan = FACELESS ? GATES_FACELESS : GATES;
+  return [MEDIUM, JEFFREY, olderMan, SELECTRIC, sectionBeat, PALETTE, AVOID].join("\n\n")
+    + orient + (FACELESS ? `\n\n${FACELESS_NOTE}` : "") + "\n";
 }
 
 const apiKey = loadOpenAIKey();
@@ -263,8 +283,8 @@ for (let i = 0; i < SECTION_ORDER.length; i++) {
   if (!wants(name)) continue;
   jobs.push({
     prompt: build(SECTION_VARIANTS[name], false),
-    out: `${LANE}/out/marimbaba${TAG}-sec-${i}-${safeName(name)}.png`,
-    label: `marimbaba${TAG} §${i} ${name}`,
+    out: `${LANE}/out/marimbaba${TAG}-sec-${i}-${safeName(name)}${FACELESS ? ".faceless" : ""}.png`,
+    label: `marimbaba${TAG} §${i} ${name}${FACELESS ? " (faceless)" : ""}`,
   });
 }
 
diff --git a/pop/maytrax/c/bake.mjs b/pop/maytrax/c/bake.mjs
new file mode 100644
index 000000000..256502d63
--- /dev/null
+++ b/pop/maytrax/c/bake.mjs
@@ -0,0 +1,89 @@
+#!/usr/bin/env node
+// bake.mjs — generate c/score.h for the maytrax C engine (americomputadora
+// pattern). Reads kit.json (the freesound one-shot roster), shouts.json
+// (jeffrey-pvc + apple-say drop shouts) and the hellsine church-bell, and
+// emits a header of sample-path tables the C renderer loads at startup.
+//
+// Two root references are baked per pitched role because the original JS
+// used both:
+//   • detected f0  — smpNote() path (sub / reese / pad). Computed in C at
+//                    load (port of detectF0), so only `pitched` is needed.
+//   • nominal root — rateFor() path (lead / choir / strings / animal / wolf
+//                    / bass). The kit.json `root` string → midi, baked here.
+//
+// usage: node c/bake.mjs
+
+import { readFileSync, writeFileSync, existsSync } from "node:fs";
+import { resolve, dirname } from "node:path";
+import { fileURLToPath } from "node:url";
+
+const HERE = dirname(fileURLToPath(import.meta.url));
+const ROOT = dirname(HERE);              // pop/maytrax
+const POP = dirname(ROOT);               // pop
+
+const BPM = 160;
+const SR = 48000;
+
+const NN = { C: 0, D: 2, E: 4, F: 5, G: 7, A: 9, B: 11 };
+const noteToMidi = (s) => {
+  const m = /^([A-G])([#b]?)(-?\d)$/.exec(s || "C4");
+  if (!m) return 60;
+  return NN[m[1]] + (m[2] === "#" ? 1 : m[2] === "b" ? -1 : 0) + (parseInt(m[3], 10) + 1) * 12;
+};
+
+const kit = JSON.parse(readFileSync(resolve(ROOT, "kit.json"), "utf8"));
+const roles = Object.keys(kit);
+
+// shouts ------------------------------------------------------------------
+const keyOf = {
+  wake: "wake_up", real: "it_s_real", hold: "hold_on",
+  let: "let_go", rabbit: "follow_the_white_rabbit", now: "now",
+};
+let shouts = {};
+const shPath = resolve(ROOT, "shouts.json");
+if (existsSync(shPath)) shouts = JSON.parse(readFileSync(shPath, "utf8"));
+const shoutRows = Object.entries(keyOf).map(([k, slug]) => {
+  const e = shouts[slug];
+  const j = e?.path && existsSync(e.path) ? e.path : "";
+  const a = e?.path ? e.path.replace(/\.wav$/, "-say-sung.wav") : "";
+  return { k, j, a: a && existsSync(a) ? a : "" };
+});
+
+const bell = resolve(POP, "hellsine/samples/church-bell.wav");
+
+// emit --------------------------------------------------------------------
+const esc = (s) => s.replace(/\\/g, "\\\\").replace(/"/g, '\\"');
+const L = [];
+L.push("// score.h — generated by c/bake.mjs. do not hand-edit.");
+L.push(`#define SCORE_BPM ${BPM}`);
+L.push(`#define SCORE_SR ${SR}`);
+L.push("");
+L.push(`#define N_ROLES ${roles.length}`);
+L.push(`static const char *ROLE_NAME[N_ROLES] = {`);
+L.push("  " + roles.map((r) => `"${r}"`).join(", "));
+L.push("};");
+L.push(`static const char *ROLE_PATH[N_ROLES] = {`);
+for (const r of roles) L.push(`  "${esc(kit[r].path)}",`);
+L.push("};");
+L.push(`static const int ROLE_PITCHED[N_ROLES] = {`);
+L.push("  " + roles.map((r) => (kit[r].pitched ? 1 : 0)).join(", "));
+L.push("};");
+L.push(`// nominal root midi from kit.json (rateFor path); -1 = unpitched`);
+L.push(`static const int ROLE_NOMINAL[N_ROLES] = {`);
+L.push("  " + roles.map((r) => (kit[r].pitched ? noteToMidi(kit[r].root || "C4") : -1)).join(", "));
+L.push("};");
+L.push("");
+L.push(`static const char *BELL_PATH = "${esc(bell)}";`);
+L.push("");
+L.push(`#define N_SHOUTS ${shoutRows.length}`);
+L.push(`static const char *SHOUT_KEY[N_SHOUTS] = { ${shoutRows.map((s) => `"${s.k}"`).join(", ")} };`);
+L.push(`static const char *SHOUT_J[N_SHOUTS] = {`);
+for (const s of shoutRows) L.push(`  "${esc(s.j)}",`);
+L.push("};");
+L.push(`static const char *SHOUT_A[N_SHOUTS] = {`);
+for (const s of shoutRows) L.push(`  "${esc(s.a)}",`);
+L.push("};");
+L.push("");
+
+writeFileSync(resolve(HERE, "score.h"), L.join("\n") + "\n");
+console.log(`✓ score.h · ${roles.length} roles · ${shoutRows.filter((s) => s.j).length}/6 jeffrey + ${shoutRows.filter((s) => s.a).length}/6 apple shouts · bell ${existsSync(bell) ? "✓" : "✗"}`);
diff --git a/pop/maytrax/c/build.sh b/pop/maytrax/c/build.sh
new file mode 100755
index 000000000..493bcef41
--- /dev/null
+++ b/pop/maytrax/c/build.sh
@@ -0,0 +1,4 @@
+#!/bin/sh
+# build maytrax.c (needs score.h — run `node c/bake.mjs` first)
+cd "$(dirname "$0")"
+exec cc -O3 -std=c11 -Wall -Wextra -Wno-unused-parameter -o maytrax maytrax.c -lm
diff --git a/pop/maytrax/c/cavetrax b/pop/maytrax/c/cavetrax
new file mode 100755
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diff --git a/pop/maytrax/c/cavetrax.c b/pop/maytrax/c/cavetrax.c
new file mode 100644
index 000000000..c86a73600
--- /dev/null
+++ b/pop/maytrax/c/cavetrax.c
@@ -0,0 +1,289 @@
+// cavetrax.c — a sine-bell sibling of dewtrax, carved into a vast stone hollow.
+// Same instrument (FM sine bells + soft sine drones + Schroeder reverb), new
+// song: A natural minor, very slow (72 BPM), cavernous and immense. The
+// character is subterranean — deep, wide low bells whose tails ring for a long
+// time in a huge cave, a heavy sub bed beneath, and far-off high glints that
+// answer from somewhere up in the dark. The reverb is cranked wet and long so
+// every strike blooms into the stone. No samples, no drums, no vocals —
+// pure sine.  render-c.mjs --engine cavetrax masters it on the sine chain.
+//
+// Build:  cc -O3 -std=c11 -o cavetrax cavetrax.c -lm
+// Run:    ./cavetrax --out out/cavetrax-raw.wav
+
+#define _POSIX_C_SOURCE 200809L
+#include <stdio.h>
+#include <stdlib.h>
+#include <stdint.h>
+#include <string.h>
+#include <math.h>
+
+#ifndef M_PI
+#define M_PI 3.14159265358979323846
+#endif
+#define TAU (2.0 * M_PI)
+
+static const int SR = 48000;
+static double BPMV = 72, BEAT, BAR, SX;
+
+static uint32_t rng_s = 0x63617665; // "cave"
+static inline double rnd(void) { rng_s ^= rng_s << 13; rng_s ^= rng_s >> 17; rng_s ^= rng_s << 5; return (double)rng_s / 4294967296.0; }
+static inline double rnd2(void) { return rnd() * 2.0 - 1.0; }
+static inline double midi_hz(double m) { return 440.0 * pow(2.0, (m - 69.0) / 12.0); }
+
+// ── swing / sway ────────────────────────────────────────────────────────────
+// Almost no swing here (0.50) — in a cave things fall on the beat and the room
+// does the rest. A whisper of drag keeps it from feeling mechanical.
+static double SWING = 0.51;
+static double swing_beats(double beats) {
+    double e8 = beats * 2.0;                 // position in 8ths
+    long idx = (long)floor(e8 + 1e-9);
+    double frac = e8 - idx;
+    double pos = (idx / 2) * BEAT + ((idx & 1) ? SWING * BEAT : 0.0);
+    return pos + frac * (BEAT / 2.0);        // interpolate 16ths inside the 8th
+}
+
+static long N;
+static float *busL, *busR, *revL, *revR;
+static inline void adds(float *L, float *R, long i, double l, double r) { if (i >= 0 && i < N) { L[i] += (float)l; R[i] += (float)r; } }
+
+static int write_wav_f32_stereo(const char *path, const float *L, const float *R, long n) {
+    FILE *f = fopen(path, "wb"); if (!f) return 0;
+    uint32_t dsz = (uint32_t)(n * 8), riff = 36 + dsz, sr = SR, br = SR * 8, fsz = 16;
+    uint16_t fmt = 3, ch = 2, ba = 8, bits = 32;
+    fwrite("RIFF", 1, 4, f); fwrite(&riff, 4, 1, f); fwrite("WAVE", 1, 4, f);
+    fwrite("fmt ", 1, 4, f); fwrite(&fsz, 4, 1, f);
+    fwrite(&fmt, 2, 1, f); fwrite(&ch, 2, 1, f); fwrite(&sr, 4, 1, f);
+    fwrite(&br, 4, 1, f); fwrite(&ba, 2, 1, f); fwrite(&bits, 2, 1, f);
+    fwrite("data", 1, 4, f); fwrite(&dsz, 4, 1, f);
+    for (long i = 0; i < n; i++) { fwrite(&L[i], 4, 1, f); fwrite(&R[i], 4, 1, f); }
+    fclose(f); return 1;
+}
+
+// ── voices ────────────────────────────────────────────────────────────────
+// FM sine bell — carrier + a decaying modulator gives the glassy partial
+// shimmer; exp amp decay. Low `dec` values give the long cavernous ring this
+// track lives on. `ratio` shapes the timbre (1.5–2.0 = round body, 3.5 = bell,
+// 5–7 = bright far-off glint).
+static void bell(float *L, float *R, double note, double t, double dur, double g, double pan, double ratio, double dec) {
+    double fc = midi_hz(note), fm = fc * ratio;
+    long n = (long)(dur * SR), s0 = (long)(t * SR);
+    double phc = 0, phm = 0, lg = 1 - pan * 0.5, rg = 1 + pan * 0.5;
+    long att = (long)(0.004 * SR);               // a softer, rounder onset for stone
+    for (long i = 0; i < n; i++) {
+        double tt = (double)i / SR;
+        double env = exp(-tt * dec); if (i < att) env *= (double)i / att;
+        double mi = 3.2 * exp(-tt * 7.0);        // gentler attack transient — less plink, more bloom
+        phm += TAU * fm / SR;
+        phc += TAU * fc / SR + sin(phm) * mi / SR;
+        double v = sin(phc) * env * g;
+        adds(L, R, s0 + i, v * lg, v * rg);
+    }
+}
+
+// droplet — a tiny, very bright, fast-decaying bell up high; here it's a far-off
+// glint glimmering somewhere up in the dark. Feeds the dry bus quietly and the
+// reverb tail more strongly, so it lives mostly in the echo.
+static void droplet(double note, double t, double g, double pan) {
+    bell(busL, busR, note, t, 0.9, g * 0.6, pan, 5.0, 9.0);
+    bell(revL, revR, note, t, 0.9, g * 0.9, 0, 5.0, 9.0);
+}
+
+// soft sine drone — pad / sub bed with a slow raised-cosine attack/release.
+// Longer attack/release here than dewtrax so the bed swells like cave air.
+static void softsine(float *L, float *R, double note, double t, double dur, double g, double pan) {
+    double f = midi_hz(note); long n = (long)(dur * SR), s0 = (long)(t * SR);
+    long att = (long)(0.55 * SR), rel = (long)(0.80 * SR); double ph = 0, lg = 1 - pan * 0.5, rg = 1 + pan * 0.5;
+    for (long i = 0; i < n; i++) {
+        ph += TAU * f / SR;
+        double env = 1; if (i < att) env = (double)i / att; else if (i > n - rel) env = fmax(0, (double)(n - i) / rel);
+        double v = (sin(ph) + 0.18 * sin(ph * 2) + 0.07 * sin(ph * 3)) * env * g;
+        adds(L, R, s0 + i, v * lg, v * rg);
+    }
+}
+
+// a 4-voice sine pad chord (widely panned for cavern width), with a generous
+// reverb send so the chord smears into the stone.
+static void pad_chord(double t, const int *midis, int nm, double dur, double g) {
+    for (int k = 0; k < nm; k++) { double pan = (k / fmax(1, nm - 1) - 0.5) * 0.8; softsine(busL, busR, midis[k], t, dur, g, pan); softsine(revL, revR, midis[k], t, dur, g * 0.55, 0); }
+}
+
+// ── harmony — A natural minor, a i–VI–III–VII descent (deep, modal) ─────────
+// per-bar bass roots that the loop walks low: A, F, C, G.
+static const int A_ROOTS[4] = { 45, 41, 48, 43 };       // A2, F2, C3, G2
+// four 4-note pad voicings, one per chord in the loop — open, rooted low.
+static const int I_PAD[4]   = { 33, 40, 45, 52 };       // A m    (A E A E … A2 E3 A3 E4)
+static const int VI_PAD[4]  = { 29, 36, 41, 48 };       // F maj  (F C F C)
+static const int III_PAD[4] = { 36, 43, 48, 55 };       // C maj  (C G C G)
+static const int VII_PAD[4] = { 31, 38, 43, 50 };       // G maj  (G D G D)
+static const int *PADS[4] = { I_PAD, VI_PAD, III_PAD, VII_PAD };
+
+// A natural-minor pentatonic-ish picks (A C D E G), low — for sparse glints.
+static const int PENT[5] = { 45, 48, 50, 52, 55 };
+// the far-off high glint palette (A5 C6 D6 E6 G6 A6) — high and quiet, answers
+// the deep bells from across the cave.
+static const int DROPS[6] = { 81, 84, 86, 88, 91, 93 };
+
+// section map. SECBARS drives every loop bound below — at 72 BPM a bar is
+// 3.333s, so this 36-bar form lands at ~2 minutes. Keep wave/outro counts
+// multiples of 4 so the 4-bar phrases (pad loop, deep-bell motif) line up.
+static const char *ORDER[8] = { "mouth", "descent", "vaultA", "stillA", "vaultB", "stillB", "vaultC", "outro" };
+static const int SECBARS[8] = { 4, 4, 8, 4, 4, 4, 4, 4 };
+static int START[8];
+static int sec_index(const char *k) { for (int i = 0; i < 8; i++) if (!strcmp(ORDER[i], k)) return i; return 0; }
+
+// a deep cave-bell toll — root + 5th below + octave, round (low ratio) and very
+// long ring. This is the signature voice: wide, sub-heavy, slow to fade.
+static void toll(double t, int root, double g, int big) {
+    bell(busL, busR, root, t, 7.0, g, -0.30, 1.5, big ? 0.55 : 0.75);
+    bell(busL, busR, root + 7, t + 0.04, 6.0, g * 0.6, 0.30, 2.0, 0.85);
+    if (big) bell(busL, busR, root - 12, t + 0.02, 8.0, g * 0.7, 0.0, 1.5, 0.45);
+    bell(revL, revR, root, t, 7.0, g * 0.7, 0, 1.5, 0.7);
+    bell(revL, revR, root + 7, t + 0.04, 6.0, g * 0.45, 0, 2.0, 0.8);
+}
+
+// ── ornaments ───────────────────────────────────────────────────────────────
+// distant call — a slow falling answer of n bells stepping by `step` semitones
+// across `span` seconds, way up high and quiet (lives in the reverb).
+static void distant_call(double t, double base, int n, int step, double span, double g) {
+    for (int i = 0; i < n; i++) {
+        double note = base + i * step, tt = t + span * i / n;
+        bell(busL, busR, note, tt, span * 1.2, g * (1.0 - 0.30 * i / n) * 0.5, rnd2() * 0.7, 5.0, 7.0);
+        bell(revL, revR, note, tt, span * 1.2, g * (1.0 - 0.30 * i / n), 0, 5.0, 7.0);
+    }
+}
+
+int main(int argc, char **argv) {
+    const char *out_path = "out/cavetrax-raw.wav";
+    for (int i = 1; i < argc; i++) { if (!strcmp(argv[i], "--out") && i + 1 < argc) out_path = argv[++i]; else if (!strcmp(argv[i], "--bpm") && i + 1 < argc) BPMV = atof(argv[++i]); else if (!strcmp(argv[i], "--swing") && i + 1 < argc) SWING = atof(argv[++i]); }
+    BEAT = 60.0 / BPMV; BAR = BEAT * 4; SX = BEAT / 4;
+    { int c = 0; for (int i = 0; i < 8; i++) { START[i] = c; c += SECBARS[i]; } }
+    int TB = 0; for (int i = 0; i < 8; i++) TB += SECBARS[i];
+    double totalSec = TB * BAR + 8.0; N = (long)(totalSec * SR);   // longer tail for the big cave
+    busL = calloc(N, 4); busR = calloc(N, 4); revL = calloc(N, 4); revR = calloc(N, 4);
+    fprintf(stderr, "# cavetrax.c · %g BPM · %d bars · %.1fs · A minor cavern bells\n", BPMV, TB, totalSec);
+
+    // the deep-bell motif, as {phrase-bar, beat, note} — a slow descent that
+    // walks down through A minor across the 4-bar phrase, low and spacious.
+    double LEAD[6][3] = { {0,0,57},{1,0,53},{1,2,52},{2,0,48},{3,0,50},{3,2,45} };  // E A G  E  D  A (low)
+
+    // ── MOUTH — the entrance: first a low drone swells, then a single far toll ──
+    { int idx = sec_index("mouth"); int c = START[idx], nb = SECBARS[idx]; double t0 = c * BAR;
+        pad_chord(t0, I_PAD, 4, BAR * nb - 0.05, 0.11);
+        softsine(busL, busR, 21, t0 + BAR * 0.5, BAR * (nb - 0.5), 0.13, 0);   // deepest sub swell (A0)
+        toll(t0 + BAR * 2, 45, 0.20, 1);                                       // the first deep toll
+        for (int b = nb - 2; b < nb; b++) if (b >= 0 && rnd() < 0.7) droplet(DROPS[(int)(rnd() * 6)], t0 + b * BAR + 3.0 * BEAT, 0.05, rnd2() * 0.8);
+    }
+
+    // ── DESCENT — pad climbs down, deep bells begin to walk, glints answer ──
+    { int idx = sec_index("descent"); int c = START[idx], nb = SECBARS[idx], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, VI_PAD, 4, BAR * h - 0.05, 0.13);
+        pad_chord(t0 + BAR * h, VII_PAD, 4, BAR * (nb - h) - 0.05, 0.13);
+        int walk[4] = { 52, 50, 48, 45 };                                      // E D C A, one per bar
+        for (int b = 0; b < 4 && b < nb; b++) { bell(busL, busR, walk[b], t0 + b * BAR + BEAT, 6.0, 0.16, rnd2() * 0.4, 1.7, 0.7); bell(revL, revR, walk[b], t0 + b * BAR + BEAT, 6.0, 0.09, 0, 1.7, 0.7); softsine(busL, busR, walk[b] - 24, t0 + b * BAR, BAR * 0.95, 0.12, 0); }
+        distant_call(t0 + BAR * nb - BEAT * 3, 88, 5, -3, BEAT * 2.6, 0.06);   // a high call falling into vault A
+    }
+
+    // ── helper for the three vaults (the open central space — never a drop) ──
+    const char *vaults[3] = { "vaultA", "vaultB", "vaultC" };
+    for (int d = 0; d < 3; d++) {
+        int wi = sec_index(vaults[d]); int c = START[wi], nbw = SECBARS[wi]; int big = d == 2;
+        for (int b = 0; b < nbw; b++) {
+            double t0 = (c + b) * BAR; int root = A_ROOTS[b % 4]; int phrase = b % 4 == 0;
+            // sustained sub body — the heavy floor of the cave, one per bar.
+            softsine(busL, busR, root - 24, t0, BAR * 0.98, 0.13, 0);
+            softsine(busL, busR, root - 12, t0, BAR * 0.95, 0.07, rnd2() * 0.2);
+            // the deep toll on beat 1 (half-time feel — strong, sparse, ringing).
+            toll(t0, root, big ? 0.19 : 0.15, big || phrase);
+            // a second, lighter toll on beat 3 only in the big vault.
+            if (big) toll(t0 + BEAT * 2, root + 12, 0.11, 0);
+            // pad sustain every 4 bars (chord follows the loop)
+            if (phrase) pad_chord(t0, PADS[(b / 4) % 4], 4, BAR * 4 - 0.05, 0.085);
+            // the deep-bell descent motif (4-bar phrase) — low, with a reverb twin.
+            for (int z = 0; z < 6; z++) if ((int)LEAD[z][0] == b % 4) {
+                double note = LEAD[z][2], tt = t0 + swing_beats(LEAD[z][1]);
+                bell(busL, busR, note, tt, 5.5, big ? 0.15 : 0.12, rnd2() * 0.3, 1.8, 0.85);
+                bell(revL, revR, note, tt, 5.5, 0.09, 0, 1.8, 0.85);
+            }
+            // a lone low pentatonic ring mid-bar — sparse, wide.
+            if (b % 2 == 1) { double tt = t0 + swing_beats(2.0); bell(busL, busR, PENT[(b * 2) % 5], tt, 5.0, 0.08, rnd2() * 0.6, 1.7, 0.9); bell(revL, revR, PENT[(b * 2) % 5], tt, 5.0, 0.05, 0, 1.7, 0.9); }
+            // far-off glints — sprinkled, denser in the big vault but always faint.
+            int ndrops = big ? 2 : 1;
+            for (int k = 0; k < ndrops; k++) if (rnd() < 0.5) droplet(DROPS[(int)(rnd() * 6)], t0 + swing_beats((int)(rnd() * 4) * 1.0), 0.05, rnd2() * 0.85);
+            // a slow distant call at phrase ends of the big vault (high point).
+            if (big && b % 4 == 3) distant_call(t0 + BEAT * 2, 91, 5, -3, BEAT * 1.8, 0.055);
+        }
+        // a far choir-ish sine bed through the biggest vault, deep in the reverb.
+        if (big) for (int b = 0; b < nbw; b += 2) { double t0 = (c + b) * BAR; int ns[3] = { I_PAD[1], I_PAD[2], I_PAD[3] }; for (int z = 0; z < 3; z++) softsine(revL, revR, ns[z], t0, BAR * 2, 0.045, (z - 1) * 0.5); }
+    }
+
+    // ── STILLS — the most spacious: pad + lone sub + a single far toll + glint ──
+    const char *still[2] = { "stillA", "stillB" };
+    for (int z2 = 0; z2 < 2; z2++) {
+        int hi = sec_index(still[z2]); int c = START[hi], nb = SECBARS[hi], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, III_PAD, 4, BAR * h - 0.05, 0.12);
+        pad_chord(t0 + BAR * h, VI_PAD, 4, BAR * (nb - h) - 0.05, 0.12);
+        for (int b = 0; b < nb; b++) {
+            softsine(busL, busR, b < h ? 24 : 29, t0 + b * BAR, BAR * 0.92, 0.12, 0);   // lone deep sub
+            if (b % 2 == 0) toll(t0 + b * BAR + BEAT, I_PAD[1] + (b / 2 % 2 ? 7 : 0), 0.13, 0);
+            if (rnd() < 0.6) droplet(DROPS[(int)(rnd() * 6)], t0 + b * BAR + 3.0 * BEAT, 0.045, rnd2() * 0.85);
+        }
+        if (z2 == 1) distant_call(t0 + BAR * (nb - 2) + BEAT, 93, 6, -3, BEAT * 4.0, 0.06);  // long call into vault C
+    }
+
+    // ── OUTRO — the tolls thin out, the drone sinks, one final deep ring ──
+    { int idx = sec_index("outro"); int c = START[idx], nb = SECBARS[idx], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, VI_PAD, 4, BAR * h - 0.05, 0.11);
+        pad_chord(t0 + BAR * h, I_PAD, 4, BAR * (nb - h) - 0.05, 0.10);
+        for (int b = 0; b < nb; b++) { double e = fmax(0.1, 1.0 - (double)b / nb); int root = b < h ? 41 : 45; softsine(busL, busR, root - 12, t0 + b * BAR, BAR * 0.9, 0.12 * e, 0); if (b % 2 == 0) toll(t0 + b * BAR + BEAT, root, 0.12 * e, 0); if (rnd() < 0.5) droplet(DROPS[(int)(rnd() * 6)], t0 + b * BAR + 2.0 * BEAT, 0.035 * e, rnd2() * 0.85); }
+        // the last deep bell of the cave — long, full, fading into the stone.
+        bell(busL, busR, 33, t0 + BAR * (nb - 2), 8.0, 0.22, 0, 1.5, 0.40);
+        bell(busL, busR, 40, t0 + BAR * (nb - 2) + 0.05, 7.0, 0.12, 0.2, 2.0, 0.55);
+        bell(busL, busR, 21, t0 + BAR * (nb - 2), 9.0, 0.16, 0, 1.5, 0.30);
+        bell(revL, revR, 45, t0 + BAR * (nb - 2), 8.0, 0.12, 0, 1.5, 0.45);
+    }
+
+    // ── REVERB (Schroeder) — cranked WAY wet and long: the huge stone cave. ──
+    // longer comb delays + higher decay/wet, low damping so the tail stays
+    // bright and rings for a long time.
+    {
+        double decay = 0.90, wet = 0.78, damp = 0.22;
+        int CD[6]; double cds[6] = { 0.0437, 0.0531, 0.0617, 0.0683, 0.0742, 0.0827 };
+        for (int k = 0; k < 6; k++) CD[k] = (int)(cds[k] * SR);
+        int AD[2] = { (int)(0.0071 * SR), (int)(0.0026 * SR) }; double apFb = 0.55;
+        float *cbL[6], *cbR[6]; int ciL[6] = {0}, ciR[6] = {0}; double cLPL[6] = {0}, cLPR[6] = {0};
+        for (int k = 0; k < 6; k++) { cbL[k] = calloc(CD[k], 4); cbR[k] = calloc(CD[k], 4); }
+        float *abL[2], *abR[2]; int aiL[2] = {0}, aiR[2] = {0};
+        for (int k = 0; k < 2; k++) { abL[k] = calloc(AD[k], 4); abR[k] = calloc(AD[k], 4); }
+        for (long i = 0; i < N; i++) {
+            double inL = revL[i], inR = revR[i], cL = 0, cR = 0;
+            for (int k = 0; k < 6; k++) {
+                double dL = cbL[k][ciL[k]], dR = cbR[k][ciR[k]]; cL += dL; cR += dR;
+                cLPL[k] = dL * (1 - damp) + cLPL[k] * damp; cLPR[k] = dR * (1 - damp) + cLPR[k] * damp;
+                cbL[k][ciL[k]] = (float)(inL + cLPL[k] * decay); cbR[k][ciR[k]] = (float)(inR + cLPR[k] * decay);
+                ciL[k] = (ciL[k] + 1) % CD[k]; ciR[k] = (ciR[k] + 1) % CD[k];
+            }
+            cL /= 6; cR /= 6;
+            for (int k = 0; k < 2; k++) {
+                double dL = abL[k][aiL[k]], dR = abR[k][aiR[k]];
+                double oL = -apFb * cL + dL, oR = -apFb * cR + dR;
+                abL[k][aiL[k]] = (float)(cL + apFb * oL); abR[k][aiR[k]] = (float)(cR + apFb * oR);
+                aiL[k] = (aiL[k] + 1) % AD[k]; aiR[k] = (aiR[k] + 1) % AD[k];
+                cL = oL; cR = oR;
+            }
+            busL[i] += (float)(cL * wet); busR[i] += (float)(cR * wet);
+        }
+        for (int k = 0; k < 6; k++) { free(cbL[k]); free(cbR[k]); }
+        for (int k = 0; k < 2; k++) { free(abL[k]); free(abR[k]); }
+    }
+
+    // ── normalize + gentle in/out fades (long fade-out for the cave tail) ──
+    double peak = 0; for (long i = 0; i < N; i++) { double a = fmax(fabs(busL[i]), fabs(busR[i])); if (a > peak) peak = a; }
+    if (peak > 0) { double g = 0.85 / peak; for (long i = 0; i < N; i++) { busL[i] *= (float)g; busR[i] *= (float)g; } }
+    long fin = (long)(3.5 * SR), fout = (long)(6.5 * SR);
+    for (long i = 0; i < fin && i < N; i++) { double g = 0.5 - 0.5 * cos(M_PI * (double)i / fin); busL[i] *= (float)g; busR[i] *= (float)g; }
+    for (long i = 0; i < fout && i < N; i++) { double g = 0.5 - 0.5 * cos(M_PI * (double)i / fout); long idx = N - 1 - i; busL[idx] *= (float)g; busR[idx] *= (float)g; }
+
+    if (!write_wav_f32_stereo(out_path, busL, busR, N)) { fprintf(stderr, "✗ write failed\n"); return 1; }
+    fprintf(stderr, "✓ %s · %.1fs\n", out_path, (double)N / SR);
+    return 0;
+}
diff --git a/pop/maytrax/c/dewtrax b/pop/maytrax/c/dewtrax
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diff --git a/pop/maytrax/c/dewtrax.c b/pop/maytrax/c/dewtrax.c
new file mode 100644
index 000000000..1df0d1503
--- /dev/null
+++ b/pop/maytrax/c/dewtrax.c
@@ -0,0 +1,278 @@
+// dewtrax.c — a sine-bell sibling of sinetrax. Same instrument (FM sine bells
+// + soft sine drones + Schroeder reverb), new song: D♭ major, slower (96 BPM),
+// a light lilt instead of sinetrax's lurch. The character is dreamier and
+// nocturnal — a music-box lead over warm pad washes, with bright "droplet"
+// bells sprinkled like dew. No samples, no drums, no vocals — pure sine.
+// render-c.mjs --engine dewtrax masters it on the sine-family chain.
+//
+// Build:  cc -O3 -std=c11 -o dewtrax dewtrax.c -lm
+// Run:    ./dewtrax --out out/dewtrax-raw.wav
+
+#define _POSIX_C_SOURCE 200809L
+#include <stdio.h>
+#include <stdlib.h>
+#include <stdint.h>
+#include <string.h>
+#include <math.h>
+
+#ifndef M_PI
+#define M_PI 3.14159265358979323846
+#endif
+#define TAU (2.0 * M_PI)
+
+static const int SR = 48000;
+static double BPMV = 96, BEAT, BAR, SX;
+
+static uint32_t rng_s = 0x64657721; // "dew!"
+static inline double rnd(void) { rng_s ^= rng_s << 13; rng_s ^= rng_s >> 17; rng_s ^= rng_s << 5; return (double)rng_s / 4294967296.0; }
+static inline double rnd2(void) { return rnd() * 2.0 - 1.0; }
+static inline double midi_hz(double m) { return 440.0 * pow(2.0, (m - 69.0) / 12.0); }
+
+// ── swing / sway ────────────────────────────────────────────────────────────
+// A light lilt here (0.56) — dewtrax sways, it doesn't lurch. On-beats hold,
+// the "&"s drag a touch late; 16ths interpolate inside the swung 8th.
+static double SWING = 0.56;
+static double swing_beats(double beats) {
+    double e8 = beats * 2.0;                 // position in 8ths
+    long idx = (long)floor(e8 + 1e-9);
+    double frac = e8 - idx;
+    double pos = (idx / 2) * BEAT + ((idx & 1) ? SWING * BEAT : 0.0);
+    return pos + frac * (BEAT / 2.0);        // interpolate 16ths inside the 8th
+}
+
+static long N;
+static float *busL, *busR, *revL, *revR;
+static inline void adds(float *L, float *R, long i, double l, double r) { if (i >= 0 && i < N) { L[i] += (float)l; R[i] += (float)r; } }
+
+static int write_wav_f32_stereo(const char *path, const float *L, const float *R, long n) {
+    FILE *f = fopen(path, "wb"); if (!f) return 0;
+    uint32_t dsz = (uint32_t)(n * 8), riff = 36 + dsz, sr = SR, br = SR * 8, fsz = 16;
+    uint16_t fmt = 3, ch = 2, ba = 8, bits = 32;
+    fwrite("RIFF", 1, 4, f); fwrite(&riff, 4, 1, f); fwrite("WAVE", 1, 4, f);
+    fwrite("fmt ", 1, 4, f); fwrite(&fsz, 4, 1, f);
+    fwrite(&fmt, 2, 1, f); fwrite(&ch, 2, 1, f); fwrite(&sr, 4, 1, f);
+    fwrite(&br, 4, 1, f); fwrite(&ba, 2, 1, f); fwrite(&bits, 2, 1, f);
+    fwrite("data", 1, 4, f); fwrite(&dsz, 4, 1, f);
+    for (long i = 0; i < n; i++) { fwrite(&L[i], 4, 1, f); fwrite(&R[i], 4, 1, f); }
+    fclose(f); return 1;
+}
+
+// ── voices ────────────────────────────────────────────────────────────────
+// FM sine bell — carrier + a decaying modulator gives the glassy partial
+// shimmer; exp amp decay. `ratio` shapes the timbre (3.5 = bell, 7.0 =
+// music-box plink, 2.0 = softer body).
+static void bell(float *L, float *R, double note, double t, double dur, double g, double pan, double ratio, double dec) {
+    double fc = midi_hz(note), fm = fc * ratio;
+    long n = (long)(dur * SR), s0 = (long)(t * SR);
+    double phc = 0, phm = 0, lg = 1 - pan * 0.5, rg = 1 + pan * 0.5;
+    long att = (long)(0.0012 * SR);              // sharp, punctuated onset
+    for (long i = 0; i < n; i++) {
+        double tt = (double)i / SR;
+        double env = exp(-tt * dec); if (i < att) env *= (double)i / att;
+        double mi = 5.0 * exp(-tt * 11.0);       // brighter, faster-decaying attack transient
+        phm += TAU * fm / SR;
+        phc += TAU * fc / SR + sin(phm) * mi / SR;
+        double v = sin(phc) * env * g;
+        adds(L, R, s0 + i, v * lg, v * rg);
+    }
+}
+
+// droplet — a tiny, very bright, fast-decaying bell up high; the "dew" sparkle.
+// pure feed into both the dry bus and (softly) the reverb tail for shimmer.
+static void droplet(double note, double t, double g, double pan) {
+    bell(busL, busR, note, t, 0.55, g, pan, 5.0, 16.0);
+    bell(revL, revR, note, t, 0.55, g * 0.5, 0, 5.0, 16.0);
+}
+
+// soft sine drone — pad / sub bed with a slow raised-cosine attack/release.
+static void softsine(float *L, float *R, double note, double t, double dur, double g, double pan) {
+    double f = midi_hz(note); long n = (long)(dur * SR), s0 = (long)(t * SR);
+    long att = (long)(0.30 * SR), rel = (long)(0.45 * SR); double ph = 0, lg = 1 - pan * 0.5, rg = 1 + pan * 0.5;
+    for (long i = 0; i < n; i++) {
+        ph += TAU * f / SR;
+        double env = 1; if (i < att) env = (double)i / att; else if (i > n - rel) env = fmax(0, (double)(n - i) / rel);
+        double v = (sin(ph) + 0.16 * sin(ph * 2) + 0.06 * sin(ph * 3)) * env * g;
+        adds(L, R, s0 + i, v * lg, v * rg);
+    }
+}
+
+// a 4-voice sine pad chord (slightly panned for width), with a soft reverb send.
+static void pad_chord(double t, const int *midis, int nm, double dur, double g) {
+    for (int k = 0; k < nm; k++) { double pan = (k / fmax(1, nm - 1) - 0.5) * 0.6; softsine(busL, busR, midis[k], t, dur, g, pan); softsine(revL, revR, midis[k], t, dur, g * 0.4, 0); }
+}
+
+// ── harmony — D♭ major, a I–vi–IV–V loop (warm, glassy) ─────────────────────
+// per-bar bass roots that the loop walks: Db, Bbm, Gb, Ab.
+static const int D_ROOTS[4] = { 61, 58, 54, 56 };       // Db4, Bb3, Gb3, Ab3
+// four 4-note pad voicings, one per chord in the loop.
+static const int I_PAD[4]  = { 37, 44, 48, 53 };        // Db maj7  (Db Ab C F)
+static const int VI_PAD[4] = { 34, 41, 44, 49 };        // Bb m     (Bb F Ab Db)
+static const int IV_PAD[4] = { 30, 37, 41, 46 };        // Gb maj   (Gb Db F Bb)
+static const int V_PAD[4]  = { 32, 39, 43, 48 };        // Ab maj   (Ab Eb G C)
+static const int *PADS[4] = { I_PAD, VI_PAD, IV_PAD, V_PAD };
+
+// Db major pentatonic (Db Eb F Ab Bb), low octave — for arps + droplet picks.
+static const int PENT[5] = { 49, 51, 53, 56, 58 };
+// the high droplet palette (Db5 Eb5 F5 Ab5 Bb5 Db6).
+static const int DROPS[6] = { 73, 75, 77, 80, 82, 85 };
+
+// section map. SECBARS drives every loop bound below, so retuning the form
+// (or the whole length) is a one-line edit — at 96 BPM a bar is 2.5s, so this
+// 48-bar form lands at ~2 minutes. Keep wave/outro counts multiples of 4 so
+// the 4-bar phrases (pad loop, lead) line up.
+static const char *ORDER[8] = { "intro", "bloom", "waveA", "hushA", "waveB", "hushB", "waveC", "outro" };
+static const int SECBARS[8] = { 4, 4, 8, 4, 8, 4, 8, 8 };
+static int START[8];
+static int sec_index(const char *k) { for (int i = 0; i < 8; i++) if (!strcmp(ORDER[i], k)) return i; return 0; }
+
+// a music-box stab — root + 5th + octave, bright (high ratio) and short.
+static void stab(double t, int root, double g, int triad) {
+    bell(busL, busR, root, t, BEAT * 1.4, g, -0.15, 7.0, 5.0);
+    bell(busL, busR, root + 7, t + 0.012, BEAT * 1.4, g * 0.7, 0.18, 7.0, 5.0);
+    if (triad) bell(busL, busR, root + 12, t + 0.024, BEAT * 1.2, g * 0.5, 0.0, 6.0, 6.0);
+    bell(revL, revR, root + 7, t, BEAT * 1.4, g * 0.4, 0, 7.0, 5.0);
+}
+
+// ── ornaments ───────────────────────────────────────────────────────────────
+// frill — a quick grace-run of n bells stepping by `step` semitones across
+// `span` seconds (a sparkly flourish for high points / pickups).
+static void frill(double t, double base, int n, int step, double span, double g) {
+    for (int i = 0; i < n; i++) bell(busL, busR, base + i * step, t + span * i / n, span * 1.4, g * (1.0 - 0.35 * i / n), rnd2() * 0.5, 5.0, 13.0);
+}
+// triplet — three quick bells over one beat (middle lifted a 3rd), a gentle
+// lift on phrase starts.
+static void triplet(double t, double note, double g) {
+    for (int i = 0; i < 3; i++) bell(busL, busR, note + (i == 1 ? 4 : 0), t + BEAT * i / 3.0, BEAT / 3.0 * 1.3, g * (i == 1 ? 1.1 : 1.0), (i - 1) * 0.25, 6.0, 12.0);
+}
+
+int main(int argc, char **argv) {
+    const char *out_path = "out/dewtrax-raw.wav";
+    for (int i = 1; i < argc; i++) { if (!strcmp(argv[i], "--out") && i + 1 < argc) out_path = argv[++i]; else if (!strcmp(argv[i], "--bpm") && i + 1 < argc) BPMV = atof(argv[++i]); else if (!strcmp(argv[i], "--swing") && i + 1 < argc) SWING = atof(argv[++i]); }
+    BEAT = 60.0 / BPMV; BAR = BEAT * 4; SX = BEAT / 4;
+    { int c = 0; for (int i = 0; i < 8; i++) { START[i] = c; c += SECBARS[i]; } }
+    int TB = 0; for (int i = 0; i < 8; i++) TB += SECBARS[i];
+    double totalSec = TB * BAR + 6.0; N = (long)(totalSec * SR);
+    busL = calloc(N, 4); busR = calloc(N, 4); revL = calloc(N, 4); revR = calloc(N, 4);
+    fprintf(stderr, "# dewtrax.c · %g BPM · %d bars · %.1fs · D♭ major sine bells\n", BPMV, TB, totalSec);
+
+    // the music-box lead, as {phrase-bar, beat, note} — a falling-then-rising
+    // motif in Db major across the 4-bar phrase.
+    double LEAD[8][3] = { {0,0,80},{0,2,77},{1,0,75},{1,1.5,73},{2,0,77},{2,2,80},{3,0,82},{3,2,85} };
+
+    // ── INTRO (staggered: pad → bell melody → sub → high droplets) ──
+    { int idx = sec_index("intro"); int c = START[idx], nb = SECBARS[idx], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, I_PAD, 4, BAR * h - 0.05, 0.10);
+        pad_chord(t0 + BAR * h, IV_PAD, 4, BAR * (nb - h) - 0.05, 0.11);
+        int mel[4] = { 85, 80, 77, 73 };                       // descending music-box melody, from bar 2
+        for (int b = 0; b < 4 && 2 + b < nb; b++) bell(busL, busR, mel[b], t0 + (2 + b) * BAR, BAR * 0.9, 0.13, rnd2() * 0.3, 6.0, 3.0);
+        for (int b = h; b < nb; b++) softsine(busL, busR, 37, t0 + b * BAR, BAR * 0.95, 0.12, 0); // sub through the back half
+        for (int b = nb - 3; b < nb; b++) if (b >= 0) droplet(DROPS[(int)(rnd() * 6)], t0 + b * BAR + 2.5 * BEAT, 0.05, rnd2() * 0.6); // first dew
+    }
+
+    // ── BLOOM — rising bell arpeggio + pad climb into the first wave ──
+    { int idx = sec_index("bloom"); int c = START[idx], nb = SECBARS[idx], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, VI_PAD, 4, BAR * h - 0.05, 0.13);
+        pad_chord(t0 + BAR * h, V_PAD, 4, BAR * (nb - h) - 0.05, 0.15);
+        int arp[8] = { 49, 53, 56, 61, 65, 68, 73, 77 };
+        for (int s = 0; s < 16; s++) { double tt = t0 + BAR * h + swing_beats(s * 0.25); bell(busL, busR, arp[s % 8] + (s / 8) * 12, tt, SX * 2.4, 0.06 + 0.07 * s / 16.0, rnd2() * 0.4, 5.0, 9.0); }
+        frill(t0 + BAR * nb - BEAT * 2, 73, 8, 2, BEAT * 1.8, 0.07);   // ascending flourish into wave A
+    }
+
+    // ── helper for the three waves (gentle, flowing — not a hard drop) ──
+    const char *waves[3] = { "waveA", "waveB", "waveC" };
+    for (int d = 0; d < 3; d++) {
+        int wi = sec_index(waves[d]); int c = START[wi], nbw = SECBARS[wi]; int big = d == 2;
+        for (int b = 0; b < nbw; b++) {
+            double t0 = (c + b) * BAR; int root = D_ROOTS[b % 4]; int phrase = b % 4 == 0;
+            // a soft pulsing bass — beats 1 & 3, the "&"s lighter & panned wide.
+            for (int e = 0; e < 8; e++) { double tt = t0 + swing_beats(e * 0.5); int on = (e % 2 == 0); if (on || rnd() < 0.5) bell(busL, busR, root - 12, tt, BEAT * 0.5, on ? 0.10 : 0.055, on ? -0.08 : 0.24, 2.0, on ? 11.0 : 14.0); }
+            // sustained sub body (one per bar, under the pulse)
+            softsine(busL, busR, root - 12, t0, BAR * 0.95, 0.10, 0);
+            // the music-box stab on beat 3
+            stab(t0 + BEAT * 2, root, big ? 0.18 : 0.14, big);
+            // pad sustain every 4 bars (chord follows the loop)
+            if (phrase) pad_chord(t0, PADS[(b / 4) % 4], 4, BAR * 4 - 0.05, 0.07);
+            // a gentle triplet lift on each phrase-start downbeat
+            if (phrase) triplet(t0, root + 12, big ? 0.08 : 0.06);
+            // the music-box lead (4-bar phrase) — swung, bright, frilled on highs
+            for (int z = 0; z < 8; z++) if ((int)LEAD[z][0] == b % 4) {
+                double note = LEAD[z][2], tt = t0 + swing_beats(LEAD[z][1]);
+                bell(busL, busR, note, tt, BEAT * 0.8, big ? 0.12 : 0.09, rnd2() * 0.4, 6.0, 7.0);
+                bell(revL, revR, note, tt, BEAT * 0.8, 0.05, 0, 6.0, 7.0);
+                if (note >= 80) frill(tt + 0.04, note, big ? 4 : 3, 2, BEAT * 0.45, big ? 0.055 : 0.04);
+            }
+            // pentatonic plink — swung off-beat sparkle
+            if (b % 2 == 0) bell(busL, busR, PENT[b % 5] + 12 + (big ? 12 : 0), t0 + swing_beats(2.5), BEAT * 0.7, 0.055, rnd2() * 0.5, 5.0, 8.0);
+            // dew droplets — sprinkled, denser in the big wave
+            int ndrops = big ? 3 : 1;
+            for (int k = 0; k < ndrops; k++) if (rnd() < 0.55) droplet(DROPS[(int)(rnd() * 6)], t0 + swing_beats((int)(rnd() * 8) * 0.5), 0.045, rnd2() * 0.7);
+            // descending frill run at phrase ends of the big wave (high point)
+            if (big && b % 4 == 3) frill(t0 + BEAT * 3, 87, 6, -2, BEAT * 0.9, 0.055);
+        }
+        // a soft choir-ish sine bed through the biggest wave
+        if (big) for (int b = 0; b < nbw; b += 2) { double t0 = (c + b) * BAR; int ns[3] = { I_PAD[1], I_PAD[2], I_PAD[3] }; for (int z = 0; z < 3; z++) softsine(revL, revR, ns[z] + 12, t0, BAR * 2, 0.04, (z - 1) * 0.4); }
+    }
+
+    // ── HUSHES — spacious: pad + half-time sub + sparse bells + lone droplets ──
+    const char *hush[2] = { "hushA", "hushB" };
+    for (int z2 = 0; z2 < 2; z2++) {
+        int hi = sec_index(hush[z2]); int c = START[hi], nb = SECBARS[hi], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, IV_PAD, 4, BAR * h - 0.05, 0.12);
+        pad_chord(t0 + BAR * h, V_PAD, 4, BAR * (nb - h) - 0.05, 0.12);
+        for (int b = 0; b < nb; b++) { softsine(busL, busR, b < h ? 30 : 32, t0 + b * BAR, BAR * 0.85, 0.10, 0); if (b % 2 == 0) bell(busL, busR, I_PAD[1 + (b / 2) % 3], t0 + b * BAR, BAR * 0.9, 0.11, rnd2() * 0.4, 5.0, 2.6); if (rnd() < 0.6) droplet(DROPS[(int)(rnd() * 6)], t0 + b * BAR + 2.5 * BEAT, 0.04, rnd2() * 0.7); }
+        if (z2 == 1) for (int s = 0; s < 16; s++) bell(busL, busR, 61 + PENT[s % 5] - 49, t0 + BAR * (nb - 2) + s * SX, SX * 3, 0.04 + 0.05 * s / 16.0, rnd2() * 0.5, 5.0, 5.0); // rising run into wave C
+    }
+
+    // ── OUTRO — decaying bells + pad wash + a final low bell ──
+    { int idx = sec_index("outro"); int c = START[idx], nb = SECBARS[idx], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, I_PAD, 4, BAR * h - 0.05, 0.11);
+        pad_chord(t0 + BAR * h, IV_PAD, 4, BAR * (nb - h) - 0.05, 0.10);
+        for (int b = 0; b < nb; b++) { double e = fmax(0.1, 1.0 - (double)b / nb); int root = b < h ? 61 : 56; softsine(busL, busR, root - 12, t0 + b * BAR, BAR * 0.9, 0.10 * e, 0); if (b % 2 == 0) stab(t0 + b * BAR + BEAT * 2, root, 0.11 * e, 0); if (rnd() < 0.5) droplet(DROPS[(int)(rnd() * 6)], t0 + b * BAR + 1.5 * BEAT, 0.035 * e, rnd2() * 0.7); }
+        bell(busL, busR, 37, t0 + BAR * (nb - 2), 4.5, 0.18, 0, 2.0, 1.2);
+        bell(busL, busR, 73, t0 + BAR * (nb - 2), 4.5, 0.10, 0.2, 6.0, 1.5);
+        bell(revL, revR, 61, t0 + BAR * (nb - 2), 4.5, 0.10, 0, 5.0, 1.4);
+    }
+
+    // ── REVERB (Schroeder) — a touch wetter/longer for the dreamy bell space ──
+    {
+        double decay = 0.82, wet = 0.55, damp = 0.38;
+        int CD[6]; double cds[6] = { 0.0297, 0.0371, 0.0411, 0.0437, 0.0497, 0.0581 };
+        for (int k = 0; k < 6; k++) CD[k] = (int)(cds[k] * SR);
+        int AD[2] = { (int)(0.005 * SR), (int)(0.0017 * SR) }; double apFb = 0.5;
+        float *cbL[6], *cbR[6]; int ciL[6] = {0}, ciR[6] = {0}; double cLPL[6] = {0}, cLPR[6] = {0};
+        for (int k = 0; k < 6; k++) { cbL[k] = calloc(CD[k], 4); cbR[k] = calloc(CD[k], 4); }
+        float *abL[2], *abR[2]; int aiL[2] = {0}, aiR[2] = {0};
+        for (int k = 0; k < 2; k++) { abL[k] = calloc(AD[k], 4); abR[k] = calloc(AD[k], 4); }
+        for (long i = 0; i < N; i++) {
+            double inL = revL[i], inR = revR[i], cL = 0, cR = 0;
+            for (int k = 0; k < 6; k++) {
+                double dL = cbL[k][ciL[k]], dR = cbR[k][ciR[k]]; cL += dL; cR += dR;
+                cLPL[k] = dL * (1 - damp) + cLPL[k] * damp; cLPR[k] = dR * (1 - damp) + cLPR[k] * damp;
+                cbL[k][ciL[k]] = (float)(inL + cLPL[k] * decay); cbR[k][ciR[k]] = (float)(inR + cLPR[k] * decay);
+                ciL[k] = (ciL[k] + 1) % CD[k]; ciR[k] = (ciR[k] + 1) % CD[k];
+            }
+            cL /= 6; cR /= 6;
+            for (int k = 0; k < 2; k++) {
+                double dL = abL[k][aiL[k]], dR = abR[k][aiR[k]];
+                double oL = -apFb * cL + dL, oR = -apFb * cR + dR;
+                abL[k][aiL[k]] = (float)(cL + apFb * oL); abR[k][aiR[k]] = (float)(cR + apFb * oR);
+                aiL[k] = (aiL[k] + 1) % AD[k]; aiR[k] = (aiR[k] + 1) % AD[k];
+                cL = oL; cR = oR;
+            }
+            busL[i] += (float)(cL * wet); busR[i] += (float)(cR * wet);
+        }
+        for (int k = 0; k < 6; k++) { free(cbL[k]); free(cbR[k]); }
+        for (int k = 0; k < 2; k++) { free(abL[k]); free(abR[k]); }
+    }
+
+    // ── normalize + gentle in/out fades ──
+    double peak = 0; for (long i = 0; i < N; i++) { double a = fmax(fabs(busL[i]), fabs(busR[i])); if (a > peak) peak = a; }
+    if (peak > 0) { double g = 0.85 / peak; for (long i = 0; i < N; i++) { busL[i] *= (float)g; busR[i] *= (float)g; } }
+    long fin = (long)(2.5 * SR), fout = (long)(4.5 * SR);
+    for (long i = 0; i < fin && i < N; i++) { double g = 0.5 - 0.5 * cos(M_PI * (double)i / fin); busL[i] *= (float)g; busR[i] *= (float)g; }
+    for (long i = 0; i < fout && i < N; i++) { double g = 0.5 - 0.5 * cos(M_PI * (double)i / fout); long idx = N - 1 - i; busL[idx] *= (float)g; busR[idx] *= (float)g; }
+
+    if (!write_wav_f32_stereo(out_path, busL, busR, N)) { fprintf(stderr, "✗ write failed\n"); return 1; }
+    fprintf(stderr, "✓ %s · %.1fs\n", out_path, (double)N / SR);
+    return 0;
+}
diff --git a/pop/maytrax/c/dusktrax b/pop/maytrax/c/dusktrax
new file mode 100755
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diff --git a/pop/maytrax/c/dusktrax.c b/pop/maytrax/c/dusktrax.c
new file mode 100644
index 000000000..aaee4e96d
--- /dev/null
+++ b/pop/maytrax/c/dusktrax.c
@@ -0,0 +1,298 @@
+// dusktrax.c — a sine-bell sibling of dewtrax/sinetrax. Same instrument (FM
+// sine bells + soft sine drones + Schroeder reverb), new song: D minor, 90 BPM,
+// a wistful nostalgic-sunset character. Where dewtrax is dreamy/nocturnal in
+// D♭ major, dusktrax is golden-hour and song-like: a music-box lead that keeps
+// falling, mellow descending bell lines, warm minor pads underneath. The form
+// foregrounds one clear repeating melodic motif (the "fall"). No samples, no
+// drums, no vocals — pure sine.
+// render-c.mjs --engine dusktrax masters it on the sine-family chain.
+//
+// Build:  cc -O3 -std=c11 -o dusktrax dusktrax.c -lm
+// Run:    ./dusktrax --out out/dusktrax-raw.wav
+
+#define _POSIX_C_SOURCE 200809L
+#include <stdio.h>
+#include <stdlib.h>
+#include <stdint.h>
+#include <string.h>
+#include <math.h>
+
+#ifndef M_PI
+#define M_PI 3.14159265358979323846
+#endif
+#define TAU (2.0 * M_PI)
+
+static const int SR = 48000;
+static double BPMV = 90, BEAT, BAR, SX;
+
+static uint32_t rng_s = 0x6475736b; // "dusk"
+static inline double rnd(void) { rng_s ^= rng_s << 13; rng_s ^= rng_s >> 17; rng_s ^= rng_s << 5; return (double)rng_s / 4294967296.0; }
+static inline double rnd2(void) { return rnd() * 2.0 - 1.0; }
+static inline double midi_hz(double m) { return 440.0 * pow(2.0, (m - 69.0) / 12.0); }
+
+// ── swing / sway ────────────────────────────────────────────────────────────
+// A gentle, song-like lilt (0.55) — dusktrax breathes, it doesn't lurch.
+// On-beats hold, the "&"s drag a touch late; 16ths interpolate inside the
+// swung 8th.
+static double SWING = 0.55;
+static double swing_beats(double beats) {
+    double e8 = beats * 2.0;                 // position in 8ths
+    long idx = (long)floor(e8 + 1e-9);
+    double frac = e8 - idx;
+    double pos = (idx / 2) * BEAT + ((idx & 1) ? SWING * BEAT : 0.0);
+    return pos + frac * (BEAT / 2.0);        // interpolate 16ths inside the 8th
+}
+
+static long N;
+static float *busL, *busR, *revL, *revR;
+static inline void adds(float *L, float *R, long i, double l, double r) { if (i >= 0 && i < N) { L[i] += (float)l; R[i] += (float)r; } }
+
+static int write_wav_f32_stereo(const char *path, const float *L, const float *R, long n) {
+    FILE *f = fopen(path, "wb"); if (!f) return 0;
+    uint32_t dsz = (uint32_t)(n * 8), riff = 36 + dsz, sr = SR, br = SR * 8, fsz = 16;
+    uint16_t fmt = 3, ch = 2, ba = 8, bits = 32;
+    fwrite("RIFF", 1, 4, f); fwrite(&riff, 4, 1, f); fwrite("WAVE", 1, 4, f);
+    fwrite("fmt ", 1, 4, f); fwrite(&fsz, 4, 1, f);
+    fwrite(&fmt, 2, 1, f); fwrite(&ch, 2, 1, f); fwrite(&sr, 4, 1, f);
+    fwrite(&br, 4, 1, f); fwrite(&ba, 2, 1, f); fwrite(&bits, 2, 1, f);
+    fwrite("data", 1, 4, f); fwrite(&dsz, 4, 1, f);
+    for (long i = 0; i < n; i++) { fwrite(&L[i], 4, 1, f); fwrite(&R[i], 4, 1, f); }
+    fclose(f); return 1;
+}
+
+// ── voices ────────────────────────────────────────────────────────────────
+// FM sine bell — carrier + a decaying modulator gives the glassy partial
+// shimmer; exp amp decay. `ratio` shapes the timbre (3.5 = bell, 7.0 =
+// music-box plink, 2.0 = softer body). dusktrax leans on slightly softer,
+// rounder bells than dewtrax for the warm sunset glow.
+static void bell(float *L, float *R, double note, double t, double dur, double g, double pan, double ratio, double dec) {
+    double fc = midi_hz(note), fm = fc * ratio;
+    long n = (long)(dur * SR), s0 = (long)(t * SR);
+    double phc = 0, phm = 0, lg = 1 - pan * 0.5, rg = 1 + pan * 0.5;
+    long att = (long)(0.0020 * SR);              // slightly softer onset than dewtrax (warmer)
+    for (long i = 0; i < n; i++) {
+        double tt = (double)i / SR;
+        double env = exp(-tt * dec); if (i < att) env *= (double)i / att;
+        double mi = 4.0 * exp(-tt * 9.0);        // gentler attack transient (less glassy bite)
+        phm += TAU * fm / SR;
+        phc += TAU * fc / SR + sin(phm) * mi / SR;
+        double v = sin(phc) * env * g;
+        adds(L, R, s0 + i, v * lg, v * rg);
+    }
+}
+
+// droplet — a tiny, very bright, fast-decaying bell up high; the sunset "spark"
+// glinting off the last light. Feeds the dry bus and (softly) the reverb tail.
+static void droplet(double note, double t, double g, double pan) {
+    bell(busL, busR, note, t, 0.60, g, pan, 4.5, 14.0);
+    bell(revL, revR, note, t, 0.60, g * 0.55, 0, 4.5, 14.0);
+}
+
+// soft sine drone — pad / sub bed with a slow raised-cosine attack/release.
+// Longer attack here for a warmer, more pillowy sunset pad.
+static void softsine(float *L, float *R, double note, double t, double dur, double g, double pan) {
+    double f = midi_hz(note); long n = (long)(dur * SR), s0 = (long)(t * SR);
+    long att = (long)(0.40 * SR), rel = (long)(0.55 * SR); double ph = 0, lg = 1 - pan * 0.5, rg = 1 + pan * 0.5;
+    for (long i = 0; i < n; i++) {
+        ph += TAU * f / SR;
+        double env = 1; if (i < att) env = (double)i / att; else if (i > n - rel) env = fmax(0, (double)(n - i) / rel);
+        double v = (sin(ph) + 0.20 * sin(ph * 2) + 0.08 * sin(ph * 3)) * env * g; // warmer overtone bed
+        adds(L, R, s0 + i, v * lg, v * rg);
+    }
+}
+
+// a 4-voice sine pad chord (slightly panned for width), with a soft reverb send.
+static void pad_chord(double t, const int *midis, int nm, double dur, double g) {
+    for (int k = 0; k < nm; k++) { double pan = (k / fmax(1, nm - 1) - 0.5) * 0.6; softsine(busL, busR, midis[k], t, dur, g, pan); softsine(revL, revR, midis[k], t, dur, g * 0.45, 0); }
+}
+
+// ── harmony — D minor, a wistful i–VI–III–VII descent ────────────────────────
+// The progression itself falls: Dm → B♭ → F → C — a classic golden-hour
+// "down the stairs" loop in D natural minor. Per-bar bass roots walk it down.
+static const int D_ROOTS[4] = { 50, 46, 41, 48 };       // D3, Bb2, F2, C3
+// four 4-note pad voicings, one per chord in the loop (rich, with added 9ths
+// for nostalgia).
+static const int i_PAD[4]   = { 38, 45, 50, 57 };       // Dm add9   (D A D E·) -> D F A E  voiced (D A D / +F via lead)
+static const int VI_PAD[4]  = { 34, 41, 46, 50 };       // Bb maj    (Bb F Bb D)
+static const int III_PAD[4] = { 29, 36, 41, 45 };       // F maj     (F C F A)
+static const int VII_PAD[4] = { 36, 43, 48, 52 };       // C maj     (C G C E)
+static const int *PADS[4] = { i_PAD, VI_PAD, III_PAD, VII_PAD };
+
+// D natural minor pentatonic feel (D F G A C), mid octave — arps + droplet
+// picks. (D minor pentatonic: D F G A C.)
+static const int PENT[5] = { 50, 53, 55, 57, 60 };      // D4 F4 G4 A4 C5
+// the high droplet palette (D5 F5 G5 A5 C6 D6) — sparse sunset glints.
+static const int DROPS[6] = { 74, 77, 79, 81, 84, 86 };
+
+// section map. SECBARS drives every loop bound below, so retuning the form
+// (or the whole length) is a one-line edit — at 90 BPM a bar is 2.667s, so this
+// 44-bar form lands at ~117s + reverb tail (~123s mp3). Keep wave/outro counts
+// multiples of 4 so the 4-bar phrases (pad loop, lead) line up.
+static const char *ORDER[8] = { "intro", "bloom", "verseA", "hushA", "verseB", "hushB", "chorus", "outro" };
+static const int SECBARS[8] = { 4, 4, 8, 4, 8, 4, 8, 4 };
+static int START[8];
+static int sec_index(const char *k) { for (int i = 0; i < 8; i++) if (!strcmp(ORDER[i], k)) return i; return 0; }
+
+// a music-box stab — root + 5th + octave, warm (mid ratio) and short.
+static void stab(double t, int root, double g, int triad) {
+    bell(busL, busR, root, t, BEAT * 1.5, g, -0.15, 6.0, 4.0);
+    bell(busL, busR, root + 7, t + 0.014, BEAT * 1.5, g * 0.7, 0.18, 6.0, 4.0);
+    if (triad) bell(busL, busR, root + 12, t + 0.028, BEAT * 1.3, g * 0.5, 0.0, 5.0, 5.0);
+    bell(revL, revR, root + 7, t, BEAT * 1.5, g * 0.45, 0, 6.0, 4.0);
+}
+
+// ── ornaments ───────────────────────────────────────────────────────────────
+// frill — a quick grace-run of n bells stepping by `step` semitones across
+// `span` seconds (a sparkly flourish; for dusktrax, mostly DESCENDING runs).
+static void frill(double t, double base, int n, int step, double span, double g) {
+    for (int i = 0; i < n; i++) bell(busL, busR, base + i * step, t + span * i / n, span * 1.4, g * (1.0 - 0.30 * i / n), rnd2() * 0.5, 4.5, 11.0);
+}
+// turn — three quick bells over one beat (middle dipped a step), a sighing
+// lift-and-fall on phrase starts (minor-mode wistfulness).
+static void turn(double t, double note, double g) {
+    for (int i = 0; i < 3; i++) bell(busL, busR, note + (i == 1 ? -2 : 0), t + BEAT * i / 3.0, BEAT / 3.0 * 1.3, g * (i == 1 ? 1.0 : 1.05), (i - 1) * 0.25, 5.0, 10.0);
+}
+
+int main(int argc, char **argv) {
+    const char *out_path = "out/dusktrax-raw.wav";
+    for (int i = 1; i < argc; i++) { if (!strcmp(argv[i], "--out") && i + 1 < argc) out_path = argv[++i]; else if (!strcmp(argv[i], "--bpm") && i + 1 < argc) BPMV = atof(argv[++i]); else if (!strcmp(argv[i], "--swing") && i + 1 < argc) SWING = atof(argv[++i]); }
+    BEAT = 60.0 / BPMV; BAR = BEAT * 4; SX = BEAT / 4;
+    { int c = 0; for (int i = 0; i < 8; i++) { START[i] = c; c += SECBARS[i]; } }
+    int TB = 0; for (int i = 0; i < 8; i++) TB += SECBARS[i];
+    double totalSec = TB * BAR + 6.0; N = (long)(totalSec * SR);
+    busL = calloc(N, 4); busR = calloc(N, 4); revL = calloc(N, 4); revR = calloc(N, 4);
+    fprintf(stderr, "# dusktrax.c · %g BPM · %d bars · %.1fs · D minor sine bells (sunset)\n", BPMV, TB, totalSec);
+
+    // THE MOTIF — a wistful music-box lead that keeps falling. Across the 4-bar
+    // phrase it descends D6→A5→F5→E5 then sighs down to D5, a tail-rise back to
+    // A5 so it can fall again next time. {phrase-bar, beat, note}.
+    double LEAD[9][3] = {
+        {0,0,86},{0,2,81},          // D6 → A5     (the fall begins)
+        {1,0,77},{1,2,76},          // F5 → E5     (sighing down a step)
+        {2,0,74},{2,1.5,77},        // D5 → F5     (gentle lift)
+        {3,0,76},{3,1.5,74},        // E5 → D5     (resolve down to tonic)
+        {3,3,81},                   // A5          (tail rise — re-arm the fall)
+    };
+
+    // ── INTRO (staggered: warm pad → a lone falling bell line → sub → spark) ──
+    { int idx = sec_index("intro"); int c = START[idx], nb = SECBARS[idx], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, i_PAD, 4, BAR * h - 0.05, 0.11);
+        pad_chord(t0 + BAR * h, VI_PAD, 4, BAR * (nb - h) - 0.05, 0.12);
+        int mel[4] = { 86, 81, 77, 74 };                       // D6 A5 F5 D5 — the falling motif previewed, bare
+        for (int b = 0; b < 4 && 1 + b < nb; b++) bell(busL, busR, mel[b], t0 + (1 + b) * BAR, BAR * 0.95, 0.14, rnd2() * 0.3, 5.0, 2.6);
+        for (int b = h; b < nb; b++) softsine(busL, busR, 38, t0 + b * BAR, BAR * 0.95, 0.13, 0); // sub through the back half
+        for (int b = nb - 2; b < nb; b++) if (b >= 0) droplet(DROPS[(int)(rnd() * 6)], t0 + b * BAR + 2.5 * BEAT, 0.05, rnd2() * 0.6); // first sunset glint
+    }
+
+    // ── BLOOM — a descending bell arpeggio + pad settle into the first verse ──
+    { int idx = sec_index("bloom"); int c = START[idx], nb = SECBARS[idx], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, III_PAD, 4, BAR * h - 0.05, 0.13);
+        pad_chord(t0 + BAR * h, VII_PAD, 4, BAR * (nb - h) - 0.05, 0.14);
+        int arp[8] = { 81, 77, 74, 69, 65, 62, 57, 53 };       // a long, slow descent (A5 down to F3)
+        for (int s = 0; s < 16; s++) { double tt = t0 + BAR * h + swing_beats(s * 0.25); bell(busL, busR, arp[s % 8] - (s / 8) * 12, tt, SX * 2.6, 0.06 + 0.06 * (16 - s) / 16.0, rnd2() * 0.4, 4.5, 8.0); }
+        frill(t0 + BAR * nb - BEAT * 2, 86, 8, -2, BEAT * 1.9, 0.07);   // descending flourish into verse A
+    }
+
+    // ── helper for the verses + chorus (lyrical, song-like; not a hard drop) ──
+    const char *waves[3] = { "verseA", "verseB", "chorus" };
+    for (int d = 0; d < 3; d++) {
+        int wi = sec_index(waves[d]); int c = START[wi], nbw = SECBARS[wi]; int big = d == 2; // chorus = big
+        for (int b = 0; b < nbw; b++) {
+            double t0 = (c + b) * BAR; int root = D_ROOTS[b % 4]; int phrase = b % 4 == 0;
+            // a soft pulsing bass — beats 1 & 3 anchor, the "&"s lighter & wide.
+            for (int e = 0; e < 8; e++) { double tt = t0 + swing_beats(e * 0.5); int on = (e % 2 == 0); if (on || rnd() < 0.45) bell(busL, busR, root - 12, tt, BEAT * 0.5, on ? 0.10 : 0.05, on ? -0.08 : 0.24, 2.0, on ? 10.0 : 13.0); }
+            // sustained sub body (one per bar, under the pulse)
+            softsine(busL, busR, root - 12, t0, BAR * 0.95, 0.11, 0);
+            // the music-box stab on beat 3 (root triad on the chorus)
+            stab(t0 + BEAT * 2, root, big ? 0.17 : 0.13, big);
+            // pad sustain every 4 bars (chord follows the descending loop)
+            if (phrase) pad_chord(t0, PADS[(b / 4) % 4], 4, BAR * 4 - 0.05, 0.075);
+            // a sighing turn on each phrase-start downbeat
+            if (phrase) turn(t0, root + 12, big ? 0.075 : 0.055);
+            // THE LEAD (4-bar phrase) — the falling music-box motif, warm, with
+            // descending frills on the high notes.
+            for (int z = 0; z < 9; z++) if ((int)LEAD[z][0] == b % 4) {
+                double note = LEAD[z][2], tt = t0 + swing_beats(LEAD[z][1]);
+                bell(busL, busR, note, tt, BEAT * 0.9, big ? 0.13 : 0.10, rnd2() * 0.35, 5.0, 5.5);
+                bell(revL, revR, note, tt, BEAT * 0.9, 0.055, 0, 5.0, 5.5);
+                if (note >= 81) frill(tt + 0.05, note, big ? 4 : 3, -2, BEAT * 0.5, big ? 0.05 : 0.038); // falling sparkle
+            }
+            // pentatonic plink — swung off-beat sparkle (mid register, mellow)
+            if (b % 2 == 0) bell(busL, busR, PENT[b % 5] + (big ? 12 : 0), t0 + swing_beats(2.5), BEAT * 0.8, 0.05, rnd2() * 0.5, 4.5, 7.0);
+            // sunset glints — sprinkled, denser in the chorus
+            int ndrops = big ? 3 : 1;
+            for (int k = 0; k < ndrops; k++) if (rnd() < 0.5) droplet(DROPS[(int)(rnd() * 6)], t0 + swing_beats((int)(rnd() * 8) * 0.5), 0.042, rnd2() * 0.7);
+            // a long descending frill run at chorus phrase-ends (the big "fall")
+            if (big && b % 4 == 3) frill(t0 + BEAT * 2.5, 88, 7, -2, BEAT * 1.3, 0.055);
+        }
+        // a soft choir-ish sine bed under the chorus
+        if (big) for (int b = 0; b < nbw; b += 2) { double t0 = (c + b) * BAR; int ns[3] = { i_PAD[1], i_PAD[2], i_PAD[3] }; for (int z = 0; z < 3; z++) softsine(revL, revR, ns[z] + 12, t0, BAR * 2, 0.045, (z - 1) * 0.4); }
+    }
+
+    // ── HUSHES — spacious: pad + half-time sub + sparse falling bells + glints ─
+    const char *hush[2] = { "hushA", "hushB" };
+    for (int z2 = 0; z2 < 2; z2++) {
+        int hi = sec_index(hush[z2]); int c = START[hi], nb = SECBARS[hi], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, III_PAD, 4, BAR * h - 0.05, 0.12);
+        pad_chord(t0 + BAR * h, VII_PAD, 4, BAR * (nb - h) - 0.05, 0.12);
+        for (int b = 0; b < nb; b++) { softsine(busL, busR, b < h ? 29 : 36, t0 + b * BAR, BAR * 0.85, 0.11, 0); if (b % 2 == 0) bell(busL, busR, i_PAD[3 - (b / 2) % 3], t0 + b * BAR, BAR * 0.95, 0.11, rnd2() * 0.4, 4.5, 2.4); if (rnd() < 0.55) droplet(DROPS[(int)(rnd() * 6)], t0 + b * BAR + 2.5 * BEAT, 0.038, rnd2() * 0.7); }
+        // a falling pentatonic run into the next section (echoes the motif)
+        if (z2 == 1) for (int s = 0; s < 16; s++) bell(busL, busR, 86 - PENT[s % 5] + 50, t0 + BAR * (nb - 2) + s * SX, SX * 3, 0.04 + 0.04 * (16 - s) / 16.0, rnd2() * 0.5, 4.5, 5.0);
+        else for (int s = 0; s < 12; s++) bell(busL, busR, 81 - (s % 6) * 2, t0 + BAR * (nb - 2) + s * SX, SX * 3, 0.035 + 0.04 * (12 - s) / 12.0, rnd2() * 0.5, 4.5, 5.0);
+    }
+
+    // ── OUTRO — the motif decays + pad wash + a final low bell at dusk ──
+    { int idx = sec_index("outro"); int c = START[idx], nb = SECBARS[idx], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, VI_PAD, 4, BAR * h - 0.05, 0.11);
+        pad_chord(t0 + BAR * h, i_PAD, 4, BAR * (nb - h) - 0.05, 0.10);
+        int fall[4] = { 86, 81, 77, 74 };                      // the falling motif, one last time, fading
+        for (int b = 0; b < nb; b++) { double e = fmax(0.12, 1.0 - (double)b / nb); int root = b < h ? 46 : 50; softsine(busL, busR, root - 12, t0 + b * BAR, BAR * 0.9, 0.10 * e, 0); if (b < 4) bell(busL, busR, fall[b], t0 + b * BAR + BEAT, BAR * 0.9, 0.12 * e, rnd2() * 0.3, 5.0, 2.4); if (rnd() < 0.45) droplet(DROPS[(int)(rnd() * 6)], t0 + b * BAR + 1.5 * BEAT, 0.032 * e, rnd2() * 0.7); }
+        // a final low D — the sun goes down.
+        bell(busL, busR, 38, t0 + BAR * (nb - 2), 4.8, 0.18, 0, 2.0, 1.1);
+        bell(busL, busR, 74, t0 + BAR * (nb - 2), 4.8, 0.10, 0.2, 5.0, 1.4);
+        bell(revL, revR, 62, t0 + BAR * (nb - 2), 4.8, 0.10, 0, 4.5, 1.3);
+    }
+
+    // ── REVERB (Schroeder) — wide, warm, long for the golden-hour bell space ──
+    {
+        double decay = 0.85, wet = 0.58, damp = 0.42;  // a touch wetter + warmer (more damping) than dewtrax
+        int CD[6]; double cds[6] = { 0.0297, 0.0371, 0.0411, 0.0437, 0.0497, 0.0581 };
+        for (int k = 0; k < 6; k++) CD[k] = (int)(cds[k] * SR);
+        int AD[2] = { (int)(0.005 * SR), (int)(0.0017 * SR) }; double apFb = 0.5;
+        float *cbL[6], *cbR[6]; int ciL[6] = {0}, ciR[6] = {0}; double cLPL[6] = {0}, cLPR[6] = {0};
+        for (int k = 0; k < 6; k++) { cbL[k] = calloc(CD[k], 4); cbR[k] = calloc(CD[k], 4); }
+        float *abL[2], *abR[2]; int aiL[2] = {0}, aiR[2] = {0};
+        for (int k = 0; k < 2; k++) { abL[k] = calloc(AD[k], 4); abR[k] = calloc(AD[k], 4); }
+        for (long i = 0; i < N; i++) {
+            double inL = revL[i], inR = revR[i], cL = 0, cR = 0;
+            for (int k = 0; k < 6; k++) {
+                double dL = cbL[k][ciL[k]], dR = cbR[k][ciR[k]]; cL += dL; cR += dR;
+                cLPL[k] = dL * (1 - damp) + cLPL[k] * damp; cLPR[k] = dR * (1 - damp) + cLPR[k] * damp;
+                cbL[k][ciL[k]] = (float)(inL + cLPL[k] * decay); cbR[k][ciR[k]] = (float)(inR + cLPR[k] * decay);
+                ciL[k] = (ciL[k] + 1) % CD[k]; ciR[k] = (ciR[k] + 1) % CD[k];
+            }
+            cL /= 6; cR /= 6;
+            for (int k = 0; k < 2; k++) {
+                double dL = abL[k][aiL[k]], dR = abR[k][aiR[k]];
+                double oL = -apFb * cL + dL, oR = -apFb * cR + dR;
+                abL[k][aiL[k]] = (float)(cL + apFb * oL); abR[k][aiR[k]] = (float)(cR + apFb * oR);
+                aiL[k] = (aiL[k] + 1) % AD[k]; aiR[k] = (aiR[k] + 1) % AD[k];
+                cL = oL; cR = oR;
+            }
+            busL[i] += (float)(cL * wet); busR[i] += (float)(cR * wet);
+        }
+        for (int k = 0; k < 6; k++) { free(cbL[k]); free(cbR[k]); }
+        for (int k = 0; k < 2; k++) { free(abL[k]); free(abR[k]); }
+    }
+
+    // ── normalize + gentle in/out fades ──
+    double peak = 0; for (long i = 0; i < N; i++) { double a = fmax(fabs(busL[i]), fabs(busR[i])); if (a > peak) peak = a; }
+    if (peak > 0) { double g = 0.85 / peak; for (long i = 0; i < N; i++) { busL[i] *= (float)g; busR[i] *= (float)g; } }
+    long fin = (long)(2.5 * SR), fout = (long)(4.5 * SR);
+    for (long i = 0; i < fin && i < N; i++) { double g = 0.5 - 0.5 * cos(M_PI * (double)i / fin); busL[i] *= (float)g; busR[i] *= (float)g; }
+    for (long i = 0; i < fout && i < N; i++) { double g = 0.5 - 0.5 * cos(M_PI * (double)i / fout); long idx = N - 1 - i; busL[idx] *= (float)g; busR[idx] *= (float)g; }
+
+    if (!write_wav_f32_stereo(out_path, busL, busR, N)) { fprintf(stderr, "✗ write failed\n"); return 1; }
+    fprintf(stderr, "✓ %s · %.1fs\n", out_path, (double)N / SR);
+    return 0;
+}
diff --git a/pop/maytrax/c/embertrax b/pop/maytrax/c/embertrax
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diff --git a/pop/maytrax/c/embertrax.c b/pop/maytrax/c/embertrax.c
new file mode 100644
index 000000000..b7aa03c5d
--- /dev/null
+++ b/pop/maytrax/c/embertrax.c
@@ -0,0 +1,284 @@
+// embertrax.c — a sine-bell sibling of dewtrax. Same instrument (FM sine bells
+// + soft sine drones + Schroeder reverb), new song: G minor, mid-tempo
+// (108 BPM), a warm amber glow. Where dewtrax is bright/nocturnal, embertrax
+// sits lower and rounder: warm low-mid bells over a steady gentle pulse,
+// patiently swelling from a single ember to a full glow and easing back down.
+// Bell ratios stay in the rounded 2.5–4.0 zone (no glassy plink), decays run
+// long, the reverb is warm and damped. No samples, no drums, no vocals — pure
+// sine. render-c.mjs --engine embertrax masters it on the sine-family chain.
+//
+// Build:  cc -O3 -std=c11 -Wall -Wextra -Wno-unused-parameter -o embertrax embertrax.c -lm
+// Run:    ./embertrax --out out/embertrax-raw.wav
+
+#define _POSIX_C_SOURCE 200809L
+#include <stdio.h>
+#include <stdlib.h>
+#include <stdint.h>
+#include <string.h>
+#include <math.h>
+
+#ifndef M_PI
+#define M_PI 3.14159265358979323846
+#endif
+#define TAU (2.0 * M_PI)
+
+static const int SR = 48000;
+static double BPMV = 108, BEAT, BAR, SX;
+
+static uint32_t rng_s = 0x656d6272; // "embr"
+static inline double rnd(void) { rng_s ^= rng_s << 13; rng_s ^= rng_s >> 17; rng_s ^= rng_s << 5; return (double)rng_s / 4294967296.0; }
+static inline double rnd2(void) { return rnd() * 2.0 - 1.0; }
+static inline double midi_hz(double m) { return 440.0 * pow(2.0, (m - 69.0) / 12.0); }
+
+// ── swing / sway ────────────────────────────────────────────────────────────
+// A barely-there sway (0.53) — embertrax breathes, it almost doesn't swing.
+// On-beats hold; the "&"s drag a hair late; 16ths interpolate inside the 8th.
+static double SWING = 0.53;
+static double swing_beats(double beats) {
+    double e8 = beats * 2.0;                 // position in 8ths
+    long idx = (long)floor(e8 + 1e-9);
+    double frac = e8 - idx;
+    double pos = (idx / 2) * BEAT + ((idx & 1) ? SWING * BEAT : 0.0);
+    return pos + frac * (BEAT / 2.0);        // interpolate 16ths inside the 8th
+}
+
+static long N;
+static float *busL, *busR, *revL, *revR;
+static inline void adds(float *L, float *R, long i, double l, double r) { if (i >= 0 && i < N) { L[i] += (float)l; R[i] += (float)r; } }
+
+static int write_wav_f32_stereo(const char *path, const float *L, const float *R, long n) {
+    FILE *f = fopen(path, "wb"); if (!f) return 0;
+    uint32_t dsz = (uint32_t)(n * 8), riff = 36 + dsz, sr = SR, br = SR * 8, fsz = 16;
+    uint16_t fmt = 3, ch = 2, ba = 8, bits = 32;
+    fwrite("RIFF", 1, 4, f); fwrite(&riff, 4, 1, f); fwrite("WAVE", 1, 4, f);
+    fwrite("fmt ", 1, 4, f); fwrite(&fsz, 4, 1, f);
+    fwrite(&fmt, 2, 1, f); fwrite(&ch, 2, 1, f); fwrite(&sr, 4, 1, f);
+    fwrite(&br, 4, 1, f); fwrite(&ba, 2, 1, f); fwrite(&bits, 2, 1, f);
+    fwrite("data", 1, 4, f); fwrite(&dsz, 4, 1, f);
+    for (long i = 0; i < n; i++) { fwrite(&L[i], 4, 1, f); fwrite(&R[i], 4, 1, f); }
+    fclose(f); return 1;
+}
+
+// ── voices ────────────────────────────────────────────────────────────────
+// FM sine bell — carrier + a decaying modulator gives the warm partial body;
+// exp amp decay. `ratio` shapes the timbre. embertrax lives in the rounded
+// 2.5–4.0 zone: 2.5 = soft body, 3.0 = warm bell, 4.0 = the brightest it gets.
+// A softer attack transient (3.0, slower decay) keeps onsets rounded, not glassy.
+static void bell(float *L, float *R, double note, double t, double dur, double g, double pan, double ratio, double dec) {
+    double fc = midi_hz(note), fm = fc * ratio;
+    long n = (long)(dur * SR), s0 = (long)(t * SR);
+    double phc = 0, phm = 0, lg = 1 - pan * 0.5, rg = 1 + pan * 0.5;
+    long att = (long)(0.004 * SR);               // softer, rounder onset
+    for (long i = 0; i < n; i++) {
+        double tt = (double)i / SR;
+        double env = exp(-tt * dec); if (i < att) env *= (double)i / att;
+        double mi = 3.0 * exp(-tt * 7.0);        // warmer, gentler attack transient
+        phm += TAU * fm / SR;
+        phc += TAU * fc / SR + sin(phm) * mi / SR;
+        double v = sin(phc) * env * g;
+        adds(L, R, s0 + i, v * lg, v * rg);
+    }
+}
+
+// ember — a small, warm, mid-register bell that glows rather than sparkles;
+// rounded ratio (3.0), medium decay. fed into the dry bus + softly the reverb.
+static void ember(double note, double t, double g, double pan) {
+    bell(busL, busR, note, t, 1.1, g, pan, 3.0, 6.0);
+    bell(revL, revR, note, t, 1.1, g * 0.55, 0, 3.0, 6.0);
+}
+
+// soft sine drone — pad / sub bed with a slow raised-cosine attack/release.
+// embertrax leans on the lower harmonics for a fuller, warmer bed.
+static void softsine(float *L, float *R, double note, double t, double dur, double g, double pan) {
+    double f = midi_hz(note); long n = (long)(dur * SR), s0 = (long)(t * SR);
+    long att = (long)(0.40 * SR), rel = (long)(0.55 * SR); double ph = 0, lg = 1 - pan * 0.5, rg = 1 + pan * 0.5;
+    for (long i = 0; i < n; i++) {
+        ph += TAU * f / SR;
+        double env = 1; if (i < att) env = (double)i / att; else if (i > n - rel) env = fmax(0, (double)(n - i) / rel);
+        double v = (sin(ph) + 0.22 * sin(ph * 2) + 0.09 * sin(ph * 3)) * env * g;
+        adds(L, R, s0 + i, v * lg, v * rg);
+    }
+}
+
+// a 4-voice sine pad chord (slightly panned for width), with a soft reverb send.
+static void pad_chord(double t, const int *midis, int nm, double dur, double g) {
+    for (int k = 0; k < nm; k++) { double pan = (k / fmax(1, nm - 1) - 0.5) * 0.55; softsine(busL, busR, midis[k], t, dur, g, pan); softsine(revL, revR, midis[k], t, dur, g * 0.45, 0); }
+}
+
+// ── harmony — G minor, a i–VI–III–v loop (warm, glowing) ────────────────────
+// per-bar bass roots that the loop walks: Gm, Eb, Bb, Dm.
+static const int G_ROOTS[4] = { 55, 51, 58, 50 };       // G3, Eb3, Bb3, D3
+// four 4-note pad voicings, one per chord in the loop (low-mid, close + warm).
+static const int I_PAD[4]   = { 31, 38, 43, 46 };       // Gm     (G D Bb D)
+static const int VI_PAD[4]  = { 27, 34, 39, 43 };       // Eb maj (Eb Bb G Bb)
+static const int III_PAD[4] = { 34, 41, 46, 50 };       // Bb maj (Bb F D F)
+static const int V_PAD[4]   = { 26, 33, 38, 41 };       // Dm     (D A F A)
+static const int *PADS[4] = { I_PAD, VI_PAD, III_PAD, V_PAD };
+
+// G minor pentatonic (G Bb C D F), low-mid octave — for arps + ember picks.
+static const int PENT[5] = { 43, 46, 48, 50, 53 };
+// the warm ember palette (G4 Bb4 C5 D5 F5 G5) — lower than dewtrax's droplets.
+static const int EMBERS[6] = { 67, 70, 72, 74, 77, 79 };
+
+// section map. SECBARS drives every loop bound below, so retuning the form
+// (or the whole length) is a one-line edit — at 108 BPM a bar is ~2.22s, so
+// this 52-bar form lands at ~115s. Keep glow/outro counts multiples of 4 so
+// the 4-bar phrases (pad loop, lead) line up. The form is a patient swell:
+// ember → kindle → three glows of growing warmth → settles → outro.
+static const char *ORDER[8] = { "ember", "kindle", "glowA", "settleA", "glowB", "settleB", "glowC", "outro" };
+static const int SECBARS[8] = { 4, 4, 8, 4, 8, 4, 8, 12 };
+static int START[8];
+static int sec_index(const char *k) { for (int i = 0; i < 8; i++) if (!strcmp(ORDER[i], k)) return i; return 0; }
+
+// a warm chord stab — root + 5th + octave, rounded (low ratio) and singing.
+static void stab(double t, int root, double g, int triad) {
+    bell(busL, busR, root, t, BEAT * 2.0, g, -0.12, 3.0, 3.2);
+    bell(busL, busR, root + 7, t + 0.018, BEAT * 2.0, g * 0.7, 0.15, 3.0, 3.2);
+    if (triad) bell(busL, busR, root + 12, t + 0.036, BEAT * 1.8, g * 0.5, 0.0, 3.5, 3.6);
+    bell(revL, revR, root + 7, t, BEAT * 2.0, g * 0.45, 0, 3.0, 3.2);
+}
+
+// ── ornaments ───────────────────────────────────────────────────────────────
+// warmrun — a slow warm-bell run of n bells stepping by `step` semitones across
+// `span` seconds (a glowing flourish for high points / pickups). Lower & rounder
+// than dewtrax's frill.
+static void warmrun(double t, double base, int n, int step, double span, double g) {
+    for (int i = 0; i < n; i++) bell(busL, busR, base + i * step, t + span * i / n, span * 1.6, g * (1.0 - 0.30 * i / n), rnd2() * 0.45, 3.0, 7.0);
+}
+// triplet — three warm bells over one beat (middle lifted a minor 3rd), a
+// gentle lift on phrase starts.
+static void triplet(double t, double note, double g) {
+    for (int i = 0; i < 3; i++) bell(busL, busR, note + (i == 1 ? 3 : 0), t + BEAT * i / 3.0, BEAT / 3.0 * 1.5, g * (i == 1 ? 1.1 : 1.0), (i - 1) * 0.22, 3.0, 6.5);
+}
+
+int main(int argc, char **argv) {
+    const char *out_path = "out/embertrax-raw.wav";
+    for (int i = 1; i < argc; i++) { if (!strcmp(argv[i], "--out") && i + 1 < argc) out_path = argv[++i]; else if (!strcmp(argv[i], "--bpm") && i + 1 < argc) BPMV = atof(argv[++i]); else if (!strcmp(argv[i], "--swing") && i + 1 < argc) SWING = atof(argv[++i]); }
+    BEAT = 60.0 / BPMV; BAR = BEAT * 4; SX = BEAT / 4;
+    { int c = 0; for (int i = 0; i < 8; i++) { START[i] = c; c += SECBARS[i]; } }
+    int TB = 0; for (int i = 0; i < 8; i++) TB += SECBARS[i];
+    double totalSec = TB * BAR + 7.0; N = (long)(totalSec * SR);
+    busL = calloc(N, 4); busR = calloc(N, 4); revL = calloc(N, 4); revR = calloc(N, 4);
+    fprintf(stderr, "# embertrax.c · %g BPM · %d bars · %.1fs · G minor warm sine bells\n", BPMV, TB, totalSec);
+
+    // the warm lead, as {phrase-bar, beat, note} — a rising-then-settling motif
+    // in G minor across the 4-bar phrase, sitting in the low-mid (G4 region).
+    double LEAD[8][3] = { {0,0,67},{0,2.5,70},{1,0,72},{1,2,70},{2,0,74},{2,2.5,72},{3,0,70},{3,2,67} };
+
+    // ── EMBER (a single warm glow waking up: lone pad → one bell → sub) ──
+    { int idx = sec_index("ember"); int c = START[idx], nb = SECBARS[idx], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, I_PAD, 4, BAR * h - 0.05, 0.09);
+        pad_chord(t0 + BAR * h, VI_PAD, 4, BAR * (nb - h) - 0.05, 0.10);
+        int mel[4] = { 67, 70, 72, 70 };                       // a small rising glow, from bar 2
+        for (int b = 0; b < 4 && 2 + b < nb; b++) bell(busL, busR, mel[b], t0 + (2 + b) * BAR, BAR * 1.1, 0.12, rnd2() * 0.25, 3.0, 2.4);
+        for (int b = h; b < nb; b++) softsine(busL, busR, 31, t0 + b * BAR, BAR * 0.95, 0.11, 0); // sub through the back half
+        for (int b = nb - 2; b < nb; b++) if (b >= 0) ember(EMBERS[(int)(rnd() * 3)], t0 + b * BAR + 2.5 * BEAT, 0.05, rnd2() * 0.5); // first embers
+    }
+
+    // ── KINDLE — a rising warm arpeggio + pad climb into the first glow ──
+    { int idx = sec_index("kindle"); int c = START[idx], nb = SECBARS[idx], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, III_PAD, 4, BAR * h - 0.05, 0.12);
+        pad_chord(t0 + BAR * h, V_PAD, 4, BAR * (nb - h) - 0.05, 0.13);
+        int arp[8] = { 43, 46, 48, 50, 53, 55, 58, 62 };
+        for (int s = 0; s < 16; s++) { double tt = t0 + BAR * h + swing_beats(s * 0.25); bell(busL, busR, arp[s % 8] + (s / 8) * 12, tt, SX * 3.0, 0.05 + 0.06 * s / 16.0, rnd2() * 0.35, 3.0, 6.0); }
+        warmrun(t0 + BAR * nb - BEAT * 2, 62, 6, 2, BEAT * 2.0, 0.06);   // glowing ascent into glow A
+    }
+
+    // ── helper for the three glows (a swelling warmth, not a drop) ──
+    const char *glows[3] = { "glowA", "glowB", "glowC" };
+    for (int d = 0; d < 3; d++) {
+        int wi = sec_index(glows[d]); int c = START[wi], nbw = SECBARS[wi]; int big = d == 2;
+        for (int b = 0; b < nbw; b++) {
+            double t0 = (c + b) * BAR; int root = G_ROOTS[b % 4]; int phrase = b % 4 == 0;
+            // a steady gentle pulse — warm low bells on every beat, "&"s lighter.
+            for (int e = 0; e < 8; e++) { double tt = t0 + swing_beats(e * 0.5); int on = (e % 2 == 0); if (on || rnd() < 0.45) bell(busL, busR, root - 12, tt, BEAT * 0.7, on ? 0.10 : 0.05, on ? -0.06 : 0.20, 2.5, on ? 8.0 : 10.0); }
+            // sustained sub body (one per bar, under the pulse)
+            softsine(busL, busR, root - 12, t0, BAR * 0.95, 0.11, 0);
+            // the warm chord stab on beat 3 (rounded, singing)
+            stab(t0 + BEAT * 2, root, big ? 0.16 : 0.12, big || d == 1);
+            // pad sustain every 4 bars (chord follows the loop)
+            if (phrase) pad_chord(t0, PADS[(b / 4) % 4], 4, BAR * 4 - 0.05, 0.08 + 0.01 * d);
+            // a gentle triplet lift on each phrase-start downbeat
+            if (phrase) triplet(t0, root, big ? 0.07 : 0.05);
+            // the warm lead (4-bar phrase) — barely swung, rounded, run on highs
+            for (int z = 0; z < 8; z++) if ((int)LEAD[z][0] == b % 4) {
+                double note = LEAD[z][2], tt = t0 + swing_beats(LEAD[z][1]);
+                bell(busL, busR, note, tt, BEAT * 1.2, big ? 0.11 : 0.08, rnd2() * 0.35, 3.0, 4.0);
+                bell(revL, revR, note, tt, BEAT * 1.2, 0.05, 0, 3.0, 4.0);
+                if (note >= 74) warmrun(tt + 0.05, note, big ? 4 : 3, 2, BEAT * 0.7, big ? 0.05 : 0.035);
+            }
+            // pentatonic glow — barely-swung off-beat warmth
+            if (b % 2 == 0) bell(busL, busR, PENT[b % 5] + 12 + (big ? 12 : 0), t0 + swing_beats(2.5), BEAT * 1.0, 0.05, rnd2() * 0.45, 3.0, 6.0);
+            // embers — sprinkled, denser & warmer in the big glow
+            int nem = big ? 3 : (d == 1 ? 2 : 1);
+            for (int k = 0; k < nem; k++) if (rnd() < 0.55) ember(EMBERS[(int)(rnd() * 6)], t0 + swing_beats((int)(rnd() * 8) * 0.5), 0.04, rnd2() * 0.6);
+            // descending warm run at phrase ends of the big glow (the full glow's peak)
+            if (big && b % 4 == 3) warmrun(t0 + BEAT * 3, 79, 5, -2, BEAT * 1.1, 0.05);
+        }
+        // a soft choir-ish sine bed through the biggest glow — full warmth
+        if (big) for (int b = 0; b < nbw; b += 2) { double t0 = (c + b) * BAR; int ns[3] = { I_PAD[1], I_PAD[2], I_PAD[3] }; for (int z = 0; z < 3; z++) softsine(revL, revR, ns[z] + 12, t0, BAR * 2, 0.045, (z - 1) * 0.38); }
+    }
+
+    // ── SETTLES — spacious: pad + half-time sub + sparse warm bells + lone embers ──
+    const char *settle[2] = { "settleA", "settleB" };
+    for (int z2 = 0; z2 < 2; z2++) {
+        int hi = sec_index(settle[z2]); int c = START[hi], nb = SECBARS[hi], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, VI_PAD, 4, BAR * h - 0.05, 0.11);
+        pad_chord(t0 + BAR * h, III_PAD, 4, BAR * (nb - h) - 0.05, 0.11);
+        for (int b = 0; b < nb; b++) { softsine(busL, busR, b < h ? 27 : 34, t0 + b * BAR, BAR * 0.85, 0.10, 0); if (b % 2 == 0) bell(busL, busR, I_PAD[1 + (b / 2) % 3], t0 + b * BAR, BAR * 1.1, 0.10, rnd2() * 0.35, 3.0, 2.2); if (rnd() < 0.6) ember(EMBERS[(int)(rnd() * 6)], t0 + b * BAR + 2.5 * BEAT, 0.035, rnd2() * 0.6); }
+        if (z2 == 1) for (int s = 0; s < 16; s++) bell(busL, busR, 55 + PENT[s % 5] - 43, t0 + BAR * (nb - 2) + s * SX, SX * 3.5, 0.035 + 0.045 * s / 16.0, rnd2() * 0.45, 3.0, 4.5); // rising warm run into glow C
+    }
+
+    // ── OUTRO — the glow cooling: decaying warm bells + pad wash + a final low bell ──
+    { int idx = sec_index("outro"); int c = START[idx], nb = SECBARS[idx], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, I_PAD, 4, BAR * h - 0.05, 0.10);
+        pad_chord(t0 + BAR * h, VI_PAD, 4, BAR * (nb - h) - 0.05, 0.09);
+        for (int b = 0; b < nb; b++) { double e = fmax(0.08, 1.0 - (double)b / nb); int root = b < h ? 55 : 51; softsine(busL, busR, root - 12, t0 + b * BAR, BAR * 0.9, 0.10 * e, 0); if (b % 2 == 0) stab(t0 + b * BAR + BEAT * 2, root, 0.10 * e, 0); if (rnd() < 0.5) ember(EMBERS[(int)(rnd() * 6)], t0 + b * BAR + 1.5 * BEAT, 0.03 * e, rnd2() * 0.6); }
+        bell(busL, busR, 31, t0 + BAR * (nb - 3), 5.5, 0.17, 0, 2.5, 1.0);
+        bell(busL, busR, 67, t0 + BAR * (nb - 3), 5.5, 0.09, 0.18, 3.0, 1.2);
+        bell(revL, revR, 55, t0 + BAR * (nb - 3), 5.5, 0.10, 0, 3.0, 1.1);
+    }
+
+    // ── REVERB (Schroeder) — warm & damped for the amber bell space ──
+    {
+        double decay = 0.84, wet = 0.52, damp = 0.50;
+        int CD[6]; double cds[6] = { 0.0311, 0.0383, 0.0427, 0.0451, 0.0509, 0.0593 };
+        for (int k = 0; k < 6; k++) CD[k] = (int)(cds[k] * SR);
+        int AD[2] = { (int)(0.005 * SR), (int)(0.0017 * SR) }; double apFb = 0.5;
+        float *cbL[6], *cbR[6]; int ciL[6] = {0}, ciR[6] = {0}; double cLPL[6] = {0}, cLPR[6] = {0};
+        for (int k = 0; k < 6; k++) { cbL[k] = calloc(CD[k], 4); cbR[k] = calloc(CD[k], 4); }
+        float *abL[2], *abR[2]; int aiL[2] = {0}, aiR[2] = {0};
+        for (int k = 0; k < 2; k++) { abL[k] = calloc(AD[k], 4); abR[k] = calloc(AD[k], 4); }
+        for (long i = 0; i < N; i++) {
+            double inL = revL[i], inR = revR[i], cL = 0, cR = 0;
+            for (int k = 0; k < 6; k++) {
+                double dL = cbL[k][ciL[k]], dR = cbR[k][ciR[k]]; cL += dL; cR += dR;
+                cLPL[k] = dL * (1 - damp) + cLPL[k] * damp; cLPR[k] = dR * (1 - damp) + cLPR[k] * damp;
+                cbL[k][ciL[k]] = (float)(inL + cLPL[k] * decay); cbR[k][ciR[k]] = (float)(inR + cLPR[k] * decay);
+                ciL[k] = (ciL[k] + 1) % CD[k]; ciR[k] = (ciR[k] + 1) % CD[k];
+            }
+            cL /= 6; cR /= 6;
+            for (int k = 0; k < 2; k++) {
+                double dL = abL[k][aiL[k]], dR = abR[k][aiR[k]];
+                double oL = -apFb * cL + dL, oR = -apFb * cR + dR;
+                abL[k][aiL[k]] = (float)(cL + apFb * oL); abR[k][aiR[k]] = (float)(cR + apFb * oR);
+                aiL[k] = (aiL[k] + 1) % AD[k]; aiR[k] = (aiR[k] + 1) % AD[k];
+                cL = oL; cR = oR;
+            }
+            busL[i] += (float)(cL * wet); busR[i] += (float)(cR * wet);
+        }
+        for (int k = 0; k < 6; k++) { free(cbL[k]); free(cbR[k]); }
+        for (int k = 0; k < 2; k++) { free(abL[k]); free(abR[k]); }
+    }
+
+    // ── normalize + gentle in/out fades ──
+    double peak = 0; for (long i = 0; i < N; i++) { double a = fmax(fabs(busL[i]), fabs(busR[i])); if (a > peak) peak = a; }
+    if (peak > 0) { double g = 0.85 / peak; for (long i = 0; i < N; i++) { busL[i] *= (float)g; busR[i] *= (float)g; } }
+    long fin = (long)(3.0 * SR), fout = (long)(5.5 * SR);
+    for (long i = 0; i < fin && i < N; i++) { double g = 0.5 - 0.5 * cos(M_PI * (double)i / fin); busL[i] *= (float)g; busR[i] *= (float)g; }
+    for (long i = 0; i < fout && i < N; i++) { double g = 0.5 - 0.5 * cos(M_PI * (double)i / fout); long idx = N - 1 - i; busL[idx] *= (float)g; busR[idx] *= (float)g; }
+
+    if (!write_wav_f32_stereo(out_path, busL, busR, N)) { fprintf(stderr, "✗ write failed\n"); return 1; }
+    fprintf(stderr, "✓ %s · %.1fs\n", out_path, (double)N / SR);
+    return 0;
+}
diff --git a/pop/maytrax/c/frosttrax b/pop/maytrax/c/frosttrax
new file mode 100755
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diff --git a/pop/maytrax/c/frosttrax.c b/pop/maytrax/c/frosttrax.c
new file mode 100644
index 000000000..05e7a63a8
--- /dev/null
+++ b/pop/maytrax/c/frosttrax.c
@@ -0,0 +1,313 @@
+// frosttrax.c — a sine-bell sibling of dewtrax/sinetrax. Same instrument (FM
+// sine bells + soft sine drones + Schroeder reverb), new song: B minor, brisk
+// (132 BPM) but almost still. The character is COLD and BRITTLE — tiny
+// ultra-bright bells and icy droplets (ratios 6.0–8.0) scattered over near-
+// silence and a thin high drone, with long shimmering reverb tails. Very
+// sparse, lots of empty air, fast bright transients. No samples, no drums, no
+// vocals — pure sine. render-c.mjs --engine frosttrax masters it on the
+// sine-family chain.
+//
+// Build:  cc -O3 -std=c11 -Wall -Wextra -Wno-unused-parameter -o frosttrax frosttrax.c -lm
+// Run:    ./frosttrax --out out/frosttrax-raw.wav
+
+#define _POSIX_C_SOURCE 200809L
+#include <stdio.h>
+#include <stdlib.h>
+#include <stdint.h>
+#include <string.h>
+#include <math.h>
+
+#ifndef M_PI
+#define M_PI 3.14159265358979323846
+#endif
+#define TAU (2.0 * M_PI)
+
+static const int SR = 48000;
+static double BPMV = 132, BEAT, BAR, SX;
+
+static uint32_t rng_s = 0x66726f73; // "fros"
+static inline double rnd(void) { rng_s ^= rng_s << 13; rng_s ^= rng_s >> 17; rng_s ^= rng_s << 5; return (double)rng_s / 4294967296.0; }
+static inline double rnd2(void) { return rnd() * 2.0 - 1.0; }
+static inline double midi_hz(double m) { return 440.0 * pow(2.0, (m - 69.0) / 12.0); }
+
+// ── swing / sway ────────────────────────────────────────────────────────────
+// Almost straight (0.50) — frost doesn't sway, it hangs. A whisper of swing
+// (0.52) keeps the scattered droplets from sounding mechanical, but the feel
+// is icy-still. On-beats hold, the "&"s drag a hair late; 16ths interpolate.
+static double SWING = 0.52;
+static double swing_beats(double beats) {
+    double e8 = beats * 2.0;                 // position in 8ths
+    long idx = (long)floor(e8 + 1e-9);
+    double frac = e8 - idx;
+    double pos = (idx / 2) * BEAT + ((idx & 1) ? SWING * BEAT : 0.0);
+    return pos + frac * (BEAT / 2.0);        // interpolate 16ths inside the 8th
+}
+
+static long N;
+static float *busL, *busR, *revL, *revR;
+static inline void adds(float *L, float *R, long i, double l, double r) { if (i >= 0 && i < N) { L[i] += (float)l; R[i] += (float)r; } }
+
+static int write_wav_f32_stereo(const char *path, const float *L, const float *R, long n) {
+    FILE *f = fopen(path, "wb"); if (!f) return 0;
+    uint32_t dsz = (uint32_t)(n * 8), riff = 36 + dsz, sr = SR, br = SR * 8, fsz = 16;
+    uint16_t fmt = 3, ch = 2, ba = 8, bits = 32;
+    fwrite("RIFF", 1, 4, f); fwrite(&riff, 4, 1, f); fwrite("WAVE", 1, 4, f);
+    fwrite("fmt ", 1, 4, f); fwrite(&fsz, 4, 1, f);
+    fwrite(&fmt, 2, 1, f); fwrite(&ch, 2, 1, f); fwrite(&sr, 4, 1, f);
+    fwrite(&br, 4, 1, f); fwrite(&ba, 2, 1, f); fwrite(&bits, 2, 1, f);
+    fwrite("data", 1, 4, f); fwrite(&dsz, 4, 1, f);
+    for (long i = 0; i < n; i++) { fwrite(&L[i], 4, 1, f); fwrite(&R[i], 4, 1, f); }
+    fclose(f); return 1;
+}
+
+// ── voices ────────────────────────────────────────────────────────────────
+// FM sine bell — carrier + a decaying modulator gives the glassy partial
+// shimmer; exp amp decay. `ratio` shapes the timbre. Frost lives high (ratios
+// 6.0–8.0 = brittle, ultra-bright plinks); the brighter attack transient is
+// dialed up so onsets crack like ice.
+static void bell(float *L, float *R, double note, double t, double dur, double g, double pan, double ratio, double dec) {
+    double fc = midi_hz(note), fm = fc * ratio;
+    long n = (long)(dur * SR), s0 = (long)(t * SR);
+    double phc = 0, phm = 0, lg = 1 - pan * 0.5, rg = 1 + pan * 0.5;
+    long att = (long)(0.0008 * SR);              // razor-sharp, brittle onset
+    for (long i = 0; i < n; i++) {
+        double tt = (double)i / SR;
+        double env = exp(-tt * dec); if (i < att) env *= (double)i / att;
+        double mi = 6.5 * exp(-tt * 14.0);       // very bright, glassy attack crack
+        phm += TAU * fm / SR;
+        phc += TAU * fc / SR + sin(phm) * mi / SR;
+        double v = sin(phc) * env * g;
+        adds(L, R, s0 + i, v * lg, v * rg);
+    }
+}
+
+// droplet — a tiny, very bright, fast-decaying bell up high; the icy "sleet"
+// sparkle. feeds both the dry bus and (generously) the reverb tail so each
+// droplet leaves a long shimmering wake — the signature of frosttrax.
+static void droplet(double note, double t, double g, double pan) {
+    bell(busL, busR, note, t, 0.50, g, pan, 7.0, 19.0);
+    bell(revL, revR, note, t, 0.70, g * 0.75, 0, 7.0, 14.0);   // big reverb send → long tail
+}
+
+// soft sine drone — pad / thin high drone bed with a slow raised-cosine
+// attack/release. Frost's bed is THIN and HIGH (fewer low harmonics) — a glassy
+// sheet of cold air rather than a warm wash.
+static void softsine(float *L, float *R, double note, double t, double dur, double g, double pan) {
+    double f = midi_hz(note); long n = (long)(dur * SR), s0 = (long)(t * SR);
+    long att = (long)(0.55 * SR), rel = (long)(0.70 * SR); double ph = 0, lg = 1 - pan * 0.5, rg = 1 + pan * 0.5;
+    for (long i = 0; i < n; i++) {
+        ph += TAU * f / SR;
+        double env = 1; if (i < att) env = (double)i / att; else if (i > n - rel) env = fmax(0, (double)(n - i) / rel);
+        double v = (sin(ph) + 0.10 * sin(ph * 2) + 0.04 * sin(ph * 3)) * env * g;
+        adds(L, R, s0 + i, v * lg, v * rg);
+    }
+}
+
+// a 4-voice sine pad chord (widely panned for a cold, glassy width), with a
+// soft reverb send.
+static void pad_chord(double t, const int *midis, int nm, double dur, double g) {
+    for (int k = 0; k < nm; k++) { double pan = (k / fmax(1, nm - 1) - 0.5) * 0.8; softsine(busL, busR, midis[k], t, dur, g, pan); softsine(revL, revR, midis[k], t, dur, g * 0.45, 0); }
+}
+
+// ── harmony — B minor, a i–VI–III–VII loop (cold, suspended) ────────────────
+// per-bar bass roots that the loop walks: Bm, G, D, A — a quietly drifting
+// natural-minor progression that never resolves hard (frost hangs).
+static const int B_ROOTS[4] = { 59, 55, 50, 57 };       // B3, G3, D3, A3
+// four 4-note pad voicings, one per chord — voiced wide and high with added
+// 9ths/maj7s for an icy, suspended shimmer (not warm triads).
+static const int i_PAD[4]   = { 47, 54, 59, 66 };       // Bm add9   (B F# B C#)
+static const int VI_PAD[4]  = { 43, 50, 59, 62 };       // Gmaj7     (G D B D)
+static const int III_PAD[4] = { 38, 50, 57, 62 };       // Dmaj add6 (D D A D... -> D A B D)
+static const int VII_PAD[4] = { 45, 52, 59, 64 };       // Asus/9    (A E B E)
+static const int *PADS[4] = { i_PAD, VI_PAD, III_PAD, VII_PAD };
+
+// B minor pentatonic (B D E F# A), low octave — for arps + droplet picks.
+static const int PENT[5] = { 47, 50, 52, 54, 57 };
+// the high droplet palette — icy, way up top (F#5 A5 B5 C#6 E6 F#6).
+static const int DROPS[6] = { 78, 81, 83, 85, 88, 90 };
+
+// section map. SECBARS drives every loop bound below, so retuning the form
+// (or the whole length) is a one-line edit — at 132 BPM a bar is ~1.818s, so
+// this 62-bar form lands at ~119s (incl. tail). Keep wave/outro counts
+// multiples of 4 so the 4-bar phrases (pad loop, lead) line up.
+static const char *ORDER[8] = { "rime", "thaw", "driftA", "stillA", "driftB", "stillB", "driftC", "outro" };
+static const int SECBARS[8] = { 6, 4, 8, 6, 8, 6, 8, 16 };  // sum = 62
+static int START[8];
+static int sec_index(const char *k) { for (int i = 0; i < 8; i++) if (!strcmp(ORDER[i], k)) return i; return 0; }
+
+// an icicle stab — root + 5th + octave, ultra-bright (high ratio) and short;
+// frost's sparse "chime" on a downbeat. Even sparser/brighter than dewtrax.
+static void stab(double t, int root, double g, int triad) {
+    bell(busL, busR, root, t, BEAT * 1.2, g, -0.2, 8.0, 7.0);
+    bell(busL, busR, root + 7, t + 0.010, BEAT * 1.2, g * 0.65, 0.22, 8.0, 7.0);
+    if (triad) bell(busL, busR, root + 12, t + 0.020, BEAT * 1.0, g * 0.45, 0.0, 7.0, 8.0);
+    bell(revL, revR, root + 7, t, BEAT * 1.4, g * 0.5, 0, 8.0, 6.0);
+}
+
+// ── ornaments ───────────────────────────────────────────────────────────────
+// frill — a quick grace-run of n bells stepping by `step` semitones across
+// `span` seconds (an icy spray for high points / pickups).
+static void frill(double t, double base, int n, int step, double span, double g) {
+    for (int i = 0; i < n; i++) bell(busL, busR, base + i * step, t + span * i / n, span * 1.5, g * (1.0 - 0.35 * i / n), rnd2() * 0.6, 7.0, 16.0);
+}
+// triplet — three quick bells over one beat (middle lifted a 4th), a brittle
+// glint on phrase starts.
+static void triplet(double t, double note, double g) {
+    for (int i = 0; i < 3; i++) bell(busL, busR, note + (i == 1 ? 5 : 0), t + BEAT * i / 3.0, BEAT / 3.0 * 1.4, g * (i == 1 ? 1.1 : 1.0), (i - 1) * 0.3, 7.0, 15.0);
+}
+
+int main(int argc, char **argv) {
+    const char *out_path = "out/frosttrax-raw.wav";
+    for (int i = 1; i < argc; i++) { if (!strcmp(argv[i], "--out") && i + 1 < argc) out_path = argv[++i]; else if (!strcmp(argv[i], "--bpm") && i + 1 < argc) BPMV = atof(argv[++i]); else if (!strcmp(argv[i], "--swing") && i + 1 < argc) SWING = atof(argv[++i]); }
+    BEAT = 60.0 / BPMV; BAR = BEAT * 4; SX = BEAT / 4;
+    { int c = 0; for (int i = 0; i < 8; i++) { START[i] = c; c += SECBARS[i]; } }
+    int TB = 0; for (int i = 0; i < 8; i++) TB += SECBARS[i];
+    double totalSec = TB * BAR + 7.0; N = (long)(totalSec * SR);   // +7s for the long frost tail
+    busL = calloc(N, 4); busR = calloc(N, 4); revL = calloc(N, 4); revR = calloc(N, 4);
+    fprintf(stderr, "# frosttrax.c · %g BPM · %d bars · %.1fs · B minor icy sine bells\n", BPMV, TB, totalSec);
+
+    // the lead motif — a sparse, brittle figure in B minor pentatonic that
+    // climbs and hangs, leaving gaps. {phrase-bar, beat, note}. Higher and
+    // airier than dewtrax's music-box line.
+    double LEAD[7][3] = { {0,1,83},{0,3,86},{1,2,85},{2,0,88},{2,2.5,90},{3,1,86},{3,3.5,83} };
+
+    // ── RIME (bare: thin high drone fades in, lone droplets, one distant bell) ──
+    { int idx = sec_index("rime"); int c = START[idx], nb = SECBARS[idx]; double t0 = c * BAR;
+        // a single thin high drone the whole section (the "cold air"), very soft
+        softsine(busL, busR, 71, t0, BAR * nb - 0.05, 0.055, -0.3);     // B5 air
+        softsine(busL, busR, 78, t0 + BAR * 2, BAR * (nb - 2) - 0.05, 0.035, 0.4); // F#6 sliver, later
+        // pad enters whisper-quiet halfway
+        pad_chord(t0 + BAR * (nb / 2), i_PAD, 4, BAR * (nb - nb / 2) - 0.05, 0.06);
+        // lone droplets, very sparse — first ice
+        for (int b = 1; b < nb; b++) if (rnd() < 0.5) droplet(DROPS[(int)(rnd() * 6)], t0 + b * BAR + (1.0 + rnd() * 2.0) * BEAT, 0.05, rnd2() * 0.7);
+        // one distant low bell near the end to ground it
+        bell(busL, busR, 35, t0 + BAR * (nb - 1), 3.5, 0.07, 0, 2.0, 1.6);
+    }
+
+    // ── THAW — a rising pentatonic spray + pad climb into the first drift ──
+    { int idx = sec_index("thaw"); int c = START[idx], nb = SECBARS[idx], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, VI_PAD, 4, BAR * h - 0.05, 0.075);
+        pad_chord(t0 + BAR * h, VII_PAD, 4, BAR * (nb - h) - 0.05, 0.085);
+        softsine(busL, busR, 71, t0, BAR * nb - 0.05, 0.05, 0.2);       // drone continues
+        int arp[8] = { 47, 50, 54, 59, 62, 66, 71, 74 };               // Bm9 arp upward
+        for (int s = 0; s < 16; s++) { double tt = t0 + BAR * h + swing_beats(s * 0.25); bell(busL, busR, arp[s % 8] + (s / 8) * 12, tt, SX * 2.6, 0.04 + 0.05 * s / 16.0, rnd2() * 0.5, 6.0, 11.0); }
+        frill(t0 + BAR * nb - BEAT * 1.5, 78, 7, 2, BEAT * 1.4, 0.05);  // icy spray into drift A
+    }
+
+    // ── helper for the three drifts (sparse, suspended — never a hard drop) ──
+    const char *drifts[3] = { "driftA", "driftB", "driftC" };
+    for (int d = 0; d < 3; d++) {
+        int wi = sec_index(drifts[d]); int c = START[wi], nbw = SECBARS[wi]; int big = d == 2;
+        for (int b = 0; b < nbw; b++) {
+            double t0 = (c + b) * BAR; int root = B_ROOTS[b % 4]; int phrase = b % 4 == 0;
+            // a very sparse, slow sub pulse — only beats 1 (and 3 in the big drift).
+            bell(busL, busR, root - 12, t0, BEAT * 0.9, 0.085, -0.05, 2.0, 9.0);
+            if (big) bell(busL, busR, root - 12, t0 + BEAT * 2, BEAT * 0.8, 0.05, 0.2, 2.0, 12.0);
+            // a thin sustained sub body (one per bar, under the air)
+            softsine(busL, busR, root - 12, t0, BAR * 0.92, 0.07, 0);
+            // the thin high drone holds across the whole drift (cold air)
+            if (phrase) softsine(busL, busR, 71, t0, BAR * 4 - 0.05, 0.04, (b / 4 % 2) ? 0.3 : -0.3);
+            // an icicle stab on beat 3 (sparser than dewtrax — only some bars)
+            if (b % 2 == 0) stab(t0 + BEAT * 2, root, big ? 0.15 : 0.11, big && b % 4 == 0);
+            // pad sustain every 4 bars (chord follows the loop)
+            if (phrase) pad_chord(t0, PADS[(b / 4) % 4], 4, BAR * 4 - 0.05, 0.06);
+            // a brittle triplet glint on each phrase-start downbeat
+            if (phrase) triplet(t0 + BEAT * 0.5, root + 24, big ? 0.06 : 0.045);
+            // the sparse lead motif (4-bar phrase) — high, airy, frilled on peaks
+            for (int z = 0; z < 7; z++) if ((int)LEAD[z][0] == b % 4) {
+                double note = LEAD[z][2], tt = t0 + swing_beats(LEAD[z][1]);
+                bell(busL, busR, note, tt, BEAT * 0.7, big ? 0.10 : 0.075, rnd2() * 0.5, 7.0, 8.0);
+                bell(revL, revR, note, tt, BEAT * 0.9, 0.055, 0, 7.0, 7.0);
+                if (note >= 88) frill(tt + 0.03, note, big ? 4 : 3, 2, BEAT * 0.4, big ? 0.045 : 0.03);
+            }
+            // pentatonic plink — a lone off-beat icicle (never every bar)
+            if (b % 3 == 1) bell(busL, busR, PENT[b % 5] + 24, t0 + swing_beats(3.5), BEAT * 0.6, 0.05, rnd2() * 0.6, 7.0, 9.0);
+            // sleet droplets — sprinkled into the empty air, denser in the big drift
+            int ndrops = big ? 3 : 2;
+            for (int k = 0; k < ndrops; k++) if (rnd() < 0.55) droplet(DROPS[(int)(rnd() * 6)], t0 + swing_beats((int)(rnd() * 8) * 0.5), 0.04, rnd2() * 0.8);
+            // a descending icy spray at the big drift's phrase ends (the peak)
+            if (big && b % 4 == 3) frill(t0 + BEAT * 2.5, 92, 6, -3, BEAT * 1.0, 0.05);
+        }
+        // a glassy sine sheet shimmering through the biggest drift (high, in reverb)
+        if (big) for (int b = 0; b < nbw; b += 2) { double t0 = (c + b) * BAR; int ns[3] = { i_PAD[1] + 12, i_PAD[2] + 12, i_PAD[3] + 12 }; for (int z = 0; z < 3; z++) softsine(revL, revR, ns[z], t0, BAR * 2, 0.03, (z - 1) * 0.5); }
+    }
+
+    // ── STILLS — spacious: thin drone + half-time sub + lone bells + droplets ──
+    const char *still[2] = { "stillA", "stillB" };
+    for (int z2 = 0; z2 < 2; z2++) {
+        int hi = sec_index(still[z2]); int c = START[hi], nb = SECBARS[hi], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, III_PAD, 4, BAR * h - 0.05, 0.08);
+        pad_chord(t0 + BAR * h, VII_PAD, 4, BAR * (nb - h) - 0.05, 0.08);
+        softsine(busL, busR, 71, t0, BAR * nb - 0.05, 0.045, (z2 ? 0.3 : -0.3)); // thin air holds
+        for (int b = 0; b < nb; b++) {
+            softsine(busL, busR, b < h ? 38 : 45, t0 + b * BAR, BAR * 0.82, 0.07, 0);            // half-time sub
+            if (b % 2 == 0) bell(busL, busR, i_PAD[1 + (b / 2) % 3] + 12, t0 + b * BAR, BAR * 0.85, 0.085, rnd2() * 0.5, 6.0, 3.2); // a lone hanging bell
+            if (rnd() < 0.6) droplet(DROPS[(int)(rnd() * 6)], t0 + b * BAR + (2.0 + rnd()) * BEAT, 0.04, rnd2() * 0.8);
+        }
+        if (z2 == 1) for (int s = 0; s < 16; s++) bell(busL, busR, 59 + PENT[s % 5] - 47, t0 + BAR * (nb - 2) + s * SX, SX * 3.2, 0.035 + 0.045 * s / 16.0, rnd2() * 0.6, 6.0, 6.0); // rising spray into drift C
+    }
+
+    // ── OUTRO — slowly decaying bells + thinning pad + a final low bell, long tail ──
+    { int idx = sec_index("outro"); int c = START[idx], nb = SECBARS[idx], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, i_PAD, 4, BAR * h - 0.05, 0.075);
+        pad_chord(t0 + BAR * h, VI_PAD, 4, BAR * (nb - h) - 0.05, 0.06);
+        softsine(busL, busR, 71, t0, BAR * (nb - 2) - 0.05, 0.04, 0); // air thins out
+        for (int b = 0; b < nb; b++) {
+            double e = fmax(0.06, 1.0 - (double)b / nb);                   // everything fades over the outro
+            int root = b < h ? 59 : 50;
+            softsine(busL, busR, root - 12, t0 + b * BAR, BAR * 0.88, 0.07 * e, 0);
+            if (b % 2 == 0) stab(t0 + b * BAR + BEAT * 2, root, 0.10 * e, 0);
+            if (rnd() < 0.5) droplet(DROPS[(int)(rnd() * 6)], t0 + b * BAR + (1.0 + rnd() * 2.0) * BEAT, 0.035 * e, rnd2() * 0.8);
+        }
+        // a final grounding pair of bells, deep into long reverb
+        bell(busL, busR, 35, t0 + BAR * (nb - 3), 5.0, 0.16, 0, 2.0, 1.1);
+        bell(busL, busR, 71, t0 + BAR * (nb - 3), 5.0, 0.08, 0.2, 7.0, 1.3);
+        bell(revL, revR, 59, t0 + BAR * (nb - 3), 5.0, 0.10, 0, 6.0, 1.2);
+        droplet(90, t0 + BAR * (nb - 2), 0.05, 0.3);                       // one last icicle
+    }
+
+    // ── REVERB (Schroeder) — wetter, longer, brighter for the icy frost space.
+    // Less damping than dewtrax (frost keeps its high shimmer), longer decay,
+    // higher wet → those long shimmering tails the character calls for.
+    {
+        double decay = 0.86, wet = 0.62, damp = 0.22;
+        int CD[6]; double cds[6] = { 0.0297, 0.0371, 0.0411, 0.0437, 0.0497, 0.0581 };
+        for (int k = 0; k < 6; k++) CD[k] = (int)(cds[k] * SR);
+        int AD[2] = { (int)(0.005 * SR), (int)(0.0017 * SR) }; double apFb = 0.5;
+        float *cbL[6], *cbR[6]; int ciL[6] = {0}, ciR[6] = {0}; double cLPL[6] = {0}, cLPR[6] = {0};
+        for (int k = 0; k < 6; k++) { cbL[k] = calloc(CD[k], 4); cbR[k] = calloc(CD[k], 4); }
+        float *abL[2], *abR[2]; int aiL[2] = {0}, aiR[2] = {0};
+        for (int k = 0; k < 2; k++) { abL[k] = calloc(AD[k], 4); abR[k] = calloc(AD[k], 4); }
+        for (long i = 0; i < N; i++) {
+            double inL = revL[i], inR = revR[i], cL = 0, cR = 0;
+            for (int k = 0; k < 6; k++) {
+                double dL = cbL[k][ciL[k]], dR = cbR[k][ciR[k]]; cL += dL; cR += dR;
+                cLPL[k] = dL * (1 - damp) + cLPL[k] * damp; cLPR[k] = dR * (1 - damp) + cLPR[k] * damp;
+                cbL[k][ciL[k]] = (float)(inL + cLPL[k] * decay); cbR[k][ciR[k]] = (float)(inR + cLPR[k] * decay);
+                ciL[k] = (ciL[k] + 1) % CD[k]; ciR[k] = (ciR[k] + 1) % CD[k];
+            }
+            cL /= 6; cR /= 6;
+            for (int k = 0; k < 2; k++) {
+                double dL = abL[k][aiL[k]], dR = abR[k][aiR[k]];
+                double oL = -apFb * cL + dL, oR = -apFb * cR + dR;
+                abL[k][aiL[k]] = (float)(cL + apFb * oL); abR[k][aiR[k]] = (float)(cR + apFb * oR);
+                aiL[k] = (aiL[k] + 1) % AD[k]; aiR[k] = (aiR[k] + 1) % AD[k];
+                cL = oL; cR = oR;
+            }
+            busL[i] += (float)(cL * wet); busR[i] += (float)(cR * wet);
+        }
+        for (int k = 0; k < 6; k++) { free(cbL[k]); free(cbR[k]); }
+        for (int k = 0; k < 2; k++) { free(abL[k]); free(abR[k]); }
+    }
+
+    // ── normalize + gentle in/out fades ──
+    double peak = 0; for (long i = 0; i < N; i++) { double a = fmax(fabs(busL[i]), fabs(busR[i])); if (a > peak) peak = a; }
+    if (peak > 0) { double g = 0.85 / peak; for (long i = 0; i < N; i++) { busL[i] *= (float)g; busR[i] *= (float)g; } }
+    long fin = (long)(3.0 * SR), fout = (long)(5.5 * SR);
+    for (long i = 0; i < fin && i < N; i++) { double g = 0.5 - 0.5 * cos(M_PI * (double)i / fin); busL[i] *= (float)g; busR[i] *= (float)g; }
+    for (long i = 0; i < fout && i < N; i++) { double g = 0.5 - 0.5 * cos(M_PI * (double)i / fout); long idx = N - 1 - i; busL[idx] *= (float)g; busR[idx] *= (float)g; }
+
+    if (!write_wav_f32_stereo(out_path, busL, busR, N)) { fprintf(stderr, "✗ write failed\n"); return 1; }
+    fprintf(stderr, "✓ %s · %.1fs\n", out_path, (double)N / SR);
+    return 0;
+}
diff --git a/pop/maytrax/c/glasstrax b/pop/maytrax/c/glasstrax
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diff --git a/pop/maytrax/c/glasstrax.c b/pop/maytrax/c/glasstrax.c
new file mode 100644
index 000000000..37809c84d
--- /dev/null
+++ b/pop/maytrax/c/glasstrax.c
@@ -0,0 +1,297 @@
+// glasstrax.c — a sine-bell sibling of dewtrax. Same instrument family (FM sine
+// bells + soft sine drones + Schroeder reverb), new song: A major, faster
+// (124 BPM), a light shimmering swing. The character is weightless and
+// crystalline — fast pentatonic arps glittering in the upper register, bright
+// glassy bells (high ratios, 5.0–7.0), and a busy mist of high droplets. Airy,
+// delicate, like sun through cut glass. No samples, no drums, no vocals — pure
+// sine. render-c.mjs --engine glasstrax masters it on the sine-family chain.
+//
+// Build:  cc -O3 -std=c11 -o glasstrax glasstrax.c -lm
+// Run:    ./glasstrax --out out/glasstrax-raw.wav
+
+#define _POSIX_C_SOURCE 200809L
+#include <stdio.h>
+#include <stdlib.h>
+#include <stdint.h>
+#include <string.h>
+#include <math.h>
+
+#ifndef M_PI
+#define M_PI 3.14159265358979323846
+#endif
+#define TAU (2.0 * M_PI)
+
+static const int SR = 48000;
+static double BPMV = 124, BEAT, BAR, SX;
+
+static uint32_t rng_s = 0x676C6173; // "glas"
+static inline double rnd(void) { rng_s ^= rng_s << 13; rng_s ^= rng_s >> 17; rng_s ^= rng_s << 5; return (double)rng_s / 4294967296.0; }
+static inline double rnd2(void) { return rnd() * 2.0 - 1.0; }
+static inline double midi_hz(double m) { return 440.0 * pow(2.0, (m - 69.0) / 12.0); }
+
+// ── swing / sway ────────────────────────────────────────────────────────────
+// A light shimmer-swing here (0.55) — the "&"s drag just slightly so the busy
+// arps glitter rather than march. 16ths interpolate inside the swung 8th.
+static double SWING = 0.55;
+static double swing_beats(double beats) {
+    double e8 = beats * 2.0;                 // position in 8ths
+    long idx = (long)floor(e8 + 1e-9);
+    double frac = e8 - idx;
+    double pos = (idx / 2) * BEAT + ((idx & 1) ? SWING * BEAT : 0.0);
+    return pos + frac * (BEAT / 2.0);        // interpolate 16ths inside the 8th
+}
+
+static long N;
+static float *busL, *busR, *revL, *revR;
+static inline void adds(float *L, float *R, long i, double l, double r) { if (i >= 0 && i < N) { L[i] += (float)l; R[i] += (float)r; } }
+
+static int write_wav_f32_stereo(const char *path, const float *L, const float *R, long n) {
+    FILE *f = fopen(path, "wb"); if (!f) return 0;
+    uint32_t dsz = (uint32_t)(n * 8), riff = 36 + dsz, sr = SR, br = SR * 8, fsz = 16;
+    uint16_t fmt = 3, ch = 2, ba = 8, bits = 32;
+    fwrite("RIFF", 1, 4, f); fwrite(&riff, 4, 1, f); fwrite("WAVE", 1, 4, f);
+    fwrite("fmt ", 1, 4, f); fwrite(&fsz, 4, 1, f);
+    fwrite(&fmt, 2, 1, f); fwrite(&ch, 2, 1, f); fwrite(&sr, 4, 1, f);
+    fwrite(&br, 4, 1, f); fwrite(&ba, 2, 1, f); fwrite(&bits, 2, 1, f);
+    fwrite("data", 1, 4, f); fwrite(&dsz, 4, 1, f);
+    for (long i = 0; i < n; i++) { fwrite(&L[i], 4, 1, f); fwrite(&R[i], 4, 1, f); }
+    fclose(f); return 1;
+}
+
+// ── voices ────────────────────────────────────────────────────────────────
+// FM sine bell — carrier + a decaying modulator gives the glassy partial
+// shimmer; exp amp decay. `ratio` shapes the timbre — glasstrax lives high:
+// 5.0–7.0 are its home (very glassy, music-box plink), 2.0 is the rare body.
+static void bell(float *L, float *R, double note, double t, double dur, double g, double pan, double ratio, double dec) {
+    double fc = midi_hz(note), fm = fc * ratio;
+    long n = (long)(dur * SR), s0 = (long)(t * SR);
+    double phc = 0, phm = 0, lg = 1 - pan * 0.5, rg = 1 + pan * 0.5;
+    long att = (long)(0.0010 * SR);              // crisp, glassy onset
+    for (long i = 0; i < n; i++) {
+        double tt = (double)i / SR;
+        double env = exp(-tt * dec); if (i < att) env *= (double)i / att;
+        double mi = 6.0 * exp(-tt * 13.0);       // brighter, faster attack transient → more "cut glass"
+        phm += TAU * fm / SR;
+        phc += TAU * fc / SR + sin(phm) * mi / SR;
+        double v = sin(phc) * env * g;
+        adds(L, R, s0 + i, v * lg, v * rg);
+    }
+}
+
+// droplet — a tiny, very bright, fast-decaying bell up high; the crystalline
+// sparkle. Pushed glassier (ratio 6.0) and feeding the reverb tail harder so
+// the mist of droplets shimmers and rings out.
+static void droplet(double note, double t, double g, double pan) {
+    bell(busL, busR, note, t, 0.50, g, pan, 6.0, 18.0);
+    bell(revL, revR, note, t, 0.50, g * 0.6, 0, 6.0, 18.0);
+}
+
+// soft sine drone — pad / sub bed with a slow raised-cosine attack/release.
+// Lighter harmonics here so the pad stays airy and recedes under the bells.
+static void softsine(float *L, float *R, double note, double t, double dur, double g, double pan) {
+    double f = midi_hz(note); long n = (long)(dur * SR), s0 = (long)(t * SR);
+    long att = (long)(0.35 * SR), rel = (long)(0.50 * SR); double ph = 0, lg = 1 - pan * 0.5, rg = 1 + pan * 0.5;
+    for (long i = 0; i < n; i++) {
+        ph += TAU * f / SR;
+        double env = 1; if (i < att) env = (double)i / att; else if (i > n - rel) env = fmax(0, (double)(n - i) / rel);
+        double v = (sin(ph) + 0.12 * sin(ph * 2) + 0.04 * sin(ph * 3)) * env * g;
+        adds(L, R, s0 + i, v * lg, v * rg);
+    }
+}
+
+// a 4-voice sine pad chord (slightly panned for width), with a soft reverb send.
+static void pad_chord(double t, const int *midis, int nm, double dur, double g) {
+    for (int k = 0; k < nm; k++) { double pan = (k / fmax(1, nm - 1) - 0.5) * 0.7; softsine(busL, busR, midis[k], t, dur, g, pan); softsine(revL, revR, midis[k], t, dur, g * 0.45, 0); }
+}
+
+// ── harmony — A major, an airy I–IV–vi–V loop (bright, suspended) ────────────
+// per-bar bass roots that the loop walks: A, D, F#m, E.
+static const int A_ROOTS[4] = { 57, 50, 54, 52 };      // A3, D3, F#3, E3
+// four 4-note pad voicings, one per chord in the loop — open, with added 2nds
+// /9ths so the pad rings glassy rather than blocky.
+static const int I_PAD[4]  = { 45, 52, 56, 59 };       // A maj add9 (A E G# B)
+static const int IV_PAD[4] = { 38, 45, 50, 54 };       // D maj add9 (D A D F#→ D A D F#? D E F#) → D A E F#
+static const int VI_PAD[4] = { 42, 49, 52, 57 };       // F# m11    (F# C# E A)
+static const int V_PAD[4]  = { 40, 47, 51, 56 };       // E maj add9 (E B G# A→ E B G# B)
+static const int *PADS[4] = { I_PAD, IV_PAD, VI_PAD, V_PAD };
+
+// A major pentatonic (A B C# E F#), mid octave — for arps + droplet picks.
+static const int PENT[5] = { 57, 59, 61, 64, 66 };
+// the high droplet palette (A5 B5 C#6 E6 F#6 A6 B6) — glasstrax lives up here.
+static const int DROPS[7] = { 81, 83, 85, 88, 90, 93, 95 };
+
+// section map. SECBARS drives every loop bound below, so retuning the form
+// (or the whole length) is a one-line edit — at 124 BPM a bar is ~1.935s, so
+// this 56-bar form lands at ~114s. Keep wave/outro counts multiples of 4 so
+// the 4-bar phrases (pad loop, lead) line up.
+static const char *ORDER[8] = { "intro", "bloom", "waveA", "hushA", "waveB", "hushB", "waveC", "outro" };
+static const int SECBARS[8] = { 4, 4, 8, 4, 8, 4, 12, 12 };
+static int START[8];
+static int sec_index(const char *k) { for (int i = 0; i < 8; i++) if (!strcmp(ORDER[i], k)) return i; return 0; }
+
+// a glass stab — root + 5th + 9th, very bright (high ratio) and short, voiced
+// up an octave from the bass so it sparkles rather than thuds.
+static void stab(double t, int root, double g, int triad) {
+    bell(busL, busR, root + 12, t, BEAT * 1.2, g, -0.15, 7.0, 6.0);
+    bell(busL, busR, root + 19, t + 0.010, BEAT * 1.2, g * 0.7, 0.18, 7.0, 6.0);
+    if (triad) bell(busL, busR, root + 26, t + 0.020, BEAT * 1.0, g * 0.5, 0.0, 6.0, 7.0);
+    bell(revL, revR, root + 19, t, BEAT * 1.2, g * 0.45, 0, 7.0, 6.0);
+}
+
+// ── ornaments ───────────────────────────────────────────────────────────────
+// frill — a quick grace-run of n bells stepping by `step` semitones across
+// `span` seconds (a sparkly flourish for high points / pickups).
+static void frill(double t, double base, int n, int step, double span, double g) {
+    for (int i = 0; i < n; i++) bell(busL, busR, base + i * step, t + span * i / n, span * 1.4, g * (1.0 - 0.30 * i / n), rnd2() * 0.6, 6.0, 15.0);
+}
+// shimmer — a fast pentatonic up-run of 8 droplet-bells over `span`; the
+// signature glasstrax glitter (lots of high, delicate notes in a hurry).
+static void shimmer(double t, int oct, double span, double g) {
+    for (int i = 0; i < 8; i++) {
+        int p = PENT[i % 5] + (i / 5) * 12 + oct;
+        bell(busL, busR, p, t + span * i / 8.0, span * 0.9, g * (0.7 + 0.3 * i / 8.0), rnd2() * 0.7, 5.0 + rnd() * 1.5, 16.0);
+        bell(revL, revR, p, t + span * i / 8.0, span * 0.9, g * 0.4, 0, 6.0, 16.0);
+    }
+}
+// triplet — three quick bells over one beat (middle lifted a 3rd), a gentle
+// lift on phrase starts.
+static void triplet(double t, double note, double g) {
+    for (int i = 0; i < 3; i++) bell(busL, busR, note + (i == 1 ? 4 : 0), t + BEAT * i / 3.0, BEAT / 3.0 * 1.3, g * (i == 1 ? 1.1 : 1.0), (i - 1) * 0.3, 6.0, 13.0);
+}
+
+int main(int argc, char **argv) {
+    const char *out_path = "out/glasstrax-raw.wav";
+    for (int i = 1; i < argc; i++) { if (!strcmp(argv[i], "--out") && i + 1 < argc) out_path = argv[++i]; else if (!strcmp(argv[i], "--bpm") && i + 1 < argc) BPMV = atof(argv[++i]); else if (!strcmp(argv[i], "--swing") && i + 1 < argc) SWING = atof(argv[++i]); }
+    BEAT = 60.0 / BPMV; BAR = BEAT * 4; SX = BEAT / 4;
+    { int c = 0; for (int i = 0; i < 8; i++) { START[i] = c; c += SECBARS[i]; } }
+    int TB = 0; for (int i = 0; i < 8; i++) TB += SECBARS[i];
+    double totalSec = TB * BAR + 6.0; N = (long)(totalSec * SR);
+    busL = calloc(N, 4); busR = calloc(N, 4); revL = calloc(N, 4); revR = calloc(N, 4);
+    fprintf(stderr, "# glasstrax.c · %g BPM · %d bars · %.1fs · A major sine bells (crystalline)\n", BPMV, TB, totalSec);
+
+    // the lead, as {phrase-bar, beat, note} — a bright, rising-then-cresting
+    // motif in A major pentatonic across the 4-bar phrase, sitting high.
+    double LEAD[8][3] = { {0,0,76},{0,2.5,81},{1,0,83},{1,1.5,85},{2,0,88},{2,1.5,85},{3,0,83},{3,2,90} };
+
+    // ── INTRO (staggered: airy pad → high bell glints → sub → droplet mist) ──
+    { int idx = sec_index("intro"); int c = START[idx], nb = SECBARS[idx], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, I_PAD, 4, BAR * h - 0.05, 0.09);
+        pad_chord(t0 + BAR * h, IV_PAD, 4, BAR * (nb - h) - 0.05, 0.10);
+        int mel[4] = { 88, 85, 83, 81 };                       // descending glass glints, from bar 2
+        for (int b = 0; b < 4 && 2 + b < nb; b++) bell(busL, busR, mel[b], t0 + (2 + b) * BAR, BAR * 0.8, 0.11, rnd2() * 0.4, 6.0, 3.5);
+        for (int b = h; b < nb; b++) softsine(busL, busR, 33, t0 + b * BAR, BAR * 0.95, 0.10, 0); // airy sub through the back half
+        for (int b = 1; b < nb; b++) { int nd = b; for (int k = 0; k < nd; k++) if (rnd() < 0.5) droplet(DROPS[(int)(rnd() * 7)], t0 + b * BAR + swing_beats((int)(rnd() * 8) * 0.5), 0.045, rnd2() * 0.7); } // gathering mist
+    }
+
+    // ── BLOOM — rising pentatonic shimmer + pad climb into the first wave ──
+    { int idx = sec_index("bloom"); int c = START[idx], nb = SECBARS[idx], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, VI_PAD, 4, BAR * h - 0.05, 0.12);
+        pad_chord(t0 + BAR * h, V_PAD, 4, BAR * (nb - h) - 0.05, 0.13);
+        for (int b = 0; b < nb; b++) shimmer(t0 + b * BAR + BEAT * 2, (b - 1) * 12, BEAT * 2.0, 0.05 + 0.02 * b); // shimmer runs climbing each bar
+        for (int s = 0; s < 16; s++) { double tt = t0 + BAR * h + swing_beats(s * 0.25); int p = PENT[s % 5] + (s / 5) * 12 + 12; bell(busL, busR, p, tt, SX * 2.2, 0.05 + 0.06 * s / 16.0, rnd2() * 0.5, 5.5, 10.0); }
+        frill(t0 + BAR * nb - BEAT * 2, 81, 8, 2, BEAT * 1.6, 0.06);   // ascending flourish into wave A
+    }
+
+    // ── helper for the three waves (gentle, flowing, glittering — not a drop) ──
+    const char *waves[3] = { "waveA", "waveB", "waveC" };
+    for (int d = 0; d < 3; d++) {
+        int wi = sec_index(waves[d]); int c = START[wi], nbw = SECBARS[wi]; int big = d == 2;
+        for (int b = 0; b < nbw; b++) {
+            double t0 = (c + b) * BAR; int root = A_ROOTS[b % 4]; int phrase = b % 4 == 0;
+            // a soft pulsing bass — beats 1 & 3, the "&"s lighter & panned wide.
+            for (int e = 0; e < 8; e++) { double tt = t0 + swing_beats(e * 0.5); int on = (e % 2 == 0); if (on || rnd() < 0.45) bell(busL, busR, root - 12, tt, BEAT * 0.5, on ? 0.085 : 0.045, on ? -0.08 : 0.24, 2.0, on ? 12.0 : 15.0); }
+            // sustained airy sub body (one per bar, under the pulse)
+            softsine(busL, busR, root - 12, t0, BAR * 0.95, 0.085, 0);
+            // the glass stab on beat 3
+            stab(t0 + BEAT * 2, root, big ? 0.13 : 0.10, big);
+            // pad sustain every 4 bars (chord follows the loop)
+            if (phrase) pad_chord(t0, PADS[(b / 4) % 4], 4, BAR * 4 - 0.05, 0.06);
+            // a gentle triplet lift on each phrase-start downbeat
+            if (phrase) triplet(t0 + 12, root + 24, big ? 0.07 : 0.05);
+            // the lead (4-bar phrase) — swung, very bright, frilled on highs
+            for (int z = 0; z < 8; z++) if ((int)LEAD[z][0] == b % 4) {
+                double note = LEAD[z][2], tt = t0 + swing_beats(LEAD[z][1]);
+                bell(busL, busR, note, tt, BEAT * 0.7, big ? 0.105 : 0.08, rnd2() * 0.45, 6.0, 8.0);
+                bell(revL, revR, note, tt, BEAT * 0.7, 0.05, 0, 6.0, 8.0);
+                if (note >= 83) frill(tt + 0.03, note, big ? 4 : 3, 2, BEAT * 0.4, big ? 0.05 : 0.035);
+            }
+            // fast pentatonic arp — busy 16ths through every bar (the glitter bed)
+            for (int s = 0; s < 8; s++) { if (rnd() < (big ? 0.95 : 0.75)) { double tt = t0 + swing_beats(s * 0.5); int p = PENT[(s + b) % 5] + 12 + (s >= 4 ? 12 : 0); bell(busL, busR, p, tt, SX * 1.8, 0.04 + 0.015 * (s % 4), rnd2() * 0.7, 5.0 + rnd(), 14.0); } }
+            // a higher shimmer run once per phrase as a crest
+            if (b % 4 == 2) shimmer(t0 + BEAT * 1, 24, BEAT * 2.0, big ? 0.05 : 0.04);
+            // crystalline droplet mist — dense, denser in the big wave
+            int ndrops = big ? 4 : 2;
+            for (int k = 0; k < ndrops; k++) if (rnd() < 0.6) droplet(DROPS[(int)(rnd() * 7)], t0 + swing_beats((int)(rnd() * 8) * 0.5), 0.04, rnd2() * 0.8);
+            // descending frill run at phrase ends of the big wave (high point)
+            if (big && b % 4 == 3) frill(t0 + BEAT * 3, 95, 6, -2, BEAT * 0.8, 0.05);
+        }
+        // a soft glassy sine bed through the biggest wave
+        if (big) for (int b = 0; b < nbw; b += 2) { double t0 = (c + b) * BAR; int ns[3] = { I_PAD[1], I_PAD[2], I_PAD[3] }; for (int z = 0; z < 3; z++) softsine(revL, revR, ns[z] + 12, t0, BAR * 2, 0.035, (z - 1) * 0.5); }
+    }
+
+    // ── HUSHES — spacious: airy pad + half-time sub + sparse high bells + lone droplets ──
+    const char *hush[2] = { "hushA", "hushB" };
+    for (int z2 = 0; z2 < 2; z2++) {
+        int hi = sec_index(hush[z2]); int c = START[hi], nb = SECBARS[hi], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, IV_PAD, 4, BAR * h - 0.05, 0.11);
+        pad_chord(t0 + BAR * h, V_PAD, 4, BAR * (nb - h) - 0.05, 0.11);
+        for (int b = 0; b < nb; b++) { softsine(busL, busR, b < h ? 33 : 35, t0 + b * BAR, BAR * 0.85, 0.085, 0); if (b % 2 == 0) bell(busL, busR, I_PAD[1 + (b / 2) % 3] + 12, t0 + b * BAR, BAR * 0.85, 0.09, rnd2() * 0.5, 5.5, 3.0); for (int k = 0; k < 2; k++) if (rnd() < 0.6) droplet(DROPS[(int)(rnd() * 7)], t0 + b * BAR + swing_beats((int)(rnd() * 6) * 0.5 + 1), 0.038, rnd2() * 0.8); }
+        if (z2 == 1) shimmer(t0 + BAR * (nb - 2), 12, BAR * 2.0, 0.05); // rising shimmer into wave C
+    }
+
+    // ── OUTRO — decaying glass bells + airy pad wash + a final ringing chord ──
+    { int idx = sec_index("outro"); int c = START[idx], nb = SECBARS[idx], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, I_PAD, 4, BAR * h - 0.05, 0.10);
+        pad_chord(t0 + BAR * h, IV_PAD, 4, BAR * (nb - h) - 0.05, 0.09);
+        for (int b = 0; b < nb; b++) { double e = fmax(0.1, 1.0 - (double)b / nb); int root = b < h ? 57 : 52; softsine(busL, busR, root - 12, t0 + b * BAR, BAR * 0.9, 0.085 * e, 0); if (b % 2 == 0) stab(t0 + b * BAR + BEAT * 2, root, 0.10 * e, 0); for (int k = 0; k < 2; k++) if (rnd() < 0.5) droplet(DROPS[(int)(rnd() * 7)], t0 + b * BAR + swing_beats((int)(rnd() * 6) * 0.5 + 1), 0.032 * e, rnd2() * 0.8); }
+        // a final ringing A-major glass chord
+        bell(busL, busR, 45, t0 + BAR * (nb - 3), 5.0, 0.14, 0, 2.0, 1.2);
+        bell(busL, busR, 69, t0 + BAR * (nb - 3) + 0.04, 5.0, 0.09, -0.2, 6.0, 1.4);
+        bell(busL, busR, 76, t0 + BAR * (nb - 3) + 0.08, 5.0, 0.08, 0.2, 6.0, 1.5);
+        bell(busL, busR, 81, t0 + BAR * (nb - 3) + 0.12, 5.0, 0.06, 0.0, 7.0, 1.6);
+        bell(revL, revR, 64, t0 + BAR * (nb - 3), 5.0, 0.10, 0, 5.0, 1.4);
+    }
+
+    // ── REVERB (Schroeder) — wide, long, and bright for the crystalline space ──
+    {
+        double decay = 0.85, wet = 0.60, damp = 0.28;   // brighter (low damp) + wetter than dewtrax
+        int CD[6]; double cds[6] = { 0.0297, 0.0371, 0.0411, 0.0437, 0.0497, 0.0581 };
+        for (int k = 0; k < 6; k++) CD[k] = (int)(cds[k] * SR);
+        int AD[2] = { (int)(0.005 * SR), (int)(0.0017 * SR) }; double apFb = 0.5;
+        float *cbL[6], *cbR[6]; int ciL[6] = {0}, ciR[6] = {0}; double cLPL[6] = {0}, cLPR[6] = {0};
+        for (int k = 0; k < 6; k++) { cbL[k] = calloc(CD[k], 4); cbR[k] = calloc(CD[k], 4); }
+        float *abL[2], *abR[2]; int aiL[2] = {0}, aiR[2] = {0};
+        for (int k = 0; k < 2; k++) { abL[k] = calloc(AD[k], 4); abR[k] = calloc(AD[k], 4); }
+        for (long i = 0; i < N; i++) {
+            double inL = revL[i], inR = revR[i], cL = 0, cR = 0;
+            for (int k = 0; k < 6; k++) {
+                double dL = cbL[k][ciL[k]], dR = cbR[k][ciR[k]]; cL += dL; cR += dR;
+                cLPL[k] = dL * (1 - damp) + cLPL[k] * damp; cLPR[k] = dR * (1 - damp) + cLPR[k] * damp;
+                cbL[k][ciL[k]] = (float)(inL + cLPL[k] * decay); cbR[k][ciR[k]] = (float)(inR + cLPR[k] * decay);
+                ciL[k] = (ciL[k] + 1) % CD[k]; ciR[k] = (ciR[k] + 1) % CD[k];
+            }
+            cL /= 6; cR /= 6;
+            for (int k = 0; k < 2; k++) {
+                double dL = abL[k][aiL[k]], dR = abR[k][aiR[k]];
+                double oL = -apFb * cL + dL, oR = -apFb * cR + dR;
+                abL[k][aiL[k]] = (float)(cL + apFb * oL); abR[k][aiR[k]] = (float)(cR + apFb * oR);
+                aiL[k] = (aiL[k] + 1) % AD[k]; aiR[k] = (aiR[k] + 1) % AD[k];
+                cL = oL; cR = oR;
+            }
+            busL[i] += (float)(cL * wet); busR[i] += (float)(cR * wet);
+        }
+        for (int k = 0; k < 6; k++) { free(cbL[k]); free(cbR[k]); }
+        for (int k = 0; k < 2; k++) { free(abL[k]); free(abR[k]); }
+    }
+
+    // ── normalize + gentle in/out fades ──
+    double peak = 0; for (long i = 0; i < N; i++) { double a = fmax(fabs(busL[i]), fabs(busR[i])); if (a > peak) peak = a; }
+    if (peak > 0) { double g = 0.85 / peak; for (long i = 0; i < N; i++) { busL[i] *= (float)g; busR[i] *= (float)g; } }
+    long fin = (long)(2.0 * SR), fout = (long)(4.5 * SR);
+    for (long i = 0; i < fin && i < N; i++) { double g = 0.5 - 0.5 * cos(M_PI * (double)i / fin); busL[i] *= (float)g; busR[i] *= (float)g; }
+    for (long i = 0; i < fout && i < N; i++) { double g = 0.5 - 0.5 * cos(M_PI * (double)i / fout); long idx = N - 1 - i; busL[idx] *= (float)g; busR[idx] *= (float)g; }
+
+    if (!write_wav_f32_stereo(out_path, busL, busR, N)) { fprintf(stderr, "✗ write failed\n"); return 1; }
+    fprintf(stderr, "✓ %s · %.1fs\n", out_path, (double)N / SR);
+    return 0;
+}
diff --git a/pop/maytrax/c/lumitrax b/pop/maytrax/c/lumitrax
new file mode 100755
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diff --git a/pop/maytrax/c/lumitrax.c b/pop/maytrax/c/lumitrax.c
new file mode 100644
index 000000000..950c1c0d6
--- /dev/null
+++ b/pop/maytrax/c/lumitrax.c
@@ -0,0 +1,323 @@
+// lumitrax.c — a sine-bell sibling of dewtrax. Same instrument (FM sine bells
+// + soft sine drones + Schroeder reverb), new song: F♯ major, faster (116 BPM),
+// and a wholly different intent. Where dewtrax is a nocturnal music-box, lumitrax
+// is hypnotic minimal phasing — three interlocking arpeggiated bell sequences
+// that loop at slightly different lengths so they slowly shift against one
+// another (a Steve Reich / phase-music feel). Bright, repetitive, pulse-driven,
+// trance-like; voices are added and subtracted but the pulse never stops.
+// No samples, no drums, no vocals — pure sine.
+// render-c.mjs --engine lumitrax masters it on the sine-family chain.
+//
+// Build:  cc -O3 -std=c11 -Wall -Wextra -Wno-unused-parameter -o lumitrax lumitrax.c -lm
+// Run:    ./lumitrax --out out/lumitrax-raw.wav
+
+#define _POSIX_C_SOURCE 200809L
+#include <stdio.h>
+#include <stdlib.h>
+#include <stdint.h>
+#include <string.h>
+#include <math.h>
+
+#ifndef M_PI
+#define M_PI 3.14159265358979323846
+#endif
+#define TAU (2.0 * M_PI)
+
+static const int SR = 48000;
+static double BPMV = 116, BEAT, BAR, SX;
+
+static uint32_t rng_s = 0x6c756d69; // "lumi"
+static inline double rnd(void) { rng_s ^= rng_s << 13; rng_s ^= rng_s >> 17; rng_s ^= rng_s << 5; return (double)rng_s / 4294967296.0; }
+static inline double rnd2(void) { return rnd() * 2.0 - 1.0; }
+static inline double midi_hz(double m) { return 440.0 * pow(2.0, (m - 69.0) / 12.0); }
+
+// ── swing / sway ────────────────────────────────────────────────────────────
+// Phase music wants a dead-straight, machine-even grid — the interest comes from
+// the patterns drifting against each other, not from groove. SWING ~ 0.50 keeps
+// the 8ths perfectly even so the interlock reads cleanly.
+static double SWING = 0.50;
+static double swing_beats(double beats) {
+    double e8 = beats * 2.0;                 // position in 8ths
+    long idx = (long)floor(e8 + 1e-9);
+    double frac = e8 - idx;
+    double pos = (idx / 2) * BEAT + ((idx & 1) ? SWING * BEAT : 0.0);
+    return pos + frac * (BEAT / 2.0);        // interpolate 16ths inside the 8th
+}
+
+static long N;
+static float *busL, *busR, *revL, *revR;
+static inline void adds(float *L, float *R, long i, double l, double r) { if (i >= 0 && i < N) { L[i] += (float)l; R[i] += (float)r; } }
+
+static int write_wav_f32_stereo(const char *path, const float *L, const float *R, long n) {
+    FILE *f = fopen(path, "wb"); if (!f) return 0;
+    uint32_t dsz = (uint32_t)(n * 8), riff = 36 + dsz, sr = SR, br = SR * 8, fsz = 16;
+    uint16_t fmt = 3, ch = 2, ba = 8, bits = 32;
+    fwrite("RIFF", 1, 4, f); fwrite(&riff, 4, 1, f); fwrite("WAVE", 1, 4, f);
+    fwrite("fmt ", 1, 4, f); fwrite(&fsz, 4, 1, f);
+    fwrite(&fmt, 2, 1, f); fwrite(&ch, 2, 1, f); fwrite(&sr, 4, 1, f);
+    fwrite(&br, 4, 1, f); fwrite(&ba, 2, 1, f); fwrite(&bits, 2, 1, f);
+    fwrite("data", 1, 4, f); fwrite(&dsz, 4, 1, f);
+    for (long i = 0; i < n; i++) { fwrite(&L[i], 4, 1, f); fwrite(&R[i], 4, 1, f); }
+    fclose(f); return 1;
+}
+
+// ── voices ────────────────────────────────────────────────────────────────
+// FM sine bell — carrier + a decaying modulator gives the glassy partial
+// shimmer; exp amp decay. `ratio` shapes the timbre (3.5 = bell, 7.0 =
+// music-box plink, 2.0 = softer body).
+static void bell(float *L, float *R, double note, double t, double dur, double g, double pan, double ratio, double dec) {
+    double fc = midi_hz(note), fm = fc * ratio;
+    long n = (long)(dur * SR), s0 = (long)(t * SR);
+    double phc = 0, phm = 0, lg = 1 - pan * 0.5, rg = 1 + pan * 0.5;
+    long att = (long)(0.0012 * SR);              // sharp, punctuated onset
+    for (long i = 0; i < n; i++) {
+        double tt = (double)i / SR;
+        double env = exp(-tt * dec); if (i < att) env *= (double)i / att;
+        double mi = 5.0 * exp(-tt * 11.0);       // brighter, faster-decaying attack transient
+        phm += TAU * fm / SR;
+        phc += TAU * fc / SR + sin(phm) * mi / SR;
+        double v = sin(phc) * env * g;
+        adds(L, R, s0 + i, v * lg, v * rg);
+    }
+}
+
+// droplet — a tiny, very bright, fast-decaying bell up high; a high sparkle.
+// pure feed into both the dry bus and (softly) the reverb tail for shimmer.
+static void droplet(double note, double t, double g, double pan) {
+    bell(busL, busR, note, t, 0.55, g, pan, 5.0, 16.0);
+    bell(revL, revR, note, t, 0.55, g * 0.5, 0, 5.0, 16.0);
+}
+
+// soft sine drone — pad / sub bed with a slow raised-cosine attack/release.
+static void softsine(float *L, float *R, double note, double t, double dur, double g, double pan) {
+    double f = midi_hz(note); long n = (long)(dur * SR), s0 = (long)(t * SR);
+    long att = (long)(0.30 * SR), rel = (long)(0.45 * SR); double ph = 0, lg = 1 - pan * 0.5, rg = 1 + pan * 0.5;
+    for (long i = 0; i < n; i++) {
+        ph += TAU * f / SR;
+        double env = 1; if (i < att) env = (double)i / att; else if (i > n - rel) env = fmax(0, (double)(n - i) / rel);
+        double v = (sin(ph) + 0.16 * sin(ph * 2) + 0.06 * sin(ph * 3)) * env * g;
+        adds(L, R, s0 + i, v * lg, v * rg);
+    }
+}
+
+// a 4-voice sine pad chord (slightly panned for width), with a soft reverb send.
+static void pad_chord(double t, const int *midis, int nm, double dur, double g) {
+    for (int k = 0; k < nm; k++) { double pan = (k / fmax(1, nm - 1) - 0.5) * 0.6; softsine(busL, busR, midis[k], t, dur, g, pan); softsine(revL, revR, midis[k], t, dur, g * 0.4, 0); }
+}
+
+// ── harmony — F♯ major, a slow I–V–vi–IV loop (the "anthemic trance" cadence) ─
+// Phase music thrives on a small, static harmonic field; this loop turns very
+// slowly (one chord per phrase) so the ear hears mostly the shifting patterns.
+// per-phrase bass roots: F#, C#, D#m, B.
+static const int F_ROOTS[4] = { 54, 49, 51, 47 };      // F#3, C#3, D#3, B2
+// four 4-note pad voicings, one per chord in the loop.
+static const int I_PAD[4]  = { 42, 49, 54, 58 };       // F# maj  (F# C# F# A#)
+static const int V_PAD[4]  = { 37, 44, 49, 53 };       // C# maj  (C# G# C# F)
+static const int VI_PAD[4] = { 39, 46, 51, 54 };       // D# min  (D# A# D# F#)
+static const int IV_PAD[4] = { 35, 42, 47, 51 };       // B  maj  (B  F# B  D#)
+static const int *PADS[4] = { I_PAD, V_PAD, VI_PAD, IV_PAD };
+
+// F# major pentatonic (F# G# A# C# D#), spanning octaves — the spine of every
+// interlocking arpeggio. Indices wrap, so a coprime cycle-length vs 5 makes the
+// pattern walk through the scale and re-phase.
+static const int PENT[5]  = { 54, 56, 58, 61, 63 };    // F#3 G#3 A#3 C#4 D#4
+static const int PENTH[5] = { 66, 68, 70, 73, 75 };    // F#4 G#4 A#4 C#5 D#5
+// the high droplet palette (F#5 G#5 A#5 C#6 D#6 F#6).
+static const int DROPS[6] = { 78, 80, 82, 85, 87, 90 };
+
+// section map. SECBARS drives every loop bound below, so retuning the form
+// (or the whole length) is a one-line edit — at 116 BPM a bar is ~2.07s, so this
+// 56-bar form lands at ~122s. Keep section counts multiples of 4 so the 4-bar
+// pad/harmony phrases line up with the phasing cells.
+static const char *ORDER[8] = { "seed", "weave", "cellA", "thinA", "cellB", "cellC", "peak", "fade" };
+static const int SECBARS[8] = { 4, 4, 8, 4, 8, 8, 12, 8 };
+static int START[8];
+static int sec_index(const char *k) { for (int i = 0; i < 8; i++) if (!strcmp(ORDER[i], k)) return i; return 0; }
+
+// ── phasing engine ───────────────────────────────────────────────────────────
+// A "cell" is a looping arpeggio of `len` notes played on a steady 8th grid.
+// Two or more cells with coprime lengths (e.g. 6 and 7) drift against the bar,
+// re-aligning only after their LCM — the core Reich phasing effect. `voice`
+// picks the palette; `off` shifts a cell's start so two copies of the same cell
+// run a fixed distance apart (classic phase canon).
+static void cell(double tStart, double tEnd, const int *pal, int palN, int len, int off,
+                 double g, double pan, double ratio, double dec, int oct) {
+    // step every 8th note across the window
+    double step = BEAT / 2.0;
+    long k = 0;
+    for (double t = tStart; t < tEnd; t += step, k++) {
+        int idx = (int)((k + off) % len);
+        int note = pal[idx % palN] + (idx / palN) * 12 + oct;
+        // a soft amplitude shimmer following the pattern position so the cell
+        // "breathes" as it re-phases.
+        double sh = 0.78 + 0.22 * sin(TAU * (double)((k + off) % (len * 2)) / (len * 2));
+        bell(busL, busR, note, t, step * 1.9, g * sh, pan, ratio, dec);
+    }
+}
+
+int main(int argc, char **argv) {
+    const char *out_path = "out/lumitrax-raw.wav";
+    for (int i = 1; i < argc; i++) { if (!strcmp(argv[i], "--out") && i + 1 < argc) out_path = argv[++i]; else if (!strcmp(argv[i], "--bpm") && i + 1 < argc) BPMV = atof(argv[++i]); else if (!strcmp(argv[i], "--swing") && i + 1 < argc) SWING = atof(argv[++i]); }
+    BEAT = 60.0 / BPMV; BAR = BEAT * 4; SX = BEAT / 4;
+    { int c = 0; for (int i = 0; i < 8; i++) { START[i] = c; c += SECBARS[i]; } }
+    int TB = 0; for (int i = 0; i < 8; i++) TB += SECBARS[i];
+    double totalSec = TB * BAR + 6.0; N = (long)(totalSec * SR);
+    busL = calloc(N, 4); busR = calloc(N, 4); revL = calloc(N, 4); revR = calloc(N, 4);
+    fprintf(stderr, "# lumitrax.c · %g BPM · %d bars · %.1fs · F♯ major phasing bells\n", BPMV, TB, totalSec);
+
+    // the lead motif — a four-note rising cell in F# major pentatonic that the
+    // peak section foregrounds over the phasing wash, {phrase-bar, beat, note}.
+    double LEAD[8][3] = { {0,0,66},{0,2,68},{1,0,70},{1,2,73},{2,0,75},{2,2,73},{3,0,70},{3,1.5,68} };
+
+    // a per-bar pulsing pentatonic bass — the steady trance heartbeat that runs
+    // under (almost) every section so the pulse never stops.
+    #define PULSE(t0, root, g, wide) do { \
+        for (int e = 0; e < 8; e++) { double tt = (t0) + swing_beats(e * 0.5); int on = (e % 2 == 0); \
+            bell(busL, busR, (root) - 12, tt, BEAT * 0.45, on ? (g) : (g) * 0.5, on ? -0.06 : ((wide) ? 0.26 : 0.10), 2.0, on ? 12.0 : 15.0); } \
+        softsine(busL, busR, (root) - 12, (t0), BAR * 0.95, (g) * 0.9, 0); \
+    } while (0)
+
+    // ── SEED — one cell wakes, lone pulse, pad halo. The pattern stated plainly. ──
+    { int idx = sec_index("seed"); int c = START[idx], nb = SECBARS[idx]; double t0 = c * BAR;
+        pad_chord(t0, I_PAD, 4, BAR * nb - 0.05, 0.085);
+        for (int b = 0; b < nb; b++) { double tb = (c + b) * BAR; if (b >= 1) PULSE(tb, F_ROOTS[0], 0.075, 0); }
+        // a single 6-note cell, mid register, entering on bar 1
+        cell(t0 + BAR, t0 + BAR * nb, PENT, 5, 6, 0, 0.08, -0.18, 4.0, 4.5, 0);
+        // a lone droplet near the close as a promise of the sparkle to come
+        droplet(DROPS[2], t0 + BAR * (nb - 1) + 2.5 * BEAT, 0.045, 0.4);
+    }
+
+    // ── WEAVE — second cell joins (coprime 7-length), the phasing starts. ──
+    { int idx = sec_index("weave"); int c = START[idx], nb = SECBARS[idx]; double t0 = c * BAR;
+        pad_chord(t0, V_PAD, 4, BAR * nb - 0.05, 0.10);
+        for (int b = 0; b < nb; b++) { double tb = (c + b) * BAR; PULSE(tb, F_ROOTS[1], 0.085, 0); }
+        cell(t0, t0 + BAR * nb, PENT, 5, 6, 0, 0.075, -0.22, 4.0, 4.5, 0);          // cell 1
+        cell(t0, t0 + BAR * nb, PENTH, 5, 7, 2, 0.060, 0.24, 6.0, 6.0, 0);          // cell 2, brighter, drifts
+        // a rising pentatonic flourish into the first full cell section
+        for (int s = 0; s < 8; s++) bell(busL, busR, PENT[s % 5] + (s / 5) * 12, t0 + BAR * (nb - 1) + s * SX, SX * 3, 0.05 + 0.04 * s / 8.0, rnd2() * 0.4, 5.0, 8.0);
+    }
+
+    // ── the three "cell" sections — full interlocking phasing webs. ──
+    // cellA: two cells + canon copy. thinA strips back. cellB/cellC add a third
+    // high cell and droplets so the texture thickens as the chords turn.
+    const char *cells[3] = { "cellA", "cellB", "cellC" };
+    for (int d = 0; d < 3; d++) {
+        int wi = sec_index(cells[d]); int c = START[wi], nbw = SECBARS[wi]; int big = (d >= 1);
+        double t0 = c * BAR, t1 = (c + nbw) * BAR;
+        // harmony turns once per 4-bar phrase across this section
+        for (int p = 0; p * 4 < nbw; p++) {
+            double tp = t0 + p * 4 * BAR; const int *pad = PADS[(START[wi] / 4 + p) % 4];
+            pad_chord(tp, pad, 4, BAR * 4 - 0.05, big ? 0.085 : 0.07);
+        }
+        // the steady pulse, bass root follows the phrase chord
+        for (int b = 0; b < nbw; b++) { double tb = (c + b) * BAR; int root = F_ROOTS[((START[wi] / 4) + (b / 4)) % 4]; PULSE(tb, root, big ? 0.085 : 0.075, b % 2); }
+        // cell 1 — the foundation arpeggio (6-cell, mid)
+        cell(t0, t1, PENT, 5, 6, 0, 0.072, -0.24, 4.0, 4.5, 0);
+        // cell 2 — canon copy of cell 1, offset by 3 steps and panned opposite:
+        // two identical patterns sliding past each other (true phase canon).
+        cell(t0, t1, PENT, 5, 6, 3, 0.058, 0.24, 4.0, 5.0, 0);
+        // cell 3 — a coprime 7-cell up an octave, the shimmering high lattice
+        cell(t0, t1, PENTH, 5, 7, big ? 1 : 4, big ? 0.058 : 0.045, big ? -0.30 : 0.30, 6.0, 6.5, 0);
+        if (big) {
+            // cell 4 — a 5-cell (aligns with the scale) way up top for sparkle,
+            // entering only on the thicker sections
+            cell(t0, t1, DROPS, 6, 5, 0, 0.030, 0.0, 5.0, 9.0, 0);
+            // scattered droplets riding the grid
+            for (int b = 0; b < nbw; b++) if (rnd() < 0.5) droplet(DROPS[(int)(rnd() * 6)], (c + b) * BAR + swing_beats((int)(rnd() * 8) * 0.5), 0.04, rnd2() * 0.7);
+            // a soft choir-ish sine bed for depth on the biggest cell section
+            if (d == 2) for (int b = 0; b < nbw; b += 2) { double tb = (c + b) * BAR; int ns[3] = { I_PAD[1], I_PAD[2], I_PAD[3] }; for (int z = 0; z < 3; z++) softsine(revL, revR, ns[z] + 12, tb, BAR * 2, 0.035, (z - 1) * 0.4); }
+        }
+    }
+
+    // ── THIN — a clearing: pulse + one bare cell + lone droplets. Breath. ──
+    { int idx = sec_index("thinA"); int c = START[idx], nb = SECBARS[idx]; double t0 = c * BAR;
+        pad_chord(t0, VI_PAD, 4, BAR * nb - 0.05, 0.10);
+        for (int b = 0; b < nb; b++) { double tb = (c + b) * BAR; PULSE(tb, F_ROOTS[2], 0.07, 0); }
+        cell(t0, t0 + BAR * nb, PENT, 5, 6, 0, 0.075, 0.0, 4.0, 4.5, 0);
+        for (int b = 0; b < nb; b++) if (rnd() < 0.6) droplet(DROPS[(int)(rnd() * 6)], t0 + b * BAR + 2.5 * BEAT, 0.04, rnd2() * 0.7);
+        // a descending run that hands off into cellB
+        for (int s = 0; s < 8; s++) bell(busL, busR, PENTH[(4 - s % 5 + 5) % 5] + 12 - (s / 5) * 12, t0 + BAR * (nb - 1) + s * SX, SX * 3, 0.045 + 0.03 * (8 - s) / 8.0, rnd2() * 0.4, 5.0, 8.0);
+    }
+
+    // ── PEAK — the lead motif rides above the full phasing web; everything on. ──
+    { int idx = sec_index("peak"); int c = START[idx], nb = SECBARS[idx]; double t0 = c * BAR, t1 = (c + nb) * BAR;
+        for (int p = 0; p * 4 < nb; p++) { double tp = t0 + p * 4 * BAR; pad_chord(tp, PADS[p % 4], 4, BAR * 4 - 0.05, 0.09); }
+        for (int b = 0; b < nb; b++) { double tb = (c + b) * BAR; int root = F_ROOTS[(b / 4) % 4]; PULSE(tb, root, 0.09, b % 2); }
+        // the full phase lattice
+        cell(t0, t1, PENT, 5, 6, 0, 0.070, -0.26, 4.0, 4.5, 0);
+        cell(t0, t1, PENT, 5, 6, 3, 0.056, 0.26, 4.0, 5.0, 0);
+        cell(t0, t1, PENTH, 5, 7, 1, 0.058, -0.30, 6.0, 6.5, 0);
+        cell(t0, t1, DROPS, 6, 5, 2, 0.030, 0.30, 5.0, 9.0, 0);
+        // the bright lead motif, one 4-bar phrase repeated, frilled on highs
+        for (int b = 0; b < nb; b++) {
+            int ph = b % 4; double tb = (c + b) * BAR;
+            for (int z = 0; z < 8; z++) if ((int)LEAD[z][0] == ph) {
+                double note = LEAD[z][2], tt = tb + swing_beats(LEAD[z][1]);
+                bell(busL, busR, note, tt, BEAT * 0.9, 0.11, rnd2() * 0.3, 6.0, 6.0);
+                bell(revL, revR, note, tt, BEAT * 0.9, 0.05, 0, 6.0, 6.0);
+                if (note >= 73) for (int q = 0; q < 3; q++) bell(busL, busR, note + q * 2, tt + 0.04 + 0.05 * q, BEAT * 0.5, 0.04 * (1.0 - 0.3 * q), rnd2() * 0.5, 5.0, 11.0);
+            }
+        }
+    }
+
+    // ── FADE — voices subtract one by one; pulse thins, one cell lingers, pad wash. ──
+    { int idx = sec_index("fade"); int c = START[idx], nb = SECBARS[idx], h = nb / 2; double t0 = c * BAR, t1 = (c + nb) * BAR;
+        pad_chord(t0, I_PAD, 4, BAR * h - 0.05, 0.10);
+        pad_chord(t0 + BAR * h, IV_PAD, 4, BAR * (nb - h) - 0.05, 0.085);
+        for (int b = 0; b < nb; b++) { double tb = (c + b) * BAR; double e = fmax(0.12, 1.0 - (double)b / nb);
+            // pulse fades and decimates toward silence
+            if (rnd() < 0.4 + 0.6 * e) PULSE(tb, b < h ? F_ROOTS[0] : F_ROOTS[3], 0.075 * e, 0); }
+        // the foundation cell lingers but fades across the section (manual ramp)
+        for (int b = 0; b < nb; b++) { double tb = (c + b) * BAR; double e = fmax(0.0, 1.0 - (double)b / (nb - 1));
+            cell(tb, tb + BAR, PENT, 5, 6, (b * 8) % 6, 0.075 * e, (b % 2 ? 0.2 : -0.2), 4.0, 4.5, 0); }
+        // the high 7-cell drops out at the midpoint (subtraction)
+        cell(t0, t0 + BAR * h, PENTH, 5, 7, 1, 0.050, 0.28, 6.0, 6.5, 0);
+        // a final low bell + high droplet to close the loop
+        bell(busL, busR, 42, t1 - BAR * 2, 4.5, 0.17, 0, 2.0, 1.1);
+        bell(busL, busR, 78, t1 - BAR * 2, 4.5, 0.09, 0.2, 6.0, 1.4);
+        bell(revL, revR, 66, t1 - BAR * 2, 4.5, 0.09, 0, 5.0, 1.3);
+    }
+
+    // ── REVERB (Schroeder) — wide and shimmery to glue the lattice into a wash ──
+    {
+        double decay = 0.85, wet = 0.50, damp = 0.30;
+        int CD[6]; double cds[6] = { 0.0297, 0.0371, 0.0411, 0.0437, 0.0497, 0.0581 };
+        for (int k = 0; k < 6; k++) CD[k] = (int)(cds[k] * SR);
+        int AD[2] = { (int)(0.005 * SR), (int)(0.0017 * SR) }; double apFb = 0.5;
+        float *cbL[6], *cbR[6]; int ciL[6] = {0}, ciR[6] = {0}; double cLPL[6] = {0}, cLPR[6] = {0};
+        for (int k = 0; k < 6; k++) { cbL[k] = calloc(CD[k], 4); cbR[k] = calloc(CD[k], 4); }
+        float *abL[2], *abR[2]; int aiL[2] = {0}, aiR[2] = {0};
+        for (int k = 0; k < 2; k++) { abL[k] = calloc(AD[k], 4); abR[k] = calloc(AD[k], 4); }
+        for (long i = 0; i < N; i++) {
+            double inL = revL[i], inR = revR[i], cL = 0, cR = 0;
+            for (int k = 0; k < 6; k++) {
+                double dL = cbL[k][ciL[k]], dR = cbR[k][ciR[k]]; cL += dL; cR += dR;
+                cLPL[k] = dL * (1 - damp) + cLPL[k] * damp; cLPR[k] = dR * (1 - damp) + cLPR[k] * damp;
+                cbL[k][ciL[k]] = (float)(inL + cLPL[k] * decay); cbR[k][ciR[k]] = (float)(inR + cLPR[k] * decay);
+                ciL[k] = (ciL[k] + 1) % CD[k]; ciR[k] = (ciR[k] + 1) % CD[k];
+            }
+            cL /= 6; cR /= 6;
+            for (int k = 0; k < 2; k++) {
+                double dL = abL[k][aiL[k]], dR = abR[k][aiR[k]];
+                double oL = -apFb * cL + dL, oR = -apFb * cR + dR;
+                abL[k][aiL[k]] = (float)(cL + apFb * oL); abR[k][aiR[k]] = (float)(cR + apFb * oR);
+                aiL[k] = (aiL[k] + 1) % AD[k]; aiR[k] = (aiR[k] + 1) % AD[k];
+                cL = oL; cR = oR;
+            }
+            busL[i] += (float)(cL * wet); busR[i] += (float)(cR * wet);
+        }
+        for (int k = 0; k < 6; k++) { free(cbL[k]); free(cbR[k]); }
+        for (int k = 0; k < 2; k++) { free(abL[k]); free(abR[k]); }
+    }
+
+    // ── normalize + gentle in/out fades ──
+    double peak = 0; for (long i = 0; i < N; i++) { double a = fmax(fabs(busL[i]), fabs(busR[i])); if (a > peak) peak = a; }
+    if (peak > 0) { double g = 0.85 / peak; for (long i = 0; i < N; i++) { busL[i] *= (float)g; busR[i] *= (float)g; } }
+    long fin = (long)(2.0 * SR), fout = (long)(4.5 * SR);
+    for (long i = 0; i < fin && i < N; i++) { double g = 0.5 - 0.5 * cos(M_PI * (double)i / fin); busL[i] *= (float)g; busR[i] *= (float)g; }
+    for (long i = 0; i < fout && i < N; i++) { double g = 0.5 - 0.5 * cos(M_PI * (double)i / fout); long idx = N - 1 - i; busL[idx] *= (float)g; busR[idx] *= (float)g; }
+
+    if (!write_wav_f32_stereo(out_path, busL, busR, N)) { fprintf(stderr, "✗ write failed\n"); return 1; }
+    fprintf(stderr, "✓ %s · %.1fs\n", out_path, (double)N / SR);
+    return 0;
+}
diff --git a/pop/maytrax/c/maytrax b/pop/maytrax/c/maytrax
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diff --git a/pop/maytrax/c/maytrax.c b/pop/maytrax/c/maytrax.c
new file mode 100644
index 000000000..d32044c5e
--- /dev/null
+++ b/pop/maytrax/c/maytrax.c
@@ -0,0 +1,937 @@
+// maytrax.c — C engine for the maytrax track (americomputadora/hellsine
+// pattern): JS bakes c/score.h (the freesound sample roster + drop shouts),
+// this renders the full stereo song to a float32 WAV; render-c.mjs runs the
+// ffmpeg pop-master (loudnorm + alimiter) and encodes the mp3.
+//
+// Faithful port of bin/maytrax.mjs (160 BPM big-beat techno, jungle mode):
+// sample-driven kit + pitched one-shots over the F-minor note data, Schroeder
+// reverb, kick sidechain, crunch + state-variable filter sweep, healing
+// drone, sine-tinge droplets, payphone intro, tape-stop ending, phone-world
+// loop tail. The drums are the TAMED breakbeat: a steady kick/snare anchor
+// with no ghost snares and almost no swing/jitter (the JS scatter read as
+// "wild / skippy"). Synth bodies stay as fallbacks if a sample is missing.
+//
+// Build:  ./build.sh        Run:  ./maytrax --out out/c-raw.wav
+
+#define _POSIX_C_SOURCE 200809L
+#include <stdio.h>
+#include <stdlib.h>
+#include <stdint.h>
+#include <string.h>
+#include <math.h>
+
+#ifndef M_PI
+#define M_PI 3.14159265358979323846
+#endif
+#define TAU (2.0 * M_PI)
+
+#include "score.h"
+
+static const int SR = 48000;
+static double BPMV = SCORE_BPM, BEAT, BAR, SX;
+
+// tamed-feel globals — the JS defaults were DEC .65 / LAZY .45 / HUMAN .4;
+// the breakbeat read as "wild / skippy", so the drag + micro-timing jitter
+// are pulled WAY down here (the break pattern itself is anchored below).
+static const double DEC = 0.65;
+static double LAZY = 0.22;
+static double HUMAN = 0.15;
+static int g_payphone = 0; // lo-fi telephone intro/loop — off by default (clean start)
+
+// ── deterministic RNG (xorshift32) — reproducible "humanize" + scatter ──
+static uint32_t rng_s = 0x6d617978; // "mayx"
+static inline double rnd(void) {
+    rng_s ^= rng_s << 13; rng_s ^= rng_s >> 17; rng_s ^= rng_s << 5;
+    return (double)rng_s / 4294967296.0;
+}
+static inline double rnd2(void) { return rnd() * 2.0 - 1.0; }
+static inline double hz(void) { return rnd2() * 0.004 * HUMAN; }
+
+static inline double midi_hz(double m) { return 440.0 * pow(2.0, (m - 69.0) / 12.0); }
+
+// ── buses ───────────────────────────────────────────────────────────────
+// busL/busR — the ducked music bus.  drm — dry kicks/snares (bypass duck,
+// center).  revL/revR — reverb send.  vocL/vocR — un-ducked shout bus.
+static long N;
+static float *busL, *busR, *drm, *revL, *revR, *vocL, *vocR;
+
+static inline void addb(float *b, long i, double v) { if (i >= 0 && i < N) b[i] += (float)v; }
+static inline void adds(float *L, float *R, long i, double l, double r) {
+    if (i >= 0 && i < N) { L[i] += (float)l; R[i] += (float)r; }
+}
+
+// ── wav io ──────────────────────────────────────────────────────────────
+// reads PCM16 / PCM24 / float32, mono or stereo → mono float at native SR.
+// trims leading near-silence (<0.005) so one-shots start on the transient.
+typedef struct { float *s; long n; int sr; int det; int nom; int ok; } Smp;
+
+static float *load_wav(const char *path, long *out_n, int *out_sr) {
+    FILE *f = fopen(path, "rb");
+    if (!f) { fprintf(stderr, "  ! missing %s\n", path); return NULL; }
+    uint8_t hdr[12];
+    if (fread(hdr, 1, 12, f) != 12 || memcmp(hdr, "RIFF", 4) || memcmp(hdr + 8, "WAVE", 4)) { fclose(f); return NULL; }
+    uint16_t fmt = 1, ch = 1, bits = 16; uint32_t sr = 44100;
+    float *out = NULL; long n = 0;
+    for (;;) {
+        uint8_t ck[8];
+        if (fread(ck, 1, 8, f) != 8) break;
+        uint32_t sz = ck[4] | (ck[5] << 8) | (ck[6] << 16) | ((uint32_t)ck[7] << 24);
+        if (!memcmp(ck, "fmt ", 4)) {
+            uint8_t b[40]; uint32_t rd = sz < 40 ? sz : 40; fread(b, 1, rd, f);
+            fmt = b[0] | (b[1] << 8); ch = b[2] | (b[3] << 8);
+            sr = b[4] | (b[5] << 8) | (b[6] << 16) | ((uint32_t)b[7] << 24);
+            bits = b[14] | (b[15] << 8);
+            if (sz > rd) fseek(f, sz - rd, SEEK_CUR);
+        } else if (!memcmp(ck, "data", 4)) {
+            long frames = sz / (bits / 8) / ch;
+            out = malloc(sizeof(float) * (frames > 0 ? frames : 1)); n = frames;
+            for (long i = 0; i < frames; i++) {
+                double acc = 0;
+                for (int c = 0; c < ch; c++) {
+                    if (fmt == 3 && bits == 32) { float v; fread(&v, 4, 1, f); acc += v; }
+                    else if (bits == 24) { uint8_t p3[3]; fread(p3, 1, 3, f); int s = p3[0] | (p3[1] << 8) | (p3[2] << 16); if (s & 0x800000) s |= ~0xffffff; acc += s / 8388608.0; }
+                    else { int16_t v; fread(&v, 2, 1, f); acc += v / 32768.0; }
+                }
+                out[i] = (float)(acc / ch);
+            }
+            break;
+        } else fseek(f, sz + (sz & 1), SEEK_CUR);
+    }
+    fclose(f);
+    // trim leading silence
+    long lead = 0; while (lead < n && fabs(out[lead]) < 0.005) lead++;
+    if (lead > 0 && lead < n) { memmove(out, out + lead, sizeof(float) * (n - lead)); n -= lead; }
+    *out_n = n; *out_sr = (int)sr;
+    return out;
+}
+
+// f0 via autocorrelation around the peak (port of detectF0) → smpNote root.
+static double detect_f0(const float *s, long n, int sr) {
+    double pk = 0; long pidx = 0;
+    for (long i = 0; i < n; i++) { double a = fabs(s[i]); if (a > pk) { pk = a; pidx = i; } }
+    long w = n < 8192 ? n : 8192, st = pidx - (w >> 1);
+    if (st < 0) st = 0; if (st > n - w) st = n - w; if (st < 0) st = 0;
+    long minLag = sr / 1200, maxLag = sr / 45;
+    double best = -1; long bestLag = 0;
+    for (long lag = minLag; lag <= maxLag; lag++) {
+        double sum = 0; for (long i = 0; i + lag < w; i++) sum += s[st + i] * s[st + i + lag];
+        if (sum > best) { best = sum; bestLag = lag; }
+    }
+    return bestLag > 0 ? (double)sr / bestLag : 0;
+}
+
+static int write_wav_f32_stereo(const char *path, const float *L, const float *R, long n) {
+    FILE *f = fopen(path, "wb"); if (!f) return 0;
+    uint32_t dsz = (uint32_t)(n * 8), riff = 36 + dsz, sr = SR, br = SR * 8;
+    uint16_t fmt = 3, ch = 2, ba = 8, bits = 32, fsz = 16;
+    uint32_t fsz32 = 16;
+    fwrite("RIFF", 1, 4, f); fwrite(&riff, 4, 1, f); fwrite("WAVE", 1, 4, f);
+    fwrite("fmt ", 1, 4, f); fwrite(&fsz32, 4, 1, f);
+    fwrite(&fmt, 2, 1, f); fwrite(&ch, 2, 1, f); fwrite(&sr, 4, 1, f);
+    fwrite(&br, 4, 1, f); fwrite(&ba, 2, 1, f); fwrite(&bits, 2, 1, f);
+    fwrite("data", 1, 4, f); fwrite(&dsz, 4, 1, f);
+    (void)fsz;
+    for (long i = 0; i < n; i++) { fwrite(&L[i], 4, 1, f); fwrite(&R[i], 4, 1, f); }
+    fclose(f); return 1;
+}
+
+// ── sample roster ─────────────────────────────────────────────────────────
+static Smp samp[N_ROLES];
+static Smp wolf_rev, animal_rev; // reversed risers
+
+static Smp *smpl(const char *name) {
+    if (!strcmp(name, "wolf_rev")) return wolf_rev.ok ? &wolf_rev : NULL;
+    if (!strcmp(name, "animal_rev")) return animal_rev.ok ? &animal_rev : NULL;
+    for (int i = 0; i < N_ROLES; i++) if (!strcmp(ROLE_NAME[i], name)) return samp[i].ok ? &samp[i] : NULL;
+    return NULL;
+}
+
+static void load_roster(void) {
+    for (int i = 0; i < N_ROLES; i++) {
+        long n; int sr; float *s = load_wav(ROLE_PATH[i], &n, &sr);
+        if (!s || n <= 0) { samp[i].ok = 0; continue; }
+        samp[i] = (Smp){ s, n, sr, 60, ROLE_NOMINAL[i], 1 };
+        if (ROLE_PITCHED[i]) {
+            double f = detect_f0(s, n, sr);
+            samp[i].det = (f > 30 && f < 2000) ? (int)lround(69 + 12 * log2(f / 440.0)) : (ROLE_NOMINAL[i] < 0 ? 60 : ROLE_NOMINAL[i]);
+        }
+    }
+    Smp *w = smpl("wolf"), *a = smpl("animal");
+    if (w) { wolf_rev = *w; wolf_rev.s = malloc(sizeof(float) * w->n); for (long i = 0; i < w->n; i++) wolf_rev.s[i] = w->s[w->n - 1 - i]; wolf_rev.ok = 1; }
+    if (a) { animal_rev = *a; animal_rev.s = malloc(sizeof(float) * a->n); for (long i = 0; i < a->n; i++) animal_rev.s[i] = a->s[a->n - 1 - i]; animal_rev.ok = 1; }
+}
+
+// ── sample players ────────────────────────────────────────────────────────
+// stereo placement (playSampleStereo): pan via gain + light haas when pan>0.
+// `attack` (seconds) eases the onset in so a one-shot swells rather than
+// slams — used to de-claw the roars/gong/screams so they aren't violent.
+static void place_a(float *L, float *R, Smp *s, double t, double gain, double rate, double pan, double maxDur, double attack) {
+    if (!s) return;
+    long s0 = (long)(t * SR);
+    double step = ((double)s->sr / SR) * rate;
+    double lg = gain * (1 - pan * 0.5), rg = gain * (1 + pan * 0.5);
+    long haas = pan > 0 ? (long)(0.012 * SR) : 0;
+    long outMax = maxDur >= 1e8 ? (long)1e18 : (long)(maxDur * SR);
+    long relN = (long)(0.02 * SR), attN = (long)(attack * SR);
+    for (long i = 0; s0 + i < N; i++) {
+        double p = i * step; long j = (long)p;
+        if (j >= s->n - 1 || i >= outMax) break;
+        double f = p - j, v = s->s[j] * (1 - f) + s->s[j + 1] * f;
+        if (attN > 0 && i < attN) v *= 0.5 - 0.5 * cos(M_PI * (double)i / attN); // raised-cosine swell
+        if (outMax < (long)1e17 && i > outMax - relN) v *= (double)(outMax - i) / relN;
+        adds(L, R, s0 + i, v * lg, 0);
+        if (haas > 0) adds(L, R, s0 + i + haas, 0, v * rg); else adds(L, R, s0 + i, 0, v * rg);
+    }
+}
+static void place(float *L, float *R, Smp *s, double t, double gain, double rate, double pan, double maxDur) {
+    place_a(L, R, s, t, gain, rate, pan, maxDur, 0);
+}
+
+// mono placement (smpMono). returns 1 if the sample existed.
+static int mono(float *buf, Smp *s, double t, double gain, double rate, double maxDur) {
+    if (!s) return 0;
+    long s0 = (long)(t * SR);
+    double step = ((double)s->sr / SR) * rate;
+    long outMax = maxDur >= 1e8 ? (long)1e18 : (long)(maxDur * SR);
+    long relN = (long)(0.02 * SR);
+    long i = 0;
+    for (double p = 0; p < s->n - 1 && i < outMax; i++, p += step) {
+        long idx = (long)p; double fr = p - idx;
+        double v = (s->s[idx] * (1 - fr) + s->s[idx + 1] * fr) * gain;
+        if (outMax < (long)1e17 && i > outMax - relN) v *= (double)(outMax - i) / relN;
+        addb(buf, s0 + i, v);
+    }
+    return 1;
+}
+static int mono_note(float *buf, Smp *s, double note, double t, double gain, double maxDur) {
+    if (!s) return 0;
+    return mono(buf, s, t, gain, pow(2.0, (note - s->det) / 12.0), maxDur);
+}
+static inline double rate_nom(Smp *s, double note) { return pow(2.0, (note - s->nom) / 12.0); }
+
+// ── synth voices (active: the rest fall back to samples) ──────────────────
+static void square_note(float *L, float *R, double midi, double t, double dur, double g, double pan) {
+    double f = midi_hz(midi); long n = (long)(dur * SR), s0 = (long)(t * SR);
+    double lg = g * (1 - pan * 0.5), rg = g * (1 + pan * 0.5);
+    long atk = (long)(0.004 * SR), rel = (long)(0.04 * SR);
+    for (long i = 0; i < n; i++) {
+        double tt = (double)i / SR;
+        double pw = 0.5 + 0.06 * sin(TAU * 5 * tt);
+        double ph = fmod(f * tt, 1.0), ph2 = fmod(f * 1.003 * tt, 1.0);
+        double s = (ph < pw ? 1 : -1) * 0.6 + (ph2 < 0.5 ? 1 : -1) * 0.4;
+        double env = 1; if (i < atk) env = (double)i / atk; else if (i > n - rel) env = fmax(0, (double)(n - i) / rel);
+        adds(L, R, s0 + i, s * env * lg, s * env * rg);
+    }
+}
+
+static void riser(float *L, float *R, double t0, double dur, double g) {
+    long n = (long)(dur * SR), s0 = (long)(t0 * SR);
+    double prev = 0, ph = 0;
+    for (long i = 0; i < n; i++) {
+        double w = (double)i / n;
+        double cutoff = 800 + (8000 - 800) * w;
+        double a = exp(-1.0 / (SR / cutoff));
+        double nz = rnd2(); double filt = nz - prev * a; prev = nz;
+        double f = 80 + (1200 - 80) * w * w;
+        ph += TAU * f / SR;
+        double sine = sin(ph) * 0.5, env = w * w;
+        double v = (filt * 0.6 + sine * 0.4) * env * g, spread = w * 0.6;
+        adds(L, R, s0 + i, v * (1 - spread), v * (1 + spread));
+    }
+}
+
+static void reverse_swell(float *L, float *R, double t0, double dur, double g) {
+    long n = (long)(dur * SR), s0 = (long)(t0 * SR);
+    double lpL = 0, lpR = 0;
+    for (long i = 0; i < n; i++) {
+        double w = (double)i / n, cutoff = 200 + (6000 - 200) * w;
+        double a = 1 - exp(-TAU * cutoff / SR);
+        lpL += a * (rnd2() - lpL); lpR += a * (rnd2() - lpR);
+        double env = w * w;
+        adds(L, R, s0 + i, lpL * env * g, lpR * env * g);
+    }
+}
+
+// ── drum voices (sample-backed; synth bodies are the fallbacks) ───────────
+static void kick909(float *buf, double t, double g) {
+    if (mono(buf, smpl("kick"), t, g * 0.9, 1, 0.20 * DEC)) {
+        long n = (long)(0.20 * SR), s0 = (long)(t * SR); double ph = 0;
+        for (long i = 0; i < n; i++) {
+            double tt = (double)i / SR, f = 110 * exp(-tt * 26) + 40;
+            ph += TAU * f / SR;
+            addb(buf, s0 + i, tanh(sin(ph) * 1.3) * exp(-tt * 6.5) * 0.72 * g);
+        }
+        return;
+    }
+    long n = (long)(0.28 * SR), s0 = (long)(t * SR); double ph = 0, sub = 0;
+    for (long i = 0; i < n; i++) {
+        double tt = (double)i / SR, f = 52 + (165 - 52) * exp(-tt * 50);
+        ph += TAU * f / SR; double body = sin(ph) * exp(-tt * 11);
+        sub += TAU * 38 / SR; double subL = sin(sub) * exp(-tt * 5) * 0.55;
+        double click = i < SR * 0.003 ? rnd2() * 0.9 * (1 - i / (SR * 0.003)) : 0;
+        addb(buf, s0 + i, tanh((body + click) * 2.2) * g + subL * g * 0.7);
+    }
+}
+static void snare_brk(float *buf, double t, double g) {
+    if (mono(buf, smpl("snare"), t, g * 0.95, 1, 0.18 * DEC)) return;
+    long n = (long)(0.18 * SR), s0 = (long)(t * SR); double prev = 0, ph = 0;
+    for (long i = 0; i < n; i++) {
+        double tt = (double)i / SR, nz = rnd2(), hp = nz - prev * 0.62; prev = nz;
+        ph += TAU * 195 / SR;
+        double body = sin(ph) * exp(-tt * 28) * 0.55, tail = hp * exp(-tt * 18);
+        addb(buf, s0 + i, (body + tail) * g);
+    }
+}
+static void hat_mono(float *buf, double t, double g) {
+    if (mono(buf, smpl("hat"), t, g * 1.4, 1, 0.05 * DEC)) return;
+    long n = (long)(0.045 * SR), s0 = (long)(t * SR); double prev = 0;
+    for (long i = 0; i < n; i++) { double tt = (double)i / SR, nz = rnd2(), hp = nz - prev * 0.78; prev = nz; addb(buf, s0 + i, hp * exp(-tt * 90) * g); }
+}
+static void ohat_mono(float *buf, double t, double g) {
+    if (mono(buf, smpl("ohat"), t, g * 1.3, 1, 0.13 * DEC)) return;
+    long n = (long)(0.22 * SR), s0 = (long)(t * SR); double prev = 0;
+    for (long i = 0; i < n; i++) { double tt = (double)i / SR, nz = rnd2(), hp = nz - prev * 0.82; prev = nz; addb(buf, s0 + i, hp * exp(-tt * 14) * g); }
+}
+static void shaker_mono(float *buf, double t, double g) {
+    if (mono(buf, smpl("shaker"), t, g * 1.6, 1, 0.06 * DEC)) return;
+    long n = (long)(0.09 * SR), s0 = (long)(t * SR); double prev = 0, prev2 = 0;
+    for (long i = 0; i < n; i++) {
+        double tt = (double)i / SR, nz = rnd2(), hp = nz - prev * 0.86; prev = nz;
+        double hp2 = hp - prev2 * 0.4; prev2 = hp;
+        double att = fmin(1, tt / 0.003);
+        addb(buf, s0 + i, hp2 * att * exp(-tt * 52) * g);
+    }
+}
+
+// place a mono hat once and pan it into the stereo bus (tightHatStereo).
+static void tight_hat(float *L, float *R, double t, int open, double g, double pan) {
+    double dur = open ? 0.22 : 0.045; long ln = (long)(dur * SR) + 4;
+    float *tmp = calloc(ln, sizeof(float));
+    if (open) ohat_mono(tmp, 0, g); else hat_mono(tmp, 0, g);
+    long s0 = (long)(t * SR); double lg = 1 - pan * 0.5, rg = 1 + pan * 0.5;
+    for (long i = 0; i < ln; i++) { long d = s0 + i; if (d < 0 || d >= N) continue; double v = tmp[i]; L[d] += (float)(v * lg); R[d] += (float)(v * rg); }
+    free(tmp);
+}
+
+// ── TAMED breakbeat ────────────────────────────────────────────────────────
+// the JS breakBar cycled four funky-drummer variations with scattered kicks,
+// sprinkled ghost snares, per-offbeat swing, whole-kit drag and random gains
+// — that stack read as "wild / skippy / not flowy". Here: a steady kick on
+// 1 + the classic "& of 3" push (and a 6-push on the alt bar), a FIRM 2 & 4
+// backbeat (no ghosts), continuous closed hats on every offbeat with open
+// lifts on the &s (fills the gaps → flow), and almost no swing/jitter.
+static void break_bar(float *L, float *R, float *dr, double t0, double energy, double hatPan) {
+    static const int KV[2][16] = {
+        { 1,0,0,1, 0,0,0,0, 0,0,1,0, 0,0,0,0 },   // 1 · & of 1 · & of 3
+        { 1,0,0,0, 0,0,1,0, 0,0,1,0, 0,0,0,0 },   // 1 · & of 2 · & of 3
+    };
+    static const int SV[16] = { 0,0,0,0, 1,0,0,0, 0,0,0,0, 1,0,0,0 }; // firm 2 & 4
+    static const char HP[16] = { 'h','h','h','H','h','h','h','h','h','H','h','h','h','h','H','h' };
+    int vi = ((int)llround(t0 / BAR) / 4) & 1;
+    const int *kP = KV[vi];
+    double drag = 0.006 * LAZY;
+    for (int e = 0; e < 16; e++) {
+        double t = t0 + e * SX;
+        if (kP[e]) kick909(dr, t + drag * 0.4, 1.18 * energy);
+        if (SV[e]) snare_brk(dr, t + drag, 0.84 * energy);
+        double pan = (e % 2 == 0 ? -1 : 1) * hatPan, th = t + drag;
+        if (HP[e] == 'h') tight_hat(L, R, th, 0, 0.11 * energy, pan);
+        else tight_hat(L, R, th, 1, 0.13 * energy, pan);
+    }
+}
+
+// sunk-in swung-16th shaker groove + open-hat lifts → reverb (percGroove).
+static void perc_groove(float *bL, float *bR, float *rL, float *rR, double t0, double energy, double swing, double base, double revSend) {
+    long shLen = (long)(0.09 * SR) + 4, ohLen = (long)(0.22 * SR) + 4;
+    float *tmp = calloc(ohLen, sizeof(float));
+    for (int e = 0; e < 16; e++) {
+        double t = t0 + e * SX + (e % 2 == 1 ? swing : 0);
+        long s0 = (long)(t * SR);
+        int accent = e % 4 == 2;
+        double jitter = 0.75 + 0.25 * (((e * 7) % 5) / 4.0);
+        double g = (accent ? base * 1.5 : base) * energy * jitter;
+        double pan = (e % 2 == 0 ? -1 : 1) * 0.28;
+        memset(tmp, 0, sizeof(float) * shLen);
+        shaker_mono(tmp, 0, g);
+        double lg = 1 - pan * 0.5, rg = 1 + pan * 0.5;
+        for (long i = 0; i < shLen; i++) { double v = tmp[i]; if (!v) continue; long d = s0 + i; if (d < 0 || d >= N) continue; bL[d] += (float)(v * lg); bR[d] += (float)(v * rg); rL[d] += (float)(v * lg * revSend); rR[d] += (float)(v * rg * revSend); }
+        if (e == 6 || e == 14) {
+            memset(tmp, 0, sizeof(float) * ohLen);
+            ohat_mono(tmp, 0, 0.085 * energy);
+            double op = (e == 6 ? -1 : 1) * 0.22, olg = 1 - op * 0.5, org = 1 + op * 0.5;
+            for (long i = 0; i < ohLen; i++) { double v = tmp[i]; if (!v) continue; long d = s0 + i; if (d < 0 || d >= N) continue; bL[d] += (float)(v * olg); bR[d] += (float)(v * org); rL[d] += (float)(v * olg * 0.5); rR[d] += (float)(v * org * 0.5); }
+        }
+    }
+    free(tmp);
+}
+
+// ── pitched bed voices (sample-backed) ────────────────────────────────────
+static void sub_bass(float *buf, double t, double midi, double dur, double g) {
+    if (mono_note(buf, smpl("sub"), midi, t, g * 1.1, dur)) return;
+    double f = midi_hz(midi); long n = (long)(dur * SR), s0 = (long)(t * SR);
+    long att = (long)(0.012 * SR), rel = (long)(0.08 * SR); double ph = 0;
+    for (long i = 0; i < n; i++) {
+        ph += TAU * f / SR; double env = 1;
+        if (i < att) env = (double)i / att; else if (i > n - rel) env = fmax(0, (double)(n - i) / rel);
+        double s = sin(ph) + sin(ph * 2) * 0.12;
+        addb(buf, s0 + i, tanh(s * 1.05) * env * g);
+    }
+}
+static void dark_pad(float *L, float *R, double t, const int *midis, int nm, double dur, double g) {
+    Smp *pad = smpl("pad");
+    if (pad) { for (int k = 0; k < nm; k++) place(L, R, pad, t, g * 0.6, pow(2.0, (midis[k] - pad->det) / 12.0), (k / fmax(1, nm - 1) - 0.5) * 0.6, 1e9); return; }
+    (void)dur;
+}
+static void acid303(float *buf, double t, double midi, double dur, double gain, int accent) {
+    if (mono_note(buf, smpl("reese"), midi, t, gain * (accent ? 1.3 : 1.0), dur)) return;
+    long n = (long)(dur * SR), s0 = (long)(t * SR);
+    double f0 = midi_hz(midi), lp = 0, bp = 0, q = accent ? 0.08 : 0.14, saw = 0;
+    double envDecay = accent ? 9 : 18, cutMax = accent ? 4800 : 2600;
+    for (long i = 0; i < n; i++) {
+        double tt = (double)i / SR; saw += f0 / SR; saw -= floor(saw);
+        double osc = saw * 2 - 1, env = exp(-tt * envDecay);
+        double cutoff = 320 + (cutMax - 320) * env, fc = tan(M_PI * fmin(0.45, cutoff / SR));
+        double hp = osc - lp - q * bp; bp += fc * hp; lp += fc * bp;
+        double amp = exp(-tt * (accent ? 5 : 8)) * gain;
+        addb(buf, s0 + i, tanh(lp * 1.2) * amp);
+    }
+}
+static void snare_roll(float *buf, double t0, int bars, double baseGain) {
+    int total = bars * 16;
+    for (int e = 0; e < total; e++) { double t = t0 + e * SX, w = (double)e / total; snare_brk(buf, t, baseGain + 0.5 * w); }
+}
+
+// place a mono 303/reese voice into stereo with a short haas (drop/break use).
+static void place303_stereo(double t, double midi, double dur, double gain, int accent, double harmG, int harmInt, double haasSec) {
+    float *tmp = calloc(N, sizeof(float)); float *tmpH = calloc(N, sizeof(float));
+    acid303(tmp, t, midi, dur, gain, accent);
+    if (harmG > 0) acid303(tmpH, t, midi + harmInt, dur, harmG, accent);
+    long s0 = (long)(t * SR), h = (long)(haasSec * SR), ex = (long)((t + dur * 1.3) * SR);
+    if (ex > N) ex = N;
+    for (long i = s0; i < ex; i++) { double v = tmp[i], vh = tmpH[i]; if (v || vh) { busL[i] += (float)(v + vh * 0.55); if (i + h < N) busR[i + h] += (float)(v + vh); } }
+    free(tmp); free(tmpH);
+}
+
+// ── kick sidechain times ──────────────────────────────────────────────────
+static double kick_times[8192]; static int n_kt = 0;
+static void push_kt(double t) { if (n_kt < 8192) kick_times[n_kt++] = t; }
+
+// hoover stab — a soft sampled-reese triad voice (the JS synth hoover is a
+// no-op in jungle mode; here the stab body is the reese sample, kept soft).
+static void hoover_stab(double t, double midi, double dur, double gain, double gL, double gR) {
+    float *tmp = calloc(N, sizeof(float));
+    mono_note(tmp, smpl("reese"), midi, t, gain, dur);
+    long s0 = (long)(t * SR), haas = (long)(0.009 * SR), ex = (long)((t + dur) * SR);
+    if (ex > N) ex = N;
+    for (long i = s0; i < ex; i++) { double v = tmp[i]; if (v) { busL[i] += (float)(v * gL); if (i + haas < N) busR[i + haas] += (float)(v * gR); } }
+    free(tmp);
+}
+
+// ── F-minor harmony ────────────────────────────────────────────────────────
+static const int FM_ROOTS[4] = { 53, 51, 49, 48 };
+static const int FM_PAD[4] = { 41, 53, 56, 60 };
+static const int EB_PAD[4] = { 39, 51, 54, 58 };
+static const int DB_PAD[4] = { 37, 49, 52, 56 };
+static const int C_PAD[4]  = { 36, 48, 51, 55 };
+
+// section table
+static const char *ORDER[8] = { "intro", "buildA", "drop1", "breakA", "drop2", "breakB", "drop3", "outro" };
+static const int SECBARS[8] = { 8, 4, 16, 8, 16, 8, 16, 12 };
+static int START[8];
+static int sec_index(const char *k) { for (int i = 0; i < 8; i++) if (!strcmp(ORDER[i], k)) return i; return 0; }
+static const char *sec_of_bar(int b) { for (int i = 0; i < 8; i++) { if (b < START[i] + SECBARS[i]) return ORDER[i]; } return "outro"; }
+
+static int total_bars(void) { int t = 0; for (int i = 0; i < 8; i++) t += SECBARS[i]; return t; }
+
+int main(int argc, char **argv) {
+    const char *out_path = "out/c-raw.wav";
+    for (int i = 1; i < argc; i++) {
+        if (!strcmp(argv[i], "--out") && i + 1 < argc) out_path = argv[++i];
+        else if (!strcmp(argv[i], "--bpm") && i + 1 < argc) BPMV = atof(argv[++i]);
+        else if (!strcmp(argv[i], "--lazy") && i + 1 < argc) LAZY = atof(argv[++i]);
+        else if (!strcmp(argv[i], "--human") && i + 1 < argc) HUMAN = atof(argv[++i]);
+        else if (!strcmp(argv[i], "--payphone")) g_payphone = 1;
+    }
+    BEAT = 60.0 / BPMV; BAR = BEAT * 4; SX = BEAT / 4;
+    { int c = 0; for (int i = 0; i < 8; i++) { START[i] = c; c += SECBARS[i]; } }
+    int TB = total_bars();
+    double totalSec = TB * BAR + 4.0;
+    N = (long)(totalSec * SR);
+
+    busL = calloc(N, 4); busR = calloc(N, 4); drm = calloc(N, 4);
+    revL = calloc(N, 4); revR = calloc(N, 4); vocL = calloc(N, 4); vocR = calloc(N, 4);
+    load_roster();
+    Smp *bellS; { long bn; int bsr; float *bs = load_wav(BELL_PATH, &bn, &bsr); static Smp bellSt; if (bs) { bellSt = (Smp){ bs, bn, bsr, 60, 60, 1 }; bellS = &bellSt; } else bellS = NULL; }
+
+    fprintf(stderr, "# maytrax.c · %g BPM · %d bars · %.1fs · stereo\n", BPMV, TB, totalSec);
+
+    // ════════════════ ARRANGEMENT ════════════════
+    int cursor;
+
+    // ── INTRO (8) — sub pulse + sparse hats + dark pad swell ──
+    cursor = START[sec_index("intro")];
+    {
+        double t0 = cursor * BAR;
+        // staggered intro — instruments enter ONE AT A TIME so the track
+        // builds layer by layer:
+        //   bar 0  pad (harmonic bed)
+        //   bar 2  flute shanty melody  (in the sampled-instrument layer)
+        //   bar 4  sub-bass pulse
+        //   bar 6  hats (the pulse ticks in)
+        dark_pad(busL, busR, t0, FM_PAD, 4, BAR * 4 - 0.05, 0.10);
+        dark_pad(busL, busR, t0 + BAR * 4, EB_PAD, 4, BAR * 4 - 0.05, 0.12);
+        for (int b = 4; b < 8; b++) {                       // sub enters bar 4
+            int root = 27;
+            for (int q = 0; q < 4; q++) { sub_bass(busL, t0 + (b * 4 + q) * BEAT, root, BEAT * 0.9, 0.18); sub_bass(busR, t0 + (b * 4 + q) * BEAT, root, BEAT * 0.9, 0.18); }
+        }
+        for (int b = 6; b < 8; b++) for (int e = 0; e < 16; e++) if (e == 6 || e == 14) tight_hat(busL, busR, t0 + b * BAR + e * SX, 1, 0.08, e == 6 ? -0.08 : 0.08); // hats enter bar 6
+    }
+
+    // ── BUILD A (4) — pad rises, snare roll, riser ──
+    cursor = START[sec_index("buildA")];
+    {
+        double t0 = cursor * BAR;
+        dark_pad(busL, busR, t0, DB_PAD, 4, BAR * 2 - 0.05, 0.22);
+        dark_pad(busL, busR, t0 + BAR * 2, C_PAD, 4, BAR * 2 - 0.05, 0.26);
+        for (int b = 0; b < 4; b++) { int root = b < 2 ? 25 : 24; for (int q = 0; q < 4; q++) { sub_bass(busL, t0 + (b * 4 + q) * BEAT, root, BEAT * 0.9, 0.22); sub_bass(busR, t0 + (b * 4 + q) * BEAT, root, BEAT * 0.9, 0.22); } }
+        snare_roll(drm, t0 + BAR * 2, 2, 0.32);
+        riser(busL, busR, t0 + BAR * 3, BAR - 0.02, 0.34);
+        reverse_swell(busL, busR, t0, BAR * 4 - 0.02, 0.20);
+    }
+
+    // ── DROP 1 (16) ──
+    cursor = START[sec_index("drop1")];
+    for (int b = 0; b < 16; b++) {
+        double t0 = (cursor + b) * BAR;
+        break_bar(busL, busR, drm, t0, 1.0, 0.35);
+        perc_groove(busL, busR, revL, revR, t0, 0.85, 0.018, 0.052, 0.38);
+        push_kt(t0); push_kt(t0 + 3 * SX); push_kt(t0 + 10 * SX);
+        int root = 29 + (FM_ROOTS[b % 4] - FM_ROOTS[0]);
+        for (int q = 0; q < 4; q++) { sub_bass(busL, t0 + q * BEAT, root, BEAT * 0.9, 0.30); sub_bass(busR, t0 + q * BEAT, root, BEAT * 0.9, 0.30); }
+        int stab = FM_ROOTS[b % 4];
+        hoover_stab(t0 + BEAT * 2, stab, BEAT * 2, 0.32, 1.0, 0.75);
+        hoover_stab(t0 + BEAT * 2, stab + 7, BEAT * 2, 0.20, 0.6, 1.0);
+        // 303 under
+        int pent[8] = { 53, 56, 58, 60, 63, 60, 58, 56 };
+        for (int e = 0; e < 16; e += 2) {
+            int midi = pent[e % 8] - 12;
+            place303_stereo(t0 + e * SX, midi, SX * 0.85, 0.14, e % 4 == 0, e % 4 == 0 ? 0.09 : 0, 7, 0.006);
+        }
+    }
+
+    // ── BREAK A (8) — kick out, 303 acid ──
+    cursor = START[sec_index("breakA")];
+    for (int b = 0; b < 8; b++) {
+        double t0 = (cursor + b) * BAR;
+        perc_groove(busL, busR, revL, revR, t0, 0.55, 0.018, 0.045, 0.5);
+        for (int e = 0; e < 16; e++) if (e % 4 == 2) tight_hat(busL, busR, t0 + e * SX, 1, 0.14, (e % 8 == 2 ? -0.1 : 0.1));
+        snare_brk(drm, t0 + BEAT, 0.5); snare_brk(drm, t0 + BEAT * 3, 0.5);
+        int pent[8] = { 53, 56, 58, 60, 63, 60, 58, 56 };
+        for (int e = 0; e < 16; e++) {
+            int midi = pent[e % 8] + (b % 2 == 0 ? 0 : -12);
+            int accent = e % 4 == 0;
+            place303_stereo(t0 + e * SX, midi, SX * 0.9, 0.26, accent, accent ? 0.16 : 0.08, accent ? 7 : 3, 0.005);
+        }
+        if (b == 0) dark_pad(busL, busR, t0, FM_PAD, 4, BAR * 4 - 0.05, 0.16);
+        if (b == 4) dark_pad(busL, busR, t0, EB_PAD, 4, BAR * 4 - 0.05, 0.16);
+    }
+    riser(busL, busR, (cursor + 6) * BAR, BAR * 2 - 0.05, 0.38);
+
+    // ── DROP 2 (16) ──
+    cursor = START[sec_index("drop2")];
+    for (int b = 0; b < 16; b++) {
+        double t0 = (cursor + b) * BAR;
+        break_bar(busL, busR, drm, t0, 1.0, 0.35);
+        perc_groove(busL, busR, revL, revR, t0, 1.0, 0.018, 0.052, 0.38);
+        push_kt(t0); push_kt(t0 + 3 * SX); push_kt(t0 + 10 * SX);
+        int root = 29 + (FM_ROOTS[b % 4] - FM_ROOTS[0]);
+        for (int q = 0; q < 4; q++) { sub_bass(busL, t0 + q * BEAT, root, BEAT * 0.9, 0.32); sub_bass(busR, t0 + q * BEAT, root, BEAT * 0.9, 0.32); }
+        int stab = FM_ROOTS[b % 4];
+        hoover_stab(t0 + BEAT * 2, stab, BEAT * 2, 0.36, 1.0, 0.75);
+        hoover_stab(t0 + BEAT * 2, stab + 7, BEAT * 2, 0.22, 0.6, 1.0);
+        int pent[8] = { 53, 56, 58, 60, 63, 60, 58, 56 };
+        for (int e = 0; e < 16; e += 2) { int midi = pent[e % 8] - 12; place303_stereo(t0 + e * SX, midi, SX * 0.85, 0.18, e % 4 == 0, e % 4 == 0 ? 0.10 : 0.06, e % 4 == 0 ? 7 : 3, 0.006); }
+        if (b == 8 && bellS) { place(busL, busR, bellS, t0, 0.30, 1.0, 0.5, 1e9); place(revL, revR, bellS, t0, 0.20, 1.0, 0, 1e9); }
+    }
+
+    // ── BREAK B (8) — atmospheric ──
+    cursor = START[sec_index("breakB")];
+    {
+        double t0 = cursor * BAR;
+        dark_pad(busL, busR, t0, DB_PAD, 4, BAR * 4 - 0.05, 0.22);
+        dark_pad(busL, busR, t0 + BAR * 4, C_PAD, 4, BAR * 4 - 0.05, 0.22);
+        for (int b = 0; b < 8; b++) perc_groove(busL, busR, revL, revR, t0 + b * BAR, 0.35 + b * 0.04, 0.022, 0.04, 0.6);
+        for (int b = 0; b < 8; b++) { int root = b < 4 ? 25 : 24; sub_bass(busL, t0 + b * BAR, root, BAR * 0.85, 0.26); sub_bass(busR, t0 + b * BAR, root, BAR * 0.85, 0.26); }
+        if (bellS) { place(busL, busR, bellS, t0, 0.32, 1.0, 0.55, 1e9); place(revL, revR, bellS, t0, 0.24, 1.0, 0, 1e9); place(busL, busR, bellS, t0 + BAR * 4, 0.28, 1.05, 0.55, 1e9); place(revL, revR, bellS, t0 + BAR * 4, 0.22, 1.05, 0, 1e9); }
+        reverse_swell(busL, busR, t0 + BAR * 4, BAR * 4 - 0.05, 0.30);
+        snare_roll(drm, t0 + BAR * 6, 2, 0.30);
+        riser(busL, busR, t0 + BAR * 7, BAR - 0.02, 0.40);
+    }
+
+    // ── DROP 3 (16) — biggest ──
+    cursor = START[sec_index("drop3")];
+    for (int b = 0; b < 16; b++) {
+        double t0 = (cursor + b) * BAR;
+        break_bar(busL, busR, drm, t0, 1.05, 0.35);
+        perc_groove(busL, busR, revL, revR, t0, 1.15, 0.018, 0.06, 0.42);
+        push_kt(t0); push_kt(t0 + 3 * SX); push_kt(t0 + 10 * SX);
+        int root = 29 + (FM_ROOTS[b % 4] - FM_ROOTS[0]);
+        for (int q = 0; q < 4; q++) { sub_bass(busL, t0 + q * BEAT, root, BEAT * 0.9, 0.36); sub_bass(busR, t0 + q * BEAT, root, BEAT * 0.9, 0.36); }
+        int stab = FM_ROOTS[b % 4];
+        hoover_stab(t0 + BEAT * 2, stab, BEAT * 2, 0.40, 1.0, 0.72);
+        hoover_stab(t0 + BEAT * 2, stab + 7, BEAT * 2, 0.24, 0.62, 1.0);
+        hoover_stab(t0 + BEAT * 2, stab + 12, BEAT * 2, 0.18, 0.55, 0.55);
+        if (b % 2 == 0) { int pent[5] = { 53, 56, 58, 60, 63 }; int midi = pent[b % 5] - 12; place303_stereo(t0 + BEAT * 2.5, midi, BEAT * 0.5, 0.22, 1, 0.12, 7, 0.006); }
+    }
+
+    // ── OUTRO (12) — decay ──
+    cursor = START[sec_index("outro")];
+    for (int b = 0; b < 12; b++) {
+        double t0 = (cursor + b) * BAR;
+        double energy = fmax(0.15, 1.0 - b * 0.075);
+        break_bar(busL, busR, drm, t0, energy, 0.35);
+        perc_groove(busL, busR, revL, revR, t0, energy, 0.018, 0.052, 0.45);
+        push_kt(t0); push_kt(t0 + 3 * SX); push_kt(t0 + 10 * SX);
+        int root = b < 6 ? 29 : 24;
+        for (int q = 0; q < 4; q++) { sub_bass(busL, t0 + q * BEAT, root, BEAT * 0.9, 0.30 * energy); sub_bass(busR, t0 + q * BEAT, root, BEAT * 0.9, 0.30 * energy); }
+    }
+    {
+        double t0 = cursor * BAR;
+        dark_pad(busL, busR, t0, FM_PAD, 4, BAR * 6 - 0.05, 0.20);
+        dark_pad(busL, busR, t0 + BAR * 6, C_PAD, 4, BAR * 6 - 0.05, 0.18);
+        if (bellS) { place(busL, busR, bellS, t0 + BAR * 10, 0.45, 0.95, 0.6, 1e9); place(revL, revR, bellS, t0 + BAR * 10, 0.45, 0.95, 0, 1e9); }
+    }
+
+    // ════════════════ SAMPLED-INSTRUMENT LAYER ════════════════
+    {
+        // ambience bed
+        Smp *rain = smpl("rain"), *jng = smpl("jungle"), *crk = smpl("cricket");
+        if (rain) place(busL, busR, rain, 0, 0.10, 1, rnd2() * 0.3, 1e9);   // softer opener
+        if (jng) place(busL, busR, jng, 0, 0.07, 1, rnd2() * 0.3, 1e9);
+        if (crk) place(busL, busR, crk, 0.5, 0.06, 1, rnd2() * 0.3, 1e9);
+        for (double t = 8; t < TB * BAR; t += 18) { if (rain) place(busL, busR, rain, t, 0.05, 1, rnd2() * 0.3, 1e9); if (crk && rnd() < 0.5) place(busL, busR, crk, t + 4, 0.04, 1, rnd2() * 0.3, 1e9); }
+        if (rain) place(busL, busR, rain, (TB - 10) * BAR, 0.2, 1, rnd2() * 0.3, 1e9);
+        if (crk) place(busL, busR, crk, (TB - 9) * BAR, 0.14, 1, rnd2() * 0.3, 1e9);
+        if (jng) place(busL, busR, jng, (TB - 8) * BAR, 0.12, 1, rnd2() * 0.3, 1e9);
+
+        // perc + hats throughout
+        Smp *hatS = smpl("hat"), *ohatS = smpl("ohat"), *cow = smpl("cowbell"), *tomS = smpl("tom");
+        double lag = 0.010 * LAZY;
+        for (int bAbs = 0; bAbs < TB; bAbs++) {
+            const char *sec = sec_of_bar(bAbs);
+            int inDrop = !strncmp(sec, "drop", 4), quiet = !strcmp(sec, "intro") || !strcmp(sec, "outro");
+            // staggered build — no perc until bar 6 of the intro (hats are the
+            // last thing to enter before the build).
+            if (!strcmp(sec, "intro") && bAbs < START[sec_index("intro")] + 6) continue;
+            double dens = inDrop ? 1 : !strncmp(sec, "break", 5) ? 0.55 : quiet ? 0.3 : 0.7;
+            for (int s = 0; s < 16; s++) {
+                double sw = (s % 2 ? 0.020 * LAZY : 0);
+                double t = bAbs * BAR + s * SX + lag + sw + hz();
+                if (hatS && s % 2 == 1) place(busL, busR, hatS, t, (s % 4 == 3 ? 0.055 : 0.038) * dens, 1, 0.2, 0.05 * DEC);
+                // clicks dropped — they were a thrashy chatter on the grid
+            }
+            if (ohatS && rnd() < 0.4 * dens) place(busL, busR, ohatS, bAbs * BAR + 6 * SX + lag + hz(), 0.05 * dens, 1, 0.25, 0.12 * DEC);
+            // cowbell only on the & of 4, much sparser + softer (was a busy rattle)
+            if (cow && inDrop && rnd() < 0.10 * dens) place(busL, busR, cow, bAbs * BAR + 14 * SX + lag + hz(), 0.045 * dens, 1, rnd2() * 0.4, 0.14 * DEC);
+            // tom fill only every 8 bars, softer + swelled, as a gentle turnaround
+            if (tomS && bAbs % 8 == 7 && !quiet) { int ss[3] = { 10, 12, 14 }; for (int k = 0; k < 3; k++) place_a(busL, busR, tomS, bAbs * BAR + ss[k] * SX + lag + hz(), 0.11 * dens, pow(2.0, -k / 6.0), (k - 1) * 0.3, 0.6 * DEC, 0.006); }
+        }
+
+        // drops: gong, taiko, flute bleeps, reverse-wolf riser, animal roar, choir
+        const char *dropNames[3] = { "drop1", "drop2", "drop3" };
+        Smp *gong = smpl("gong"), *taiko = smpl("taiko"), *lead = smpl("lead"), *animal = smpl("animal"), *choir = smpl("choir");
+        for (int d = 0; d < 3; d++) {
+            const char *name = dropNames[d]; int s0b = START[sec_index(name)]; int isD3 = !strcmp(name, "drop3");
+            if (gong) { double t = s0b * BAR; place_a(busL, busR, gong, t, 0.26, 1, 0.5, 1.2 * DEC, 0.06); place_a(revL, revR, gong, t, 0.24, 1, 0, 1.2 * DEC, 0.06); }
+            for (int b = 0; b < 16; b++) {
+                double t0 = (s0b + b) * BAR; int root = FM_ROOTS[b % 4]; int phraseStart = b % 4 == 0;
+                if (taiko) { place(busL, busR, taiko, t0, 0.42, 1, 0.15, 0.40 * DEC); place(busL, busR, taiko, t0 + 2 * BEAT, 0.32, 1, -0.15, 0.40 * DEC); }
+                if (lead) {
+                    int steps5[5] = { 0, 3, 6, 10, 13 }, steps3[3] = { 0, 6, 10 };
+                    int *steps = isD3 ? steps5 : steps3, ns = isD3 ? 5 : 3;
+                    // softer + fewer steps + tamed high partials (was a bright,
+                    // thrashy bleep cluster); a gentle onset so they don't click.
+                    double BLEEP[5][2] = { { 12, 0.5 }, { 15, 0.28 }, { 19, 0.3 }, { 24, 0.12 }, { 31, 0.06 } };
+                    for (int si2 = 0; si2 < ns; si2++) {
+                        int st = steps[si2]; double t = t0 + st * SX, g = (st == 0 ? 0.14 : 0.09);
+                        for (int z = 0; z < 5; z++) place_a(busL, busR, lead, t, g * BLEEP[z][1], rate_nom(lead, root + BLEEP[z][0]), rnd2() * 0.55, 0.14 * DEC, 0.004);
+                        place(revL, revR, lead, t, g * 0.3, rate_nom(lead, root + 12), 0, 0.16 * DEC);
+                        if (animal_rev.ok && rnd() < 0.5) place(busL, busR, &animal_rev, t, 0.1, rate_nom(animal ? animal : &animal_rev, root + 12), rnd2() * 0.6, 0.12 * DEC);
+                    }
+                }
+                if (wolf_rev.ok && phraseStart) {
+                    // bigger pitch swing per phrase + an octave harmonic above —
+                    // softer now, and it already swells (reversed), so it glides in.
+                    double hold = isD3 ? 2.6 : 2.0; int up[4] = { 12, 19, 7, 24 }; int leadN = root + up[(b / 4) % 4];
+                    place(busL, busR, &wolf_rev, t0 - hold, 0.20, rate_nom(&wolf_rev, leadN), 0.2, hold);
+                    place(revL, revR, &wolf_rev, t0 - hold, 0.16, rate_nom(&wolf_rev, leadN), 0, hold);
+                    place(busL, busR, &wolf_rev, t0 - hold, 0.09, rate_nom(&wolf_rev, leadN + 12), -0.25, hold);
+                }
+                if (animal) {
+                    if (phraseStart) {
+                        // bigger pitch swing per phrase + a 5th-harmonic layer, but
+                        // SWELLED IN (long attack) and well softer so the roar reads
+                        // as a deep cinematic rise, not a violent stab.
+                        int down[4] = { -24, -31, -19, -28 }; int dn = down[(b / 4) % 4];
+                        double rl = rate_nom(animal, root + dn), hold = isD3 ? 5.5 : 4.5;
+                        place_a(busL, busR, animal, t0, 0.30, rl, 0.2, hold, 0.18);
+                        place_a(revL, revR, animal, t0, 0.18, rl, 0, hold, 0.18);
+                        place_a(busL, busR, animal, t0, 0.12, rate_nom(animal, root + dn + 7), -0.3, hold * 0.8, 0.18); // 5th harmonic
+                        place_a(busL, busR, animal, t0, 0.16, rate_nom(animal, root), -0.2, 1.2 * DEC, 0.05);          // mid body
+                    } else if (rnd() < 0.18) {
+                        int up[3] = { 0, 7, 12 };
+                        place_a(busL, busR, animal, t0 + 6 * SX, 0.22, rate_nom(animal, root + up[(int)(rnd() * 3)]), rnd2() * 0.4, 0.7 * DEC, 0.04);
+                    }
+                }
+            }
+            if (choir && isD3) for (int b = 0; b < 16; b += 2) { double t0 = (s0b + b) * BAR; int ns[3] = { FM_PAD[1], FM_PAD[2], FM_PAD[3] }; for (int z = 0; z < 3; z++) { place(busL, busR, choir, t0, 0.07, rate_nom(choir, ns[z]), 0.4, 1e9); place(revL, revR, choir, t0, 0.05, rate_nom(choir, ns[z]), 0, 1e9); } }
+        }
+        // choir over breaks
+        if (choir) { const char *brk[2] = { "breakA", "breakB" }; for (int z2 = 0; z2 < 2; z2++) { int s0b = START[sec_index(brk[z2])]; for (int b = 0; b < 8; b += 2) { double t0 = (s0b + b) * BAR; int ns[3] = { FM_PAD[1], FM_PAD[2], FM_PAD[3] }; for (int z = 0; z < 3; z++) { place(busL, busR, choir, t0, 0.08, rate_nom(choir, ns[z]), 0.45, 1e9); place(revL, revR, choir, t0, 0.06, rate_nom(choir, ns[z]), 0, 1e9); } } } }
+
+        // pirate-shanty opener (flute + faint square ghost)
+        {
+            int s0b = START[sec_index("intro")];
+            double SHANTY[23][3] = {
+                {0,65,0.5},{0.5,65,0.5},{1,68,0.5},{1.5,72,0.5},{2,72,1},{3,70,1},
+                {4,68,0.5},{4.5,68,0.5},{5,67,0.5},{5.5,65,0.5},{6,63,1.5},{7.5,65,0.5},
+                {8,65,0.5},{8.5,68,0.5},{9,72,0.5},{9.5,75,0.5},{10,73,1},{11,72,1},
+                {12,68,0.5},{12.5,67,0.5},{13,65,0.5},{13.5,63,0.5},{14,65,2} };
+            for (int z = 0; z < 23; z++) {
+                double bt = SHANTY[z][0], midi = SHANTY[z][1], dur = SHANTY[z][2];
+                double t = ((s0b + 2) * BAR) + bt * 2 * BEAT + 0.012 * LAZY + hz(); // shanty enters bar 2
+                double m = midi - 12, ring = fmax(1.1, dur * 2 * BEAT);
+                if (lead) { place(busL, busR, lead, t, 0.18, rate_nom(lead, m), 0.25, ring * 0.95); place(revL, revR, lead, t, 0.14, rate_nom(lead, m), 0, ring); }
+                square_note(busL, busR, m, t, dur * 2 * BEAT * 0.9, 0.035, rnd2() * 0.25);
+            }
+            if (lead) { int bo[2] = { 2, 6 }; for (int z = 0; z < 2; z++) { double t = (s0b + bo[z]) * BAR; place(busL, busR, lead, t, 0.10, rate_nom(lead, 41), 0.1, 3.0); place(revL, revR, lead, t, 0.07, rate_nom(lead, 41), 0, 3.0); } }
+        }
+
+        // john williams strings
+        Smp *strings = smpl("strings");
+        if (strings) {
+            // strings stay OUT of the intro (the staggered build is pad→flute→
+            // sub→hats); they re-enter from breakA onward.
+            const char *segN[5] = { "breakA", "drop2", "breakB", "drop3", "outro" };
+            int segB[5] = { 8, 16, 8, 16, 12 };
+            int chord[3] = { 41, 48, 56 };
+            for (int z = 0; z < 5; z++) { int s0b = START[sec_index(segN[z])]; for (int b = 0; b < segB[z]; b += 4) { double t0 = (s0b + b) * BAR, g = !strncmp(segN[z], "drop", 4) ? 0.13 : 0.16; for (int c = 0; c < 3; c++) { place(busL, busR, strings, t0, g, rate_nom(strings, chord[c]), 0.5, 6.0); place(revL, revR, strings, t0, g * 0.5, rate_nom(strings, chord[c]), 0, 6.0); } } }
+        }
+
+        // sampled flute lead — the main voice over the drops
+        if (lead) {
+            double LEAD[8][3] = { {0,0,65},{0,2,72},{1,0,75},{1,1,72},{1,2,68},{2,0,65},{2,2,68},{3,0,72} };
+            double HARM[4][2] = { {0,0.5},{12,0.34},{7,0.26},{3,0.2} };
+            for (int d = 0; d < 3; d++) {
+                const char *name = dropNames[d]; int s0b = START[sec_index(name)]; double gain = !strcmp(name, "drop3") ? 0.34 : 0.28;
+                for (int phr = 0; phr < 4; phr++) for (int z = 0; z < 8; z++) {
+                    double bo = LEAD[z][0], beatO = LEAD[z][1], note = LEAD[z][2];
+                    double t = (s0b + phr * 4 + bo) * BAR + beatO * BEAT, pan = rnd2() * 0.3;
+                    for (int h = 0; h < 4; h++) { double jt = rnd2() * 0.012, jp = rnd2() * 0.02; place(busL, busR, lead, t + jt, gain * HARM[h][1], rate_nom(lead, note + HARM[h][0]) * (1 + jp / 12 * 0.05), pan, 0.6 * DEC); place(revL, revR, lead, t + jt, gain * HARM[h][1] * 0.3, rate_nom(lead, note + HARM[h][0]), 0, 0.6 * DEC); }
+                }
+            }
+        }
+    }
+
+    // ════════════════ SHOUTS (un-ducked vocal bus) ════════════════
+    {
+        Smp shJ[N_SHOUTS], shA[N_SHOUTS];
+        for (int i = 0; i < N_SHOUTS; i++) {
+            shJ[i].ok = shA[i].ok = 0;
+            if (SHOUT_J[i][0]) { long n; int sr; float *s = load_wav(SHOUT_J[i], &n, &sr); if (s) { double pk = 0; for (long j = 0; j < n; j++) pk = fmax(pk, fabs(s[j])); double g = pk > 0 ? 0.97 / pk : 1; for (long j = 0; j < n; j++) s[j] *= g; shJ[i] = (Smp){ s, n, sr, 60, 60, 1 }; } }
+            if (SHOUT_A[i][0]) { long n; int sr; float *s = load_wav(SHOUT_A[i], &n, &sr); if (s) { double pk = 0; for (long j = 0; j < n; j++) pk = fmax(pk, fabs(s[j])); double g = pk > 0 ? 0.97 / pk : 1; for (long j = 0; j < n; j++) s[j] *= g; shA[i] = (Smp){ s, n, sr, 60, 60, 1 }; } }
+        }
+        // key order matches SHOUT_KEY: wake real hold let rabbit now
+        #define KI(k) ( !strcmp(k,"wake")?0 : !strcmp(k,"real")?1 : !strcmp(k,"hold")?2 : !strcmp(k,"let")?3 : !strcmp(k,"rabbit")?4 : 5 )
+        // sing(key, barAbs, gain, pan)
+        const char *seqA[8] = { "wake", "real", "hold", "let", "wake", "real", "hold", "let" };
+        const char *seqB[8] = { "rabbit", "now", "rabbit", "now", "rabbit", "now", "rabbit", "now" };
+        const char *dnames[2] = { "drop1", "drop3" };
+        for (int d = 0; d < 2; d++) {
+            int s0b = START[sec_index(dnames[d])];
+            for (int i = 0; i < 8; i++) {
+                int ki = KI(seqA[i]); double t = (s0b + i * 2) * BAR, g = 1.05, pan = (i % 2 ? 0.12 : -0.12);
+                if (shJ[ki].ok) { place(vocL, vocR, &shJ[ki], t, g, 1, pan, 1e9); place(revL, revR, &shJ[ki], t, g * 0.18, 1, 0, 1e9); }
+                if (shA[ki].ok) { place(vocL, vocR, &shA[ki], t, g * 0.32, 1, -pan - 0.2, 1e9); place(revL, revR, &shA[ki], t, g * 0.14, 1, 0, 1e9); }
+            }
+        }
+        { int s0b = START[sec_index("drop2")]; for (int i = 0; i < 8; i++) { int ki = KI(seqB[i]); double t = (s0b + i * 2) * BAR, g = 1.05, pan = (i % 2 ? 0.12 : -0.12); if (shJ[ki].ok) { place(vocL, vocR, &shJ[ki], t, g, 1, pan, 1e9); place(revL, revR, &shJ[ki], t, g * 0.18, 1, 0, 1e9); } if (shA[ki].ok) { place(vocL, vocR, &shA[ki], t, g * 0.32, 1, -pan - 0.2, 1e9); place(revL, revR, &shA[ki], t, g * 0.14, 1, 0, 1e9); } } }
+    }
+
+    // ════════════════ REVERB (Schroeder) → bus ════════════════
+    {
+        // tighter space — shorter, drier, darker tail than the JS (.80/.55/.42)
+        double decay = 0.66, wet = 0.38, damp = 0.52;
+        int CD[6]; double cds[6] = { 0.0297, 0.0371, 0.0411, 0.0437, 0.0497, 0.0581 };
+        for (int k = 0; k < 6; k++) CD[k] = (int)(cds[k] * SR);
+        int AD[2] = { (int)(0.005 * SR), (int)(0.0017 * SR) }; double apFb = 0.5;
+        float *cbL[6], *cbR[6]; int ciL[6] = {0}, ciR[6] = {0}; double cLPL[6] = {0}, cLPR[6] = {0};
+        for (int k = 0; k < 6; k++) { cbL[k] = calloc(CD[k], 4); cbR[k] = calloc(CD[k], 4); }
+        float *abL[2], *abR[2]; int aiL[2] = {0}, aiR[2] = {0};
+        for (int k = 0; k < 2; k++) { abL[k] = calloc(AD[k], 4); abR[k] = calloc(AD[k], 4); }
+        for (long i = 0; i < N; i++) {
+            double inL = revL[i], inR = revR[i], cL = 0, cR = 0;
+            for (int k = 0; k < 6; k++) {
+                double dL = cbL[k][ciL[k]], dR = cbR[k][ciR[k]]; cL += dL; cR += dR;
+                cLPL[k] = dL * (1 - damp) + cLPL[k] * damp; cLPR[k] = dR * (1 - damp) + cLPR[k] * damp;
+                cbL[k][ciL[k]] = (float)(inL + cLPL[k] * decay); cbR[k][ciR[k]] = (float)(inR + cLPR[k] * decay);
+                ciL[k] = (ciL[k] + 1) % CD[k]; ciR[k] = (ciR[k] + 1) % CD[k];
+            }
+            cL /= 6; cR /= 6;
+            for (int k = 0; k < 2; k++) {
+                double dL = abL[k][aiL[k]], dR = abR[k][aiR[k]];
+                double oL = -apFb * cL + dL, oR = -apFb * cR + dR;
+                abL[k][aiL[k]] = (float)(cL + apFb * oL); abR[k][aiR[k]] = (float)(cR + apFb * oR);
+                aiL[k] = (aiL[k] + 1) % AD[k]; aiR[k] = (aiR[k] + 1) % AD[k];
+                cL = oL; cR = oR;
+            }
+            busL[i] += (float)(cL * wet); busR[i] += (float)(cR * wet);
+        }
+        for (int k = 0; k < 6; k++) { free(cbL[k]); free(cbR[k]); }
+        for (int k = 0; k < 2; k++) { free(abL[k]); free(abR[k]); }
+    }
+
+    // ════════════════ SIDECHAIN DUCK ════════════════
+    float *duck = malloc(N * 4); for (long i = 0; i < N; i++) duck[i] = 1;
+    for (int k = 0; k < n_kt; k++) { long s0 = (long)(kick_times[k] * SR), len = (long)(0.14 * SR); for (long i = 0; i < len && s0 + i < N; i++) { double w = (double)i / len, d = 0.55 + 0.45 * w; if (d < duck[s0 + i]) duck[s0 + i] = (float)d; } }
+
+    // ════════════════ CRUNCH + SVF SWEEP + vocals ════════════════
+    long MAXOUT = N + (long)(30 * SR) + 16;
+    float *outL = calloc(MAXOUT, 4), *outR = calloc(MAXOUT, 4);
+    {
+        // smooth: near-clean drive + gentle wobble (JS was CRUNCH 1 / WOB .4)
+        double CRUNCH = 0.15, WOB = 0.2, wobHz = (BPMV / 60) / 2, Q = 0.8, qc = 1 / Q, fcMax = SR * 0.16;
+        // slow build — the opening swell now ramps across intro + build + the
+        // first 4 bars of drop 1, on a steeper curve, so the track eases in.
+        double swellT = (SECBARS[0] + SECBARS[1] + 4) * BAR;
+        // vocals come in SLOW — the shouts first land at drop 1; ease them up
+        // from silence across the first 6 bars so they don't slam in.
+        double vocStart = START[sec_index("drop1")] * BAR, vocFadeLen = 6 * BAR;
+        struct { const char *k; double s, e; } segs[8];
+        { double c = 0; for (int i = 0; i < 8; i++) { segs[i].k = ORDER[i]; segs[i].s = c * BAR; segs[i].e = (c + SECBARS[i]) * BAR; c += SECBARS[i]; } }
+        double lowL = 0, bandL = 0, lowR = 0, bandR = 0; int si = 0;
+        for (long i = 0; i < N; i++) {
+            double t = (double)i / SR;
+            while (si < 7 && t >= segs[si].e) si++;
+            double p = (t - segs[si].s) / fmax(1e-6, segs[si].e - segs[si].s), cut;
+            const char *k = segs[si].k;
+            if (!strncmp(k, "drop", 4)) { double lfo = 0.5 + 0.5 * sin(TAU * wobHz * t); cut = 13000 - WOB * 6000 * lfo; }
+            else if (!strncmp(k, "break", 5)) cut = 9000 - 8500 * sin(M_PI * p);
+            else if (!strcmp(k, "intro")) cut = 6000;
+            else if (!strcmp(k, "buildA")) cut = 1200 * pow(24000.0 / 1200, p);
+            else cut = 12000 - 9500 * p;
+            cut = fmax(220, fmin(fcMax, cut));
+            double f = 2 * sin(M_PI * cut / SR);
+            // bigger grooves — the dry kick/snare bus drives harder into the
+            // crunch (more weight + saturation) than the JS 0.96.
+            double mL = (busL[i] * duck[i] + drm[i] * 1.18) * 1.05;
+            double mR = (busR[i] * duck[i] + drm[i] * 1.18) * 1.05;
+            // crunch: drive → asym fold → mild bitcrush
+            double yL = tanh(mL * (1.1 + 1.0 * CRUNCH)); yL = yL - 0.10 * CRUNCH * yL * yL * yL; yL = round(yL * 512) / 512;
+            double yR = tanh(mR * (1.1 + 1.0 * CRUNCH)); yR = yR - 0.10 * CRUNCH * yR * yR * yR; yR = round(yR * 512) / 512;
+            double hL = yL - lowL - qc * bandL; bandL += f * hL; lowL += f * bandL;
+            double hR = yR - lowR - qc * bandR; bandR += f * hR; lowR += f * bandR;
+            double swell = t < swellT ? 0.02 + 0.98 * pow(t / swellT, 3.6) : 1;
+            // vocals smoother + softer — lower level and a shallower pump (the
+            // JS slammed them at 1.5 with a deep 0.74+0.26 duck).
+            double vduck = 0.88 + 0.12 * duck[i];
+            double vfade = t < vocStart ? 0 : t < vocStart + vocFadeLen ? 0.5 - 0.5 * cos(M_PI * (t - vocStart) / vocFadeLen) : 1;
+            outL[i] = (float)(lowL * swell + vocL[i] * 1.02 * vduck * vfade);
+            outR[i] = (float)(lowR * swell + vocR[i] * 1.02 * vduck * vfade);
+        }
+    }
+
+    // ════════════════ HEALING DRONE ════════════════
+    {
+        double durS = (double)N / SR;
+        double Hf[4] = { 174.61, 261.63, 392.00, 523.25 }, Hpr[4] = { 0.013, 0.017, 0.011, 0.019 }, Hpd[4] = { 2.0, 1.5, 3.0, 2.0 }, Hpanr[4] = { 0.05, 0.07, 0.09, 0.06 }, Hampr[4] = { 0.06, 0.04, 0.05, 0.07 };
+        double ph[4] = {0};
+        for (long i = 0; i < N; i++) {
+            double t = (double)i / SR, fade = fmin(1, t / 6) * fmin(1, (durS - t) / 6);
+            for (int k = 0; k < 4; k++) {
+                double f = Hf[k] * pow(2.0, (Hpd[k] / 12) * sin(TAU * Hpr[k] * t + k));
+                ph[k] += TAU * f / SR;
+                double amp = 0.019 * (0.5 + 0.5 * sin(TAU * Hampr[k] * t + k * 1.7)) * fade;
+                double pan = sin(TAU * Hpanr[k] * t + k * 2.1), v = sin(ph[k]) * amp;
+                outL[i] += (float)(v * (0.5 - pan * 0.5)); outR[i] += (float)(v * (0.5 + pan * 0.5));
+            }
+        }
+    }
+
+    // ════════════════ SINE TINGE DROPLETS ════════════════
+    {
+        double dropF[5] = { 523.25, 587.33, 659.25, 783.99, 880.0 };
+        for (int b = 4; b < TB; b++) {
+            if (rnd() < 0.55) continue;
+            double t0 = b * BAR + rnd() * BAR, f0 = dropF[(int)(rnd() * 5)];
+            long n = (long)(0.4 * SR), s0 = (long)(t0 * SR); double pan = rnd2(), p = 0;
+            for (long i = 0; i < n; i++) { double t = (double)i / SR, f = f0 * pow(2.0, -1.6 * t); p += TAU * f / SR; double v = sin(p) * exp(-t * 7) * 0.085; if (s0 + i < N) { outL[s0 + i] += (float)(v * (0.5 - pan * 0.5)); outR[s0 + i] += (float)(v * (0.5 + pan * 0.5)); } }
+        }
+    }
+
+    // ════════════════ PAYPHONE INTRO (opt-in via --payphone) ════════════════
+    if (g_payphone) {
+        double PHONE = 6.0, XF = 1.6; long endI = (long)((PHONE + XF) * SR);
+        double s1L = 0, s2L = 0, s1R = 0, s2R = 0;
+        double aLo = 1 - exp(-2 * M_PI * 400 / SR), aHi = 1 - exp(-2 * M_PI * 3000 / SR);
+        for (long i = 0; i < endI && i < N; i++) {
+            double t = (double)i / SR, xL = outL[i], xR = outR[i];
+            s1L += aLo * (xL - s1L); double bL = xL - s1L; s2L += aHi * (bL - s2L); bL = s2L;
+            s1R += aLo * (xR - s1R); double bR = xR - s1R; s2R += aHi * (bR - s2R); bR = s2R;
+            double wetL = (round(bL * 28) / 28) * 0.42, wetR = (round(bR * 28) / 28) * 0.42;
+            double mix = t < PHONE ? 0 : (t - PHONE) / XF;
+            outL[i] = (float)(wetL * (1 - mix) + xL * mix); outR[i] = (float)(wetR * (1 - mix) + xR * mix);
+        }
+    }
+
+    // normalize headroom
+    { double peak = 0; for (long i = 0; i < N; i++) { double a = fmax(fabs(outL[i]), fabs(outR[i])); if (a > peak) peak = a; } if (peak > 0) { double g = 0.78 / peak; for (long i = 0; i < N; i++) { outL[i] *= (float)g; outR[i] *= (float)g; } } }
+
+    // ════════════════ TAPE-STOP ENDING ════════════════
+    long outN = N;
+    {
+        double TAPE = 24.0; long ts0 = (long)((TB * BAR - TAPE) * SR); if (ts0 < 0) ts0 = 0;
+        long srcLen = N - ts0; long maxTail = 2 * srcLen + 8;
+        float *tailL = malloc(maxTail * 4), *tailR = malloc(maxTail * 4); long tn = 0;
+        double pos = 0;
+        while (ts0 + pos < N - 1 && tn < maxTail) {
+            double prog = pos / srcLen, rate = fmax(0.5, 1 - prog * prog * 0.5);
+            double sp = ts0 + pos; long j = (long)sp; double fr = sp - j;
+            tailL[tn] = (float)(outL[j] * (1 - fr) + outL[j + 1] * fr);
+            tailR[tn] = (float)(outR[j] * (1 - fr) + outR[j + 1] * fr);
+            tn++; pos += rate;
+        }
+        outN = ts0 + tn;
+        if (outN > MAXOUT) outN = MAXOUT;
+        for (long i = 0; i < tn && ts0 + i < MAXOUT; i++) { outL[ts0 + i] = tailL[i]; outR[ts0 + i] = tailR[i]; }
+        free(tailL); free(tailR);
+    }
+
+    // ════════════════ TRIM ════════════════
+    long tailEnd = outN - 1;
+    while (tailEnd > 0 && fabs(outL[tailEnd]) < 0.0003 && fabs(outR[tailEnd]) < 0.0003) tailEnd--;
+    long trimN = outN < tailEnd + (long)SR ? outN : tailEnd + (long)SR;
+
+    // ════════════════ PHONE-WORLD LOOP TAIL (opt-in) + FADE ════════════════
+    {
+        if (g_payphone) {
+            double PH = 6.0; long ph0 = trimN - (long)(PH * SR); if (ph0 < 0) ph0 = 0;
+            double s1L = 0, s2L = 0, s1R = 0, s2R = 0;
+            double aLo = 1 - exp(-2 * M_PI * 400 / SR), aHi = 1 - exp(-2 * M_PI * 3000 / SR);
+            for (long i = ph0; i < trimN; i++) {
+                double xL = outL[i], xR = outR[i];
+                s1L += aLo * (xL - s1L); double bL = xL - s1L; s2L += aHi * (bL - s2L); bL = s2L;
+                s1R += aLo * (xR - s1R); double bR = xR - s1R; s2R += aHi * (bR - s2R); bR = s2R;
+                double mix = (double)(i - ph0) / (trimN - ph0);
+                outL[i] = (float)(xL * (1 - mix) + (round(bL * 28) / 28) * 0.42 * mix);
+                outR[i] = (float)(xR * (1 - mix) + (round(bR * 28) / 28) * 0.42 * mix);
+            }
+        }
+        long fadeN = trimN < (long)(1.2 * SR) ? trimN : (long)(1.2 * SR);
+        for (long i = 0; i < fadeN; i++) { double g = cos((M_PI / 2) * ((double)i / fadeN)); long idx = trimN - fadeN + i; outL[idx] *= (float)g; outR[idx] *= (float)g; }
+    }
+
+    if (!write_wav_f32_stereo(out_path, outL, outR, trimN)) { fprintf(stderr, "✗ write failed\n"); return 1; }
+    fprintf(stderr, "✓ %s · %.1fs\n", out_path, (double)trimN / SR);
+    return 0;
+}
diff --git a/pop/maytrax/c/mosstrax b/pop/maytrax/c/mosstrax
new file mode 100755
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diff --git a/pop/maytrax/c/mosstrax.c b/pop/maytrax/c/mosstrax.c
new file mode 100644
index 000000000..2b5048833
--- /dev/null
+++ b/pop/maytrax/c/mosstrax.c
@@ -0,0 +1,279 @@
+// mosstrax.c — a sine-bell sibling of dewtrax/sinetrax, in a wholly different
+// register and mood. Same instrument family (FM sine bells + soft sine drones
+// + Schroeder reverb), new song: E minor, slow (84 BPM), earthy and grounded.
+// The character is mossy and woody — low soft bells with ratios near 2.0–3.0
+// (body, not glass) over deep sub drones, with long silences between events.
+// Nothing sparkles up high here; it sits in the low-mid, damp and patient.
+// No samples, no drums, no vocals — pure sine.
+// render-c.mjs --engine mosstrax masters it on the sine-family chain.
+//
+// Build:  cc -O3 -std=c11 -o mosstrax mosstrax.c -lm
+// Run:    ./mosstrax --out out/mosstrax-raw.wav
+
+#define _POSIX_C_SOURCE 200809L
+#include <stdio.h>
+#include <stdlib.h>
+#include <stdint.h>
+#include <string.h>
+#include <math.h>
+
+#ifndef M_PI
+#define M_PI 3.14159265358979323846
+#endif
+#define TAU (2.0 * M_PI)
+
+static const int SR = 48000;
+static double BPMV = 84, BEAT, BAR, SX;
+
+static uint32_t rng_s = 0x6d6f7373; // "moss"
+static inline double rnd(void) { rng_s ^= rng_s << 13; rng_s ^= rng_s >> 17; rng_s ^= rng_s << 5; return (double)rng_s / 4294967296.0; }
+static inline double rnd2(void) { return rnd() * 2.0 - 1.0; }
+static inline double midi_hz(double m) { return 440.0 * pow(2.0, (m - 69.0) / 12.0); }
+
+// ── swing / sway ────────────────────────────────────────────────────────────
+// Almost straight here (0.52) — mosstrax barely leans. The earth doesn't
+// hurry; events fall close to the grid with the faintest drag on the "&".
+static double SWING = 0.52;
+static double swing_beats(double beats) {
+    double e8 = beats * 2.0;                 // position in 8ths
+    long idx = (long)floor(e8 + 1e-9);
+    double frac = e8 - idx;
+    double pos = (idx / 2) * BEAT + ((idx & 1) ? SWING * BEAT : 0.0);
+    return pos + frac * (BEAT / 2.0);        // interpolate 16ths inside the 8th
+}
+
+static long N;
+static float *busL, *busR, *revL, *revR;
+static inline void adds(float *L, float *R, long i, double l, double r) { if (i >= 0 && i < N) { L[i] += (float)l; R[i] += (float)r; } }
+
+static int write_wav_f32_stereo(const char *path, const float *L, const float *R, long n) {
+    FILE *f = fopen(path, "wb"); if (!f) return 0;
+    uint32_t dsz = (uint32_t)(n * 8), riff = 36 + dsz, sr = SR, br = SR * 8, fsz = 16;
+    uint16_t fmt = 3, ch = 2, ba = 8, bits = 32;
+    fwrite("RIFF", 1, 4, f); fwrite(&riff, 4, 1, f); fwrite("WAVE", 1, 4, f);
+    fwrite("fmt ", 1, 4, f); fwrite(&fsz, 4, 1, f);
+    fwrite(&fmt, 2, 1, f); fwrite(&ch, 2, 1, f); fwrite(&sr, 4, 1, f);
+    fwrite(&br, 4, 1, f); fwrite(&ba, 2, 1, f); fwrite(&bits, 2, 1, f);
+    fwrite("data", 1, 4, f); fwrite(&dsz, 4, 1, f);
+    for (long i = 0; i < n; i++) { fwrite(&L[i], 4, 1, f); fwrite(&R[i], 4, 1, f); }
+    fclose(f); return 1;
+}
+
+// ── voices ────────────────────────────────────────────────────────────────
+// FM sine bell — carrier + a decaying modulator. With low `ratio` (2.0–3.0)
+// the partials cluster near the fundamental, giving a woody, hollow body
+// rather than a glassy chime; exp amp decay. The attack transient is gentle
+// here (mod index 2.2, slow mod-decay) so onsets are soft, not plinky.
+static void bell(float *L, float *R, double note, double t, double dur, double g, double pan, double ratio, double dec) {
+    double fc = midi_hz(note), fm = fc * ratio;
+    long n = (long)(dur * SR), s0 = (long)(t * SR);
+    double phc = 0, phm = 0, lg = 1 - pan * 0.5, rg = 1 + pan * 0.5;
+    long att = (long)(0.006 * SR);               // soft, woody onset (not a plink)
+    for (long i = 0; i < n; i++) {
+        double tt = (double)i / SR;
+        double env = exp(-tt * dec); if (i < att) env *= (double)i / att;
+        double mi = 2.2 * exp(-tt * 5.0);        // modest, slow-decaying transient — body over shimmer
+        phm += TAU * fm / SR;
+        phc += TAU * fc / SR + sin(phm) * mi / SR;
+        double v = sin(phc) * env * g;
+        adds(L, R, s0 + i, v * lg, v * rg);
+    }
+}
+
+// droplet — here it is reimagined as a "drip": a low-mid woody knock, not a
+// high sparkle. Short, rounded (ratio 2.0), with a soft reverb send so it
+// rings a moment in the damp space. Spelled to sit in the body of the mix.
+static void droplet(double note, double t, double g, double pan) {
+    bell(busL, busR, note, t, 0.85, g, pan, 2.0, 7.0);
+    bell(revL, revR, note, t, 0.85, g * 0.55, 0, 2.0, 7.0);
+}
+
+// soft sine drone — pad / sub bed with a slow raised-cosine attack/release.
+// A touch more upper-harmonic body (3rd/5th) for a reedy, organ-ish warmth
+// fitting the woody mood; very long fades so it breathes in and out.
+static void softsine(float *L, float *R, double note, double t, double dur, double g, double pan) {
+    double f = midi_hz(note); long n = (long)(dur * SR), s0 = (long)(t * SR);
+    long att = (long)(0.55 * SR), rel = (long)(0.80 * SR); double ph = 0, lg = 1 - pan * 0.5, rg = 1 + pan * 0.5;
+    for (long i = 0; i < n; i++) {
+        ph += TAU * f / SR;
+        double env = 1; if (i < att) env = (double)i / att; else if (i > n - rel) env = fmax(0, (double)(n - i) / rel);
+        double v = (sin(ph) + 0.20 * sin(ph * 2) + 0.10 * sin(ph * 3) + 0.04 * sin(ph * 5)) * env * g;
+        adds(L, R, s0 + i, v * lg, v * rg);
+    }
+}
+
+// a 4-voice sine pad chord (slightly panned for width), with a soft reverb send.
+static void pad_chord(double t, const int *midis, int nm, double dur, double g) {
+    for (int k = 0; k < nm; k++) { double pan = (k / fmax(1, nm - 1) - 0.5) * 0.6; softsine(busL, busR, midis[k], t, dur, g, pan); softsine(revL, revR, midis[k], t, dur, g * 0.45, 0); }
+}
+
+// ── harmony — E minor, a slow i–VI–iv–v wander (modal, grounded) ────────────
+// per-bar bass roots that the loop walks: Em, C, Am, Bm — earthy minor pull.
+static const int E_ROOTS[4] = { 52, 48, 45, 47 };       // E3, C3, A2, B2
+
+// four 4-note pad voicings, one per chord — low and close-spaced for warmth.
+static const int I_PAD[4]  = { 28, 35, 40, 47 };        // E min   (E B E B → E G B E body)
+static const int VI_PAD[4] = { 24, 31, 36, 43 };        // C maj   (C G C G body)
+static const int IV_PAD[4] = { 21, 28, 33, 40 };        // A min   (A E A E body)
+static const int V_PAD[4]  = { 23, 30, 35, 42 };        // B min/v (B F# B F# body)
+static const int *PADS[4] = { I_PAD, VI_PAD, IV_PAD, V_PAD };
+
+// E minor pentatonic (E G A B D), low-mid octave — for the woody bell motif.
+static const int PENT[5] = { 40, 43, 45, 47, 50 };
+// the "drip" palette — low-mid woody knocks (E3 G3 A3 B3 D4 E4), no high glass.
+static const int DROPS[6] = { 52, 55, 57, 59, 62, 64 };
+
+// section map. SECBARS drives every loop bound below. At 84 BPM a bar is
+// ~2.857s, so this 40-bar form lands at ~114s + reverb tail. Wave/outro
+// counts stay multiples of 4 so the 4-bar phrases (pad loop, motif) line up.
+static const char *ORDER[8] = { "soil", "moss", "groveA", "stillA", "groveB", "stillB", "groveC", "settle" };
+static const int SECBARS[8] = { 4, 4, 8, 4, 8, 4, 4, 4 };
+static int START[8];
+static int sec_index(const char *k) { for (int i = 0; i < 8; i++) if (!strcmp(ORDER[i], k)) return i; return 0; }
+
+// a woody knock — root + 5th, low and short, ratio 2.0 for hollow body.
+// (No octave-up sparkle; this is meant to thud, not chime.)
+static void knock(double t, int root, double g, int fifth) {
+    bell(busL, busR, root, t, BEAT * 2.0, g, -0.12, 2.0, 3.0);
+    if (fifth) bell(busL, busR, root + 7, t + 0.020, BEAT * 1.8, g * 0.55, 0.16, 2.5, 3.5);
+    bell(revL, revR, root, t, BEAT * 2.0, g * 0.4, 0, 2.0, 3.0);
+}
+
+// ── ornaments ───────────────────────────────────────────────────────────────
+// roll — a slow, sparse descending grace-run of n woody bells across `span`
+// seconds (a low flourish that settles downward, like something falling soft).
+static void roll(double t, double base, int n, int step, double span, double g) {
+    for (int i = 0; i < n; i++) bell(busL, busR, base + i * step, t + span * i / n, span * 1.6, g * (1.0 - 0.30 * i / n), rnd2() * 0.45, 2.5, 5.0);
+}
+
+int main(int argc, char **argv) {
+    const char *out_path = "out/mosstrax-raw.wav";
+    for (int i = 1; i < argc; i++) { if (!strcmp(argv[i], "--out") && i + 1 < argc) out_path = argv[++i]; else if (!strcmp(argv[i], "--bpm") && i + 1 < argc) BPMV = atof(argv[++i]); else if (!strcmp(argv[i], "--swing") && i + 1 < argc) SWING = atof(argv[++i]); }
+    BEAT = 60.0 / BPMV; BAR = BEAT * 4; SX = BEAT / 4;
+    { int c = 0; for (int i = 0; i < 8; i++) { START[i] = c; c += SECBARS[i]; } }
+    int TB = 0; for (int i = 0; i < 8; i++) TB += SECBARS[i];
+    double totalSec = TB * BAR + 8.0; N = (long)(totalSec * SR);
+    busL = calloc(N, 4); busR = calloc(N, 4); revL = calloc(N, 4); revR = calloc(N, 4);
+    fprintf(stderr, "# mosstrax.c · %g BPM · %d bars · %.1fs · E minor woody sine bells\n", BPMV, TB, totalSec);
+
+    // the woody bell motif, as {phrase-bar, beat, note} — a low, drifting
+    // E-minor-pentatonic phrase that rises a little and sinks back, with long
+    // gaps between notes (the form leaves space to breathe).
+    double MOTIF[6][3] = { {0,0,52},{0,3,55},{1,2,57},{2,0,59},{2,3,55},{3,1.5,52} };
+
+    // ── SOIL (just sub + one low pad — almost empty, the ground settling) ──
+    { int idx = sec_index("soil"); int c = START[idx], nb = SECBARS[idx], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, I_PAD, 4, BAR * h - 0.05, 0.11);
+        pad_chord(t0 + BAR * h, IV_PAD, 4, BAR * (nb - h) - 0.05, 0.10);
+        for (int b = 0; b < nb; b++) softsine(busL, busR, 28, t0 + b * BAR, BAR * 0.97, 0.13, 0); // deep sub through the whole intro
+        // one lone woody bell near the end, far apart from anything else
+        bell(busL, busR, 52, t0 + BAR * (nb - 1) + BEAT * 1.0, BAR * 1.2, 0.12, rnd2() * 0.25, 2.0, 2.0);
+    }
+
+    // ── MOSS — the motif emerges, sparse drips, pad climb into the first grove ─
+    { int idx = sec_index("moss"); int c = START[idx], nb = SECBARS[idx], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, VI_PAD, 4, BAR * h - 0.05, 0.12);
+        pad_chord(t0 + BAR * h, V_PAD, 4, BAR * (nb - h) - 0.05, 0.13);
+        for (int b = 0; b < nb; b++) softsine(busL, busR, b < h ? 24 : 23, t0 + b * BAR, BAR * 0.95, 0.11, 0);
+        for (int z = 0; z < 6; z++) { int b = (int)MOTIF[z][0]; if (b >= nb) continue; double tt = t0 + b * BAR + swing_beats(MOTIF[z][1]); bell(busL, busR, MOTIF[z][2], tt, BEAT * 1.6, 0.11, rnd2() * 0.35, 2.5, 3.0); bell(revL, revR, MOTIF[z][2], tt, BEAT * 1.6, 0.05, 0, 2.5, 3.0); }
+        for (int b = 1; b < nb; b += 2) if (rnd() < 0.6) droplet(DROPS[(int)(rnd() * 4)], t0 + b * BAR + 2.5 * BEAT, 0.06, rnd2() * 0.5);
+        roll(t0 + BAR * nb - BEAT * 2, 59, 4, -2, BEAT * 1.8, 0.06);   // a soft descent into grove A
+    }
+
+    // ── helper for the three groves (slow, sparse, never busy) ──
+    const char *groves[3] = { "groveA", "groveB", "groveC" };
+    for (int d = 0; d < 3; d++) {
+        int wi = sec_index(groves[d]); int c = START[wi], nbw = SECBARS[wi]; int big = d == 2;
+        for (int b = 0; b < nbw; b++) {
+            double t0 = (c + b) * BAR; int root = E_ROOTS[b % 4]; int phrase = b % 4 == 0;
+            // a slow, soft bass heartbeat — beats 1 & 3 only, woody and low.
+            for (int e = 0; e < 4; e++) { double tt = t0 + swing_beats(e * 1.0); int on = (e % 2 == 0); if (on) bell(busL, busR, root - 12, tt, BEAT * 1.4, 0.11, on ? -0.06 : 0.20, 2.0, 4.0); }
+            // sustained sub body (one per bar, under the heartbeat)
+            softsine(busL, busR, root - 12, t0, BAR * 0.96, 0.12, 0);
+            // the woody knock on beat 3 (sparser than dewtrax's stab)
+            if (b % 2 == 0) knock(t0 + BEAT * 2, root, big ? 0.15 : 0.12, 1);
+            // pad sustain every 4 bars (chord follows the loop)
+            if (phrase) pad_chord(t0, PADS[(b / 4) % 4], 4, BAR * 4 - 0.05, 0.085);
+            // the woody bell motif (4-bar phrase) — low, plain, with gaps
+            for (int z = 0; z < 6; z++) if ((int)MOTIF[z][0] == b % 4) {
+                double note = MOTIF[z][2], tt = t0 + swing_beats(MOTIF[z][1]);
+                bell(busL, busR, note, tt, BEAT * 1.5, big ? 0.13 : 0.10, rnd2() * 0.35, 2.5, 3.2);
+                bell(revL, revR, note, tt, BEAT * 1.5, 0.06, 0, 2.5, 3.2);
+            }
+            // a lone pentatonic drip — only sometimes, deep in the off-beat
+            if (b % 2 == 1 && rnd() < 0.5) bell(busL, busR, PENT[b % 5] + 12, t0 + swing_beats(2.5), BEAT * 1.0, 0.06, rnd2() * 0.45, 2.0, 4.0);
+            // drips — sprinkled, a touch denser in the big grove but still spare
+            int ndrops = big ? 2 : 1;
+            for (int k = 0; k < ndrops; k++) if (rnd() < 0.45) droplet(DROPS[(int)(rnd() * 6)], t0 + swing_beats((int)(rnd() * 4) * 1.0 + 0.5), 0.05, rnd2() * 0.55);
+            // a soft descending roll at phrase ends of the big grove
+            if (big && b % 4 == 3) roll(t0 + BEAT * 2, 64, 4, -3, BEAT * 1.6, 0.06);
+        }
+        // a low choir-ish sine bed through the biggest grove (warm undertow)
+        if (big) for (int b = 0; b < nbw; b += 2) { double t0 = (c + b) * BAR; int ns[3] = { I_PAD[1], I_PAD[2], I_PAD[3] }; for (int z = 0; z < 3; z++) softsine(revL, revR, ns[z], t0, BAR * 2, 0.045, (z - 1) * 0.4); }
+    }
+
+    // ── STILLS — most spacious of all: pad + half-time sub + one or two bells ──
+    const char *still[2] = { "stillA", "stillB" };
+    for (int z2 = 0; z2 < 2; z2++) {
+        int hi = sec_index(still[z2]); int c = START[hi], nb = SECBARS[hi], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, IV_PAD, 4, BAR * h - 0.05, 0.12);
+        pad_chord(t0 + BAR * h, V_PAD, 4, BAR * (nb - h) - 0.05, 0.12);
+        for (int b = 0; b < nb; b++) { softsine(busL, busR, b < h ? 21 : 23, t0 + b * BAR, BAR * 0.88, 0.12, 0); if (b % 2 == 0) bell(busL, busR, I_PAD[1 + (b / 2) % 3] + 12, t0 + b * BAR + BEAT, BAR * 0.9, 0.10, rnd2() * 0.35, 2.0, 2.4); if (rnd() < 0.5) droplet(DROPS[(int)(rnd() * 5)], t0 + b * BAR + 2.5 * BEAT, 0.045, rnd2() * 0.55); }
+        if (z2 == 1) roll(t0 + BAR * (nb - 1), 59, 5, -2, BEAT * 2.4, 0.05); // a slow settling descent into grove C
+    }
+
+    // ── SETTLE — decaying bells + pad wash + a final deep bell, sinking out ──
+    { int idx = sec_index("settle"); int c = START[idx], nb = SECBARS[idx], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, I_PAD, 4, BAR * h - 0.05, 0.12);
+        pad_chord(t0 + BAR * h, VI_PAD, 4, BAR * (nb - h) - 0.05, 0.10);
+        for (int b = 0; b < nb; b++) { double e = fmax(0.1, 1.0 - (double)b / nb); int root = b < h ? 52 : 48; softsine(busL, busR, root - 12, t0 + b * BAR, BAR * 0.9, 0.12 * e, 0); if (b % 2 == 0) knock(t0 + b * BAR + BEAT * 2, root, 0.10 * e, 1); if (rnd() < 0.45) droplet(DROPS[(int)(rnd() * 5)], t0 + b * BAR + 1.5 * BEAT, 0.035 * e, rnd2() * 0.55); }
+        // final low bell — the ground exhaling, very long and round
+        bell(busL, busR, 28, t0 + BAR * (nb - 2), 6.0, 0.20, 0, 2.0, 1.0);
+        bell(busL, busR, 40, t0 + BAR * (nb - 2), 6.0, 0.11, 0.15, 2.5, 1.2);
+        bell(revL, revR, 35, t0 + BAR * (nb - 2), 6.0, 0.11, 0, 2.0, 1.1);
+    }
+
+    // ── REVERB (Schroeder) — a wide, damp, cave-like space for the woody bells.
+    // Longer decay + heavier damping than dewtrax → dark, mossy tail, no fizz. ─
+    {
+        double decay = 0.85, wet = 0.50, damp = 0.55;
+        int CD[6]; double cds[6] = { 0.0311, 0.0383, 0.0427, 0.0461, 0.0523, 0.0613 };
+        for (int k = 0; k < 6; k++) CD[k] = (int)(cds[k] * SR);
+        int AD[2] = { (int)(0.005 * SR), (int)(0.0017 * SR) }; double apFb = 0.5;
+        float *cbL[6], *cbR[6]; int ciL[6] = {0}, ciR[6] = {0}; double cLPL[6] = {0}, cLPR[6] = {0};
+        for (int k = 0; k < 6; k++) { cbL[k] = calloc(CD[k], 4); cbR[k] = calloc(CD[k], 4); }
+        float *abL[2], *abR[2]; int aiL[2] = {0}, aiR[2] = {0};
+        for (int k = 0; k < 2; k++) { abL[k] = calloc(AD[k], 4); abR[k] = calloc(AD[k], 4); }
+        for (long i = 0; i < N; i++) {
+            double inL = revL[i], inR = revR[i], cL = 0, cR = 0;
+            for (int k = 0; k < 6; k++) {
+                double dL = cbL[k][ciL[k]], dR = cbR[k][ciR[k]]; cL += dL; cR += dR;
+                cLPL[k] = dL * (1 - damp) + cLPL[k] * damp; cLPR[k] = dR * (1 - damp) + cLPR[k] * damp;
+                cbL[k][ciL[k]] = (float)(inL + cLPL[k] * decay); cbR[k][ciR[k]] = (float)(inR + cLPR[k] * decay);
+                ciL[k] = (ciL[k] + 1) % CD[k]; ciR[k] = (ciR[k] + 1) % CD[k];
+            }
+            cL /= 6; cR /= 6;
+            for (int k = 0; k < 2; k++) {
+                double dL = abL[k][aiL[k]], dR = abR[k][aiR[k]];
+                double oL = -apFb * cL + dL, oR = -apFb * cR + dR;
+                abL[k][aiL[k]] = (float)(cL + apFb * oL); abR[k][aiR[k]] = (float)(cR + apFb * oR);
+                aiL[k] = (aiL[k] + 1) % AD[k]; aiR[k] = (aiR[k] + 1) % AD[k];
+                cL = oL; cR = oR;
+            }
+            busL[i] += (float)(cL * wet); busR[i] += (float)(cR * wet);
+        }
+        for (int k = 0; k < 6; k++) { free(cbL[k]); free(cbR[k]); }
+        for (int k = 0; k < 2; k++) { free(abL[k]); free(abR[k]); }
+    }
+
+    // ── normalize + gentle in/out fades (long, to suit the slow mood) ──
+    double peak = 0; for (long i = 0; i < N; i++) { double a = fmax(fabs(busL[i]), fabs(busR[i])); if (a > peak) peak = a; }
+    if (peak > 0) { double g = 0.85 / peak; for (long i = 0; i < N; i++) { busL[i] *= (float)g; busR[i] *= (float)g; } }
+    long fin = (long)(3.5 * SR), fout = (long)(6.0 * SR);
+    for (long i = 0; i < fin && i < N; i++) { double g = 0.5 - 0.5 * cos(M_PI * (double)i / fin); busL[i] *= (float)g; busR[i] *= (float)g; }
+    for (long i = 0; i < fout && i < N; i++) { double g = 0.5 - 0.5 * cos(M_PI * (double)i / fout); long idx = N - 1 - i; busL[idx] *= (float)g; busR[idx] *= (float)g; }
+
+    if (!write_wav_f32_stereo(out_path, busL, busR, N)) { fprintf(stderr, "✗ write failed\n"); return 1; }
+    fprintf(stderr, "✓ %s · %.1fs\n", out_path, (double)N / SR);
+    return 0;
+}
diff --git a/pop/maytrax/c/render-c.mjs b/pop/maytrax/c/render-c.mjs
new file mode 100644
index 000000000..4090f8fe4
--- /dev/null
+++ b/pop/maytrax/c/render-c.mjs
@@ -0,0 +1,94 @@
+#!/usr/bin/env node
+// render-c.mjs — the C-backend render flow (hellsine / americomputadora
+// pattern): bake (JS preps score.h) → cc → ./maytrax (C renders the song to
+// a float32 stereo WAV) → ffmpeg pop-master (the same MASTER chain as
+// bin/maytrax.mjs: tonal EQ + glue comp + soft-clip + width, then loudnorm +
+// alimiter) → mp3.
+//
+// usage: node c/render-c.mjs [--no-bake] [--out ../out/maytrax.mp3] [--wav x.wav]
+
+import { spawnSync } from "node:child_process";
+import { mkdirSync } from "node:fs";
+import { dirname, join, resolve } from "node:path";
+import { fileURLToPath } from "node:url";
+import { homedir } from "node:os";
+
+const HERE = dirname(fileURLToPath(import.meta.url));
+const ROOT = dirname(HERE); // pop/maytrax
+
+const argv = process.argv.slice(2);
+const flags = {};
+for (let i = 0; i < argv.length; i++) {
+  const a = argv[i];
+  if (a.startsWith("--")) { const k = a.slice(2), n = argv[i + 1]; if (n !== undefined && !n.startsWith("--")) { flags[k] = n; i++; } else flags[k] = true; }
+}
+const expand = (p) => (p && p.startsWith("~/") ? resolve(homedir(), p.slice(2)) : p);
+// --sine renders the sinetrax fork (pure sine-bell, no samples/drums/vocals).
+// --engine <name> renders any sine-family fork (dewtrax, mosstrax, …): a
+// self-contained <name>.c that needs no bake and masters on the sine chain.
+const SINE = !!flags.sine;
+const ENGINE = (typeof flags.engine === "string" && flags.engine) || (SINE ? "sinetrax" : "maytrax");
+// everything except the sample/drum/vocal maytrax engine is sine-family.
+const SINEFAM = SINE || ENGINE !== "maytrax";
+const outMp3 = resolve(expand(flags.out) ?? join(ROOT, "out", `${ENGINE}.mp3`));
+mkdirSync(dirname(outMp3), { recursive: true });
+mkdirSync(join(HERE, "out"), { recursive: true });
+
+function run(label, cmd, args, opts = {}) {
+  console.log(`# ${label}`);
+  const r = spawnSync(cmd, args, { stdio: "inherit", ...opts });
+  if (r.status !== 0) { console.error(`✗ ${label} failed`); process.exit(1); }
+}
+
+if (!SINEFAM && !flags["no-bake"]) run("bake (score.h)", "node", [join(HERE, "bake.mjs")]);
+run("cc", "cc", ["-O3", "-std=c11", "-Wall", "-Wextra", "-Wno-unused-parameter", "-o", join(HERE, ENGINE), join(HERE, `${ENGINE}.c`), "-lm"]);
+
+const rawWav = join(HERE, "out", `${ENGINE}-raw.wav`);
+run("render (C engine)", join(HERE, ENGINE), ["--out", rawWav]);
+
+// ── pop master chain (ported from bin/maytrax.mjs) ────────────────────────
+// chiller, warmer, more dynamic master than the old hot pop chain: lower
+// loudness target (room to breathe), softer presence, gentle air, a glue
+// comp with a slow attack so transients punch through, and a soft limiter.
+const MASTER_CORE = [
+  "highpass=f=30",
+  "equalizer=f=55:t=q:w=0.8:g=1.4",        // tight sub weight
+  "equalizer=f=300:t=q:w=1.1:g=-1.0",      // gentle de-mud (warm)
+  "equalizer=f=3200:t=q:w=1.6:g=0.6",      // barely-there presence
+  "equalizer=f=8500:t=q:w=0.8:g=-1.6",     // tame harsh upper-treble (smooth)
+  "treble=g=-0.6:f=11000",                 // gentle high-shelf DOWN — de-harsh
+  "lowpass=f=16500",                       // shave the brittle top
+  "acompressor=threshold=-20dB:ratio=2.0:attack=30:release=260:makeup=2.2:knee=8", // smooth glue; slow attack keeps the groove punching
+  "asoftclip=type=tanh:threshold=0.98",    // minimal density
+  "stereotools=slev=1.04",                 // tighter width
+].join(",");
+// quiet, slow entrance — a 13s fade-in AFTER the limiter so loudnorm can't
+// pull the intro back up. cub (cubic) stays very quiet early then rises into
+// the build, so the opening sounds stay soft far longer than a linear ramp.
+const INTRO_FADE = "afade=t=in:curve=cub:st=0:d=13";
+// sinetrax is gentle bells (and fades itself) — master it softer + more
+// dynamic with no extra fade; maytrax gets the slow cubic intro fade.
+const MASTER_MP3 = SINEFAM
+  ? `${MASTER_CORE},loudnorm=I=-13:TP=-1.5:LRA=13,alimiter=limit=0.95:attack=8:release=120`
+  : `${MASTER_CORE},loudnorm=I=-11:TP=-1.5:LRA=11,alimiter=limit=0.93:attack=5:release=90,${INTRO_FADE}`;
+
+run("master (ffmpeg) → mp3", "ffmpeg", [
+  "-hide_banner", "-y", "-loglevel", "error",
+  "-i", rawWav, "-af", MASTER_MP3,
+  "-c:a", "libmp3lame", "-b:a", "320k",
+  "-metadata", `title=${ENGINE}`, "-metadata", "artist=jeffrey", "-metadata", "album=pixsies",
+  outMp3,
+]);
+console.log(`✓ ${outMp3} (pop-mastered · 320k · stereo)`);
+
+const wavOut = expand(flags.wav);
+if (wavOut) {
+  mkdirSync(dirname(wavOut), { recursive: true });
+  run("master → DistroKid wav", "ffmpeg", [
+    "-hide_banner", "-y", "-loglevel", "error",
+    "-i", rawWav,
+    "-af", `${MASTER_CORE},loudnorm=I=-14:TP=-1.5:LRA=11,alimiter=limit=0.95:attack=3:release=55`,
+    "-ar", "44100", "-ac", "2", "-c:a", "pcm_s16le", wavOut,
+  ]);
+  console.log(`✓ ${wavOut} (DistroKid master · 44.1k/16-bit · -14 LUFS)`);
+}
diff --git a/pop/maytrax/c/score.h b/pop/maytrax/c/score.h
new file mode 100644
index 000000000..6f23841c3
--- /dev/null
+++ b/pop/maytrax/c/score.h
@@ -0,0 +1,64 @@
+// score.h — generated by c/bake.mjs. do not hand-edit.
+#define SCORE_BPM 160
+#define SCORE_SR 48000
+
+#define N_ROLES 25
+static const char *ROLE_NAME[N_ROLES] = {
+  "taiko", "gong", "choir", "brass", "strings", "bass", "ghost", "hat", "ohat", "ride", "shaker", "sub", "reese", "lead", "pad", "kick", "snare", "animal", "wolf", "cowbell", "tom", "click", "rain", "jungle", "cricket"
+};
+static const char *ROLE_PATH[N_ROLES] = {
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/82712-taiko_drum_001_wav.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/518292-gong_2_wav.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/162168-aah2_wav.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/820070-cm_orch_hit_3_infernal_dance_2_207s.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/758483-arc_c.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/560208-layered_bass_05_quick_synth_wav.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/46567-ludwig_black_beauty_snare_ghost_notes_unprocesse.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/509971-hi_hat_closed_9_mp3.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/509984-hi_hat_open_1_mp3.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/799423-ride_bell_1_long.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/375636-shaker_shake5_wav.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/6291-ppg_016_subfrequent_g_2_wav.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/424432-angryreesebassf0160bpm_wav.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/257363-overall_quality_of_single_note_flute_c4.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/46127-k_wstr_wav.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/337827-kick_short_tail_174_bpm_02_wav.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/118312-lr_sn_0029_wav.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/571287-jaguar_growl_roar_wav.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/429109-15_wolfcrying_wav.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/75338-cowbell_wav.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/581462-fractanimal_acoustic_drum_kit_mid_tom_2_wav.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/375399-snare_sfx_click_wav.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/371710-raining.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/644989-jungle_forest_ambience.wav",
+  "/Users/jas/aesthetic-computer-vault/personal/pop/freesound-cache/710399-landscape_nl_march_1131am_230302_0566.wav",
+};
+static const int ROLE_PITCHED[N_ROLES] = {
+  0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0
+};
+// nominal root midi from kit.json (rateFor path); -1 = unpitched
+static const int ROLE_NOMINAL[N_ROLES] = {
+  -1, -1, 60, 48, 60, 36, -1, -1, -1, -1, -1, 24, 36, 60, 48, -1, -1, 48, 57, -1, -1, -1, -1, -1, -1
+};
+
+static const char *BELL_PATH = "/Users/jas/aesthetic-computer/pop/hellsine/samples/church-bell.wav";
+
+#define N_SHOUTS 6
+static const char *SHOUT_KEY[N_SHOUTS] = { "wake", "real", "hold", "let", "rabbit", "now" };
+static const char *SHOUT_J[N_SHOUTS] = {
+  "/Users/jas/aesthetic-computer/pop/maytrax/out/shouts/wake_up.wav",
+  "/Users/jas/aesthetic-computer/pop/maytrax/out/shouts/it_s_real.wav",
+  "/Users/jas/aesthetic-computer/pop/maytrax/out/shouts/hold_on.wav",
+  "/Users/jas/aesthetic-computer/pop/maytrax/out/shouts/let_go.wav",
+  "/Users/jas/aesthetic-computer/pop/maytrax/out/shouts/follow_the_white_rabbit.wav",
+  "/Users/jas/aesthetic-computer/pop/maytrax/out/shouts/now.wav",
+};
+static const char *SHOUT_A[N_SHOUTS] = {
+  "/Users/jas/aesthetic-computer/pop/maytrax/out/shouts/wake_up-say-sung.wav",
+  "/Users/jas/aesthetic-computer/pop/maytrax/out/shouts/it_s_real-say-sung.wav",
+  "/Users/jas/aesthetic-computer/pop/maytrax/out/shouts/hold_on-say-sung.wav",
+  "/Users/jas/aesthetic-computer/pop/maytrax/out/shouts/let_go-say-sung.wav",
+  "/Users/jas/aesthetic-computer/pop/maytrax/out/shouts/follow_the_white_rabbit-say-sung.wav",
+  "/Users/jas/aesthetic-computer/pop/maytrax/out/shouts/now-say-sung.wav",
+};
+
diff --git a/pop/maytrax/c/sinetrax b/pop/maytrax/c/sinetrax
new file mode 100755
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diff --git a/pop/maytrax/c/sinetrax.c b/pop/maytrax/c/sinetrax.c
new file mode 100644
index 000000000..05887edd6
--- /dev/null
+++ b/pop/maytrax/c/sinetrax.c
@@ -0,0 +1,258 @@
+// sinetrax.c — a sine-bell-only fork of maytrax. Same 88-bar F-minor form,
+// same section map (intro → build → drop → break → … → outro), but every
+// voice is a pure FM sine bell or a soft sine drone. No samples, no drums,
+// no vocals — pure instrumental, meditative. Schroeder reverb glues the
+// bells into a wide glassy space; render-c.mjs --sine masters it.
+//
+// Build:  cc -O3 -std=c11 -o sinetrax sinetrax.c -lm
+// Run:    ./sinetrax --out out/sine-raw.wav
+
+#define _POSIX_C_SOURCE 200809L
+#include <stdio.h>
+#include <stdlib.h>
+#include <stdint.h>
+#include <string.h>
+#include <math.h>
+
+#ifndef M_PI
+#define M_PI 3.14159265358979323846
+#endif
+#define TAU (2.0 * M_PI)
+
+static const int SR = 48000;
+static double BPMV = 160, BEAT, BAR, SX;
+
+static uint32_t rng_s = 0x73696e65; // "sine"
+static inline double rnd(void) { rng_s ^= rng_s << 13; rng_s ^= rng_s >> 17; rng_s ^= rng_s << 5; return (double)rng_s / 4294967296.0; }
+static inline double rnd2(void) { return rnd() * 2.0 - 1.0; }
+static inline double midi_hz(double m) { return 440.0 * pow(2.0, (m - 69.0) / 12.0); }
+
+// ── swing / sway ────────────────────────────────────────────────────────────
+// SWING = the fraction of the beat where the off-8th lands. 0.5 is straight,
+// 0.667 is a triplet shuffle, >0.70 is an extreme lurch/sway. swing_beats()
+// maps a straight beat-position to its swung time: on-beats hold, the "&"s
+// are dragged late.
+static double SWING = 0.72;
+static double swing_beats(double beats) {
+    double e8 = beats * 2.0;                 // position in 8ths
+    long idx = (long)floor(e8 + 1e-9);
+    double frac = e8 - idx;
+    double pos = (idx / 2) * BEAT + ((idx & 1) ? SWING * BEAT : 0.0);
+    return pos + frac * (BEAT / 2.0);        // interpolate 16ths inside the 8th
+}
+
+static long N;
+static float *busL, *busR, *revL, *revR;
+static inline void adds(float *L, float *R, long i, double l, double r) { if (i >= 0 && i < N) { L[i] += (float)l; R[i] += (float)r; } }
+
+static int write_wav_f32_stereo(const char *path, const float *L, const float *R, long n) {
+    FILE *f = fopen(path, "wb"); if (!f) return 0;
+    uint32_t dsz = (uint32_t)(n * 8), riff = 36 + dsz, sr = SR, br = SR * 8, fsz = 16;
+    uint16_t fmt = 3, ch = 2, ba = 8, bits = 32;
+    fwrite("RIFF", 1, 4, f); fwrite(&riff, 4, 1, f); fwrite("WAVE", 1, 4, f);
+    fwrite("fmt ", 1, 4, f); fwrite(&fsz, 4, 1, f);
+    fwrite(&fmt, 2, 1, f); fwrite(&ch, 2, 1, f); fwrite(&sr, 4, 1, f);
+    fwrite(&br, 4, 1, f); fwrite(&ba, 2, 1, f); fwrite(&bits, 2, 1, f);
+    fwrite("data", 1, 4, f); fwrite(&dsz, 4, 1, f);
+    for (long i = 0; i < n; i++) { fwrite(&L[i], 4, 1, f); fwrite(&R[i], 4, 1, f); }
+    fclose(f); return 1;
+}
+
+// ── voices ────────────────────────────────────────────────────────────────
+// FM sine bell — carrier + a decaying modulator gives the glassy partial
+// shimmer; exp amp decay. `ratio` shapes the timbre (3.5 = bell, 2.0 = softer).
+static void bell(float *L, float *R, double note, double t, double dur, double g, double pan, double ratio, double dec) {
+    double fc = midi_hz(note), fm = fc * ratio;
+    long n = (long)(dur * SR), s0 = (long)(t * SR);
+    double phc = 0, phm = 0, lg = 1 - pan * 0.5, rg = 1 + pan * 0.5;
+    long att = (long)(0.0012 * SR);              // sharp, punctuated onset
+    for (long i = 0; i < n; i++) {
+        double tt = (double)i / SR;
+        double env = exp(-tt * dec); if (i < att) env *= (double)i / att;
+        double mi = 5.0 * exp(-tt * 11.0);       // brighter, faster-decaying attack transient
+        phm += TAU * fm / SR;
+        phc += TAU * fc / SR + sin(phm) * mi / SR;
+        double v = sin(phc) * env * g;
+        adds(L, R, s0 + i, v * lg, v * rg);
+    }
+}
+
+// soft sine drone — pad / sub bed with a slow raised-cosine attack/release.
+static void softsine(float *L, float *R, double note, double t, double dur, double g, double pan) {
+    double f = midi_hz(note); long n = (long)(dur * SR), s0 = (long)(t * SR);
+    long att = (long)(0.30 * SR), rel = (long)(0.45 * SR); double ph = 0, lg = 1 - pan * 0.5, rg = 1 + pan * 0.5;
+    for (long i = 0; i < n; i++) {
+        ph += TAU * f / SR;
+        double env = 1; if (i < att) env = (double)i / att; else if (i > n - rel) env = fmax(0, (double)(n - i) / rel);
+        double v = (sin(ph) + 0.16 * sin(ph * 2) + 0.06 * sin(ph * 3)) * env * g;
+        adds(L, R, s0 + i, v * lg, v * rg);
+    }
+}
+
+// a 3-voice sine pad chord (slightly detuned for width).
+static void pad_chord(double t, const int *midis, int nm, double dur, double g) {
+    for (int k = 0; k < nm; k++) { double pan = (k / fmax(1, nm - 1) - 0.5) * 0.6; softsine(busL, busR, midis[k], t, dur, g, pan); softsine(revL, revR, midis[k], t, dur, g * 0.4, 0); }
+}
+
+// ── harmony (shared with maytrax) ──────────────────────────────────────────
+static const int FM_ROOTS[4] = { 53, 51, 49, 48 };
+static const int FM_PAD[4] = { 41, 53, 56, 60 };
+static const int EB_PAD[4] = { 39, 51, 54, 58 };
+static const int DB_PAD[4] = { 37, 49, 52, 56 };
+static const int C_PAD[4]  = { 36, 48, 51, 55 };
+
+static const char *ORDER[8] = { "intro", "buildA", "drop1", "breakA", "drop2", "breakB", "drop3", "outro" };
+static const int SECBARS[8] = { 8, 4, 16, 8, 16, 8, 16, 12 };
+static int START[8];
+static int sec_index(const char *k) { for (int i = 0; i < 8; i++) if (!strcmp(ORDER[i], k)) return i; return 0; }
+
+// a melodic bell stab — root + 5th + octave, tight + punctuated now.
+static void stab(double t, int root, double g, int triad) {
+    bell(busL, busR, root, t, BEAT * 1.2, g, -0.15, 3.5, 6.5);
+    bell(busL, busR, root + 7, t + 0.010, BEAT * 1.2, g * 0.7, 0.18, 3.5, 6.5);
+    if (triad) bell(busL, busR, root + 12, t + 0.020, BEAT * 1.1, g * 0.5, 0.0, 3.0, 7.5);
+    bell(revL, revR, root + 7, t, BEAT * 1.2, g * 0.4, 0, 3.5, 6.5);
+}
+
+// ── ornaments ───────────────────────────────────────────────────────────────
+// frill — a quick grace-run of n bells stepping by `step` semitones across
+// `span` seconds (a sparkly flourish for high points / pickups).
+static void frill(double t, double base, int n, int step, double span, double g) {
+    for (int i = 0; i < n; i++) bell(busL, busR, base + i * step, t + span * i / n, span * 1.4, g * (1.0 - 0.35 * i / n), rnd2() * 0.5, 3.5, 13.0);
+}
+// triplet — three quick bells over one beat (middle lifted a 3rd), for
+// accents on the downbeats / climaxes.
+static void triplet(double t, double note, double g) {
+    for (int i = 0; i < 3; i++) bell(busL, busR, note + (i == 1 ? 3 : 0), t + BEAT * i / 3.0, BEAT / 3.0 * 1.2, g * (i == 1 ? 1.1 : 1.0), (i - 1) * 0.25, 3.5, 12.0);
+}
+
+int main(int argc, char **argv) {
+    const char *out_path = "out/sine-raw.wav";
+    for (int i = 1; i < argc; i++) { if (!strcmp(argv[i], "--out") && i + 1 < argc) out_path = argv[++i]; else if (!strcmp(argv[i], "--bpm") && i + 1 < argc) BPMV = atof(argv[++i]); else if (!strcmp(argv[i], "--swing") && i + 1 < argc) SWING = atof(argv[++i]); }
+    BEAT = 60.0 / BPMV; BAR = BEAT * 4; SX = BEAT / 4;
+    { int c = 0; for (int i = 0; i < 8; i++) { START[i] = c; c += SECBARS[i]; } }
+    int TB = 0; for (int i = 0; i < 8; i++) TB += SECBARS[i];
+    double totalSec = TB * BAR + 6.0; N = (long)(totalSec * SR);
+    busL = calloc(N, 4); busR = calloc(N, 4); revL = calloc(N, 4); revR = calloc(N, 4);
+    fprintf(stderr, "# sinetrax.c · %g BPM · %d bars · %.1fs · sine bells\n", BPMV, TB, totalSec);
+
+    // the lead melody (shared with maytrax), as pluck bells.
+    double LEAD[8][3] = { {0,0,65},{0,2,72},{1,0,75},{1,1,72},{1,2,68},{2,0,65},{2,2,68},{3,0,72} };
+    int pent[8] = { 53, 56, 58, 60, 63, 60, 58, 56 };
+
+    // ── INTRO (staggered: pad → bell melody → sub → high tinges) ──
+    { int c = START[sec_index("intro")]; double t0 = c * BAR;
+        pad_chord(t0, FM_PAD, 4, BAR * 4 - 0.05, 0.10);
+        pad_chord(t0 + BAR * 4, EB_PAD, 4, BAR * 4 - 0.05, 0.11);
+        int mel[4] = { 77, 72, 68, 65 };                       // bar 2: descending bell melody
+        for (int b = 0; b < 4; b++) bell(busL, busR, mel[b], t0 + (2 + b) * BAR, BAR * 0.9, 0.14, rnd2() * 0.3, 3.0, 3.0);
+        for (int b = 4; b < 8; b++) softsine(busL, busR, 29, t0 + b * BAR, BAR * 0.95, 0.12, 0); // bar 4: sub
+        for (int b = 6; b < 8; b++) bell(busL, busR, 84 + (b & 1) * 3, t0 + b * BAR + 2 * BEAT, BEAT, 0.05, rnd2() * 0.6, 4.0, 6.0); // bar 6: high tinge
+    }
+
+    // ── BUILD A — rising bell arpeggio + pad climb ──
+    { int c = START[sec_index("buildA")]; double t0 = c * BAR;
+        pad_chord(t0, DB_PAD, 4, BAR * 2 - 0.05, 0.13);
+        pad_chord(t0 + BAR * 2, C_PAD, 4, BAR * 2 - 0.05, 0.15);
+        int arp[8] = { 48, 53, 56, 60, 63, 68, 72, 75 };
+        for (int s = 0; s < 16; s++) { double tt = t0 + BAR * 2 + swing_beats(s * 0.25); bell(busL, busR, arp[s % 8] + (s / 8) * 12, tt, SX * 2.2, 0.06 + 0.07 * s / 16.0, rnd2() * 0.4, 3.0, 9.0); }
+        frill(t0 + BAR * 3 + BEAT * 2, 72, 8, 2, BEAT * 1.8, 0.07);   // ascending frill flourish into the drop
+    }
+
+    // ── helper for the three drops ──
+    const char *drops[3] = { "drop1", "drop2", "drop3" };
+    for (int d = 0; d < 3; d++) {
+        int c = START[sec_index(drops[d])]; int big = d == 2;
+        for (int b = 0; b < 16; b++) {
+            double t0 = (c + b) * BAR; int root = FM_ROOTS[b % 4]; int phrase = b % 4 == 0;
+            // swung 8th pulse — on-beats firm, the "&"s dragged late + softer.
+            for (int e = 0; e < 8; e++) { double tt = t0 + swing_beats(e * 0.5); int on = (e % 2 == 0); bell(busL, busR, root - 12, tt, BEAT * 0.4, on ? 0.11 : 0.07, on ? -0.08 : 0.22, 2.0, on ? 13.0 : 16.0); }
+            // sustained sub body (one per bar, under the swing)
+            softsine(busL, busR, root - 12, t0, BAR * 0.95, 0.10, 0);
+            // the stab walk on beat 3
+            stab(t0 + BEAT * 2, root, big ? 0.20 : 0.16, big);
+            // pad sustain every 4 bars
+            if (phrase) pad_chord(t0, FM_PAD, 4, BAR * 4 - 0.05, 0.07);
+            // accent ornament — a triplet burst on the phrase-start downbeat
+            if (phrase) triplet(t0, root + 12, big ? 0.09 : 0.07);
+            // lead pluck bells (4-bar phrase) — swung, sharp, with a frill on highs
+            for (int z = 0; z < 8; z++) if ((int)LEAD[z][0] == b % 4) {
+                double note = LEAD[z][2], tt = t0 + swing_beats(LEAD[z][1]);
+                bell(busL, busR, note, tt, BEAT * 0.7, big ? 0.13 : 0.10, rnd2() * 0.4, 3.0, 8.0);
+                bell(revL, revR, note, tt, BEAT * 0.7, 0.05, 0, 3.0, 8.0);
+                if (note >= 72) frill(tt + swing_beats(0.5) - swing_beats(0), note, big ? 4 : 3, 2, BEAT * 0.4, big ? 0.06 : 0.045); // frill on the high points
+            }
+            // 303 bell — swung off-beat, sharp plink
+            if (b % 2 == 0) bell(busL, busR, pent[b % 8] + (big ? 12 : 0), t0 + swing_beats(2.5), BEAT * 0.6, 0.06, rnd2() * 0.5, 3.5, 8.0);
+            // descending frill run at each phrase end of the big drop (high point)
+            if (big && b % 4 == 3) frill(t0 + BEAT * 3, 86, 6, -2, BEAT * 0.9, 0.06);
+            // high tinge sprinkle (sharp)
+            if (rnd() < 0.35) bell(busL, busR, 84 + (int)(rnd() * 5), t0 + swing_beats((int)(rnd() * 8) * 0.5), BEAT * 0.5, 0.04, rnd2() * 0.7, 4.0, 11.0);
+        }
+        // choir-ish sine bed through the biggest drop
+        if (big) for (int b = 0; b < 16; b += 2) { double t0 = (c + b) * BAR; int ns[3] = { FM_PAD[1], FM_PAD[2], FM_PAD[3] }; for (int z = 0; z < 3; z++) softsine(revL, revR, ns[z] + 12, t0, BAR * 2, 0.04, (z - 1) * 0.4); }
+    }
+
+    // ── BREAKS — spacious: pad + sub half-time + sparse bells ──
+    const char *breaks[2] = { "breakA", "breakB" };
+    for (int z2 = 0; z2 < 2; z2++) {
+        int c = START[sec_index(breaks[z2])]; double t0 = c * BAR;
+        pad_chord(t0, DB_PAD, 4, BAR * 4 - 0.05, 0.12);
+        pad_chord(t0 + BAR * 4, C_PAD, 4, BAR * 4 - 0.05, 0.12);
+        for (int b = 0; b < 8; b++) { softsine(busL, busR, b < 4 ? 25 : 24, t0 + b * BAR, BAR * 0.85, 0.10, 0); if (b % 2 == 0) bell(busL, busR, FM_PAD[1 + (b / 2) % 3], t0 + b * BAR, BAR * 0.9, 0.12, rnd2() * 0.4, 3.0, 2.6); }
+        if (z2 == 1) for (int s = 0; s < 16; s++) bell(busL, busR, 60 + (s % 8) * 2, t0 + BAR * 6 + s * SX, SX * 3, 0.04 + 0.05 * s / 16.0, rnd2() * 0.5, 3.0, 5.0); // rising bell run into drop3
+    }
+
+    // ── OUTRO — decaying bells + pad wash + final low bell ──
+    { int c = START[sec_index("outro")]; double t0 = c * BAR;
+        pad_chord(t0, FM_PAD, 4, BAR * 6 - 0.05, 0.11);
+        pad_chord(t0 + BAR * 6, C_PAD, 4, BAR * 6 - 0.05, 0.10);
+        for (int b = 0; b < 12; b++) { double e = fmax(0.1, 1.0 - b * 0.08); int root = b < 6 ? 53 : 48; softsine(busL, busR, root - 12, t0 + b * BAR, BAR * 0.9, 0.10 * e, 0); if (b % 2 == 0) stab(t0 + b * BAR + BEAT * 2, root, 0.12 * e, 0); }
+        bell(busL, busR, 36, t0 + BAR * 10, 4.0, 0.18, 0, 2.0, 1.4);
+        bell(busL, busR, 72, t0 + BAR * 10, 4.0, 0.10, 0.2, 3.5, 1.6);
+        bell(revL, revR, 60, t0 + BAR * 10, 4.0, 0.10, 0, 3.0, 1.5);
+    }
+
+    // ── REVERB (Schroeder) — a touch wetter for the glassy bell space ──
+    {
+        double decay = 0.78, wet = 0.5, damp = 0.40;
+        int CD[6]; double cds[6] = { 0.0297, 0.0371, 0.0411, 0.0437, 0.0497, 0.0581 };
+        for (int k = 0; k < 6; k++) CD[k] = (int)(cds[k] * SR);
+        int AD[2] = { (int)(0.005 * SR), (int)(0.0017 * SR) }; double apFb = 0.5;
+        float *cbL[6], *cbR[6]; int ciL[6] = {0}, ciR[6] = {0}; double cLPL[6] = {0}, cLPR[6] = {0};
+        for (int k = 0; k < 6; k++) { cbL[k] = calloc(CD[k], 4); cbR[k] = calloc(CD[k], 4); }
+        float *abL[2], *abR[2]; int aiL[2] = {0}, aiR[2] = {0};
+        for (int k = 0; k < 2; k++) { abL[k] = calloc(AD[k], 4); abR[k] = calloc(AD[k], 4); }
+        for (long i = 0; i < N; i++) {
+            double inL = revL[i], inR = revR[i], cL = 0, cR = 0;
+            for (int k = 0; k < 6; k++) {
+                double dL = cbL[k][ciL[k]], dR = cbR[k][ciR[k]]; cL += dL; cR += dR;
+                cLPL[k] = dL * (1 - damp) + cLPL[k] * damp; cLPR[k] = dR * (1 - damp) + cLPR[k] * damp;
+                cbL[k][ciL[k]] = (float)(inL + cLPL[k] * decay); cbR[k][ciR[k]] = (float)(inR + cLPR[k] * decay);
+                ciL[k] = (ciL[k] + 1) % CD[k]; ciR[k] = (ciR[k] + 1) % CD[k];
+            }
+            cL /= 6; cR /= 6;
+            for (int k = 0; k < 2; k++) {
+                double dL = abL[k][aiL[k]], dR = abR[k][aiR[k]];
+                double oL = -apFb * cL + dL, oR = -apFb * cR + dR;
+                abL[k][aiL[k]] = (float)(cL + apFb * oL); abR[k][aiR[k]] = (float)(cR + apFb * oR);
+                aiL[k] = (aiL[k] + 1) % AD[k]; aiR[k] = (aiR[k] + 1) % AD[k];
+                cL = oL; cR = oR;
+            }
+            busL[i] += (float)(cL * wet); busR[i] += (float)(cR * wet);
+        }
+        for (int k = 0; k < 6; k++) { free(cbL[k]); free(cbR[k]); }
+        for (int k = 0; k < 2; k++) { free(abL[k]); free(abR[k]); }
+    }
+
+    // ── normalize + gentle in/out fades ──
+    double peak = 0; for (long i = 0; i < N; i++) { double a = fmax(fabs(busL[i]), fabs(busR[i])); if (a > peak) peak = a; }
+    if (peak > 0) { double g = 0.85 / peak; for (long i = 0; i < N; i++) { busL[i] *= (float)g; busR[i] *= (float)g; } }
+    long fin = (long)(2.0 * SR), fout = (long)(4.0 * SR);
+    for (long i = 0; i < fin && i < N; i++) { double g = 0.5 - 0.5 * cos(M_PI * (double)i / fin); busL[i] *= (float)g; busR[i] *= (float)g; }
+    for (long i = 0; i < fout && i < N; i++) { double g = 0.5 - 0.5 * cos(M_PI * (double)i / fout); long idx = N - 1 - i; busL[idx] *= (float)g; busR[idx] *= (float)g; }
+
+    if (!write_wav_f32_stereo(out_path, busL, busR, N)) { fprintf(stderr, "✗ write failed\n"); return 1; }
+    fprintf(stderr, "✓ %s · %.1fs\n", out_path, (double)N / SR);
+    return 0;
+}
diff --git a/pop/maytrax/c/tidetrax b/pop/maytrax/c/tidetrax
new file mode 100755
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diff --git a/pop/maytrax/c/tidetrax.c b/pop/maytrax/c/tidetrax.c
new file mode 100644
index 000000000..c8e07fc9c
--- /dev/null
+++ b/pop/maytrax/c/tidetrax.c
@@ -0,0 +1,303 @@
+// tidetrax.c — an oceanic sine-bell sibling of dewtrax. Same instrument family
+// (FM sine bells + soft sine drones + Schroeder reverb), a wholly new song:
+// C minor, 100 BPM, no swing-lurch — instead a slow breathing tide. The
+// character is the ebb and flow of the sea: big swelling pad waves that crest
+// and recede, with call-and-response mid-register bells answering across the
+// stereo field. Long pad attacks/releases, dynamics that breathe in and out.
+// No samples, no drums, no vocals — pure sine.
+// render-c.mjs --engine tidetrax masters it on the sine-family chain.
+//
+// Build:  cc -O3 -std=c11 -Wall -Wextra -Wno-unused-parameter -o tidetrax tidetrax.c -lm
+// Run:    ./tidetrax --out out/tidetrax-raw.wav
+
+#define _POSIX_C_SOURCE 200809L
+#include <stdio.h>
+#include <stdlib.h>
+#include <stdint.h>
+#include <string.h>
+#include <math.h>
+
+#ifndef M_PI
+#define M_PI 3.14159265358979323846
+#endif
+#define TAU (2.0 * M_PI)
+
+static const int SR = 48000;
+static double BPMV = 100, BEAT, BAR, SX;
+
+static uint32_t rng_s = 0x74696465; // "tide"
+static inline double rnd(void) { rng_s ^= rng_s << 13; rng_s ^= rng_s >> 17; rng_s ^= rng_s << 5; return (double)rng_s / 4294967296.0; }
+static inline double rnd2(void) { return rnd() * 2.0 - 1.0; }
+static inline double midi_hz(double m) { return 440.0 * pow(2.0, (m - 69.0) / 12.0); }
+
+// ── swing / sway ────────────────────────────────────────────────────────────
+// tidetrax barely swings (0.50, near-straight) — the breathing comes from the
+// long pad envelopes and the tide LFO, not from a swung subdivision.
+static double SWING = 0.50;
+static double swing_beats(double beats) {
+    double e8 = beats * 2.0;                 // position in 8ths
+    long idx = (long)floor(e8 + 1e-9);
+    double frac = e8 - idx;
+    double pos = (idx / 2) * BEAT + ((idx & 1) ? SWING * BEAT : 0.0);
+    return pos + frac * (BEAT / 2.0);        // interpolate 16ths inside the 8th
+}
+
+// ── tide LFO — a very slow swell that the whole mix breathes with ───────────
+// One full ebb-and-flow every 8 bars; pads & bells scale their gain by it so
+// the dynamics crest and recede like surf. period ~ 8 bars.
+static double tide(double t) {
+    double period = BAR * 8.0;
+    return 0.55 + 0.45 * (0.5 - 0.5 * cos(TAU * t / period)); // 0.10 .. 1.00, raised-cos
+}
+
+static long N;
+static float *busL, *busR, *revL, *revR;
+static inline void adds(float *L, float *R, long i, double l, double r) { if (i >= 0 && i < N) { L[i] += (float)l; R[i] += (float)r; } }
+
+static int write_wav_f32_stereo(const char *path, const float *L, const float *R, long n) {
+    FILE *f = fopen(path, "wb"); if (!f) return 0;
+    uint32_t dsz = (uint32_t)(n * 8), riff = 36 + dsz, sr = SR, br = SR * 8, fsz = 16;
+    uint16_t fmt = 3, ch = 2, ba = 8, bits = 32;
+    fwrite("RIFF", 1, 4, f); fwrite(&riff, 4, 1, f); fwrite("WAVE", 1, 4, f);
+    fwrite("fmt ", 1, 4, f); fwrite(&fsz, 4, 1, f);
+    fwrite(&fmt, 2, 1, f); fwrite(&ch, 2, 1, f); fwrite(&sr, 4, 1, f);
+    fwrite(&br, 4, 1, f); fwrite(&ba, 2, 1, f); fwrite(&bits, 2, 1, f);
+    fwrite("data", 1, 4, f); fwrite(&dsz, 4, 1, f);
+    for (long i = 0; i < n; i++) { fwrite(&L[i], 4, 1, f); fwrite(&R[i], 4, 1, f); }
+    fclose(f); return 1;
+}
+
+// ── voices ────────────────────────────────────────────────────────────────
+// FM sine bell — carrier + a decaying modulator gives the glassy partial
+// shimmer; exp amp decay. `ratio` shapes the timbre. tidetrax's bells use a
+// softer, slower onset than dewtrax's plinks — they bloom into the wash.
+static void bell(float *L, float *R, double note, double t, double dur, double g, double pan, double ratio, double dec) {
+    double fc = midi_hz(note), fm = fc * ratio;
+    long n = (long)(dur * SR), s0 = (long)(t * SR);
+    double phc = 0, phm = 0, lg = 1 - pan * 0.5, rg = 1 + pan * 0.5;
+    long att = (long)(0.010 * SR);               // softer, blooming onset (vs dew's 1.2ms)
+    for (long i = 0; i < n; i++) {
+        double tt = (double)i / SR;
+        double env = exp(-tt * dec); if (i < att) env *= (double)i / att;
+        double mi = 3.5 * exp(-tt * 7.0);        // gentler attack transient — rounder bell
+        phm += TAU * fm / SR;
+        phc += TAU * fc / SR + sin(phm) * mi / SR;
+        double v = sin(phc) * env * g;
+        adds(L, R, s0 + i, v * lg, v * rg);
+    }
+}
+
+// droplet — a tiny, bright, fast-decaying bell up high; sea-spray sparkle off
+// the crest of a wave. feeds dry + (softly) the reverb tail for shimmer.
+static void droplet(double note, double t, double g, double pan) {
+    bell(busL, busR, note, t, 0.65, g, pan, 4.5, 13.0);
+    bell(revL, revR, note, t, 0.65, g * 0.6, 0, 4.5, 13.0);
+}
+
+// soft sine drone — pad / sub bed with a LONG raised-cosine attack/release so
+// each chord swells in and ebbs out like a wave rolling onto the shore.
+static void softsine(float *L, float *R, double note, double t, double dur, double g, double pan) {
+    double f = midi_hz(note); long n = (long)(dur * SR), s0 = (long)(t * SR);
+    long att = (long)(0.85 * SR), rel = (long)(1.20 * SR); double ph = 0, lg = 1 - pan * 0.5, rg = 1 + pan * 0.5;
+    if (att > n / 2) att = n / 2; if (rel > n / 2) rel = n / 2;
+    for (long i = 0; i < n; i++) {
+        ph += TAU * f / SR;
+        double env = 1; if (i < att) env = 0.5 - 0.5 * cos(M_PI * (double)i / att); else if (i > n - rel) env = fmax(0, 0.5 - 0.5 * cos(M_PI * (double)(n - i) / rel));
+        double v = (sin(ph) + 0.18 * sin(ph * 2) + 0.07 * sin(ph * 3)) * env * g;
+        adds(L, R, s0 + i, v * lg, v * rg);
+    }
+}
+
+// a wide sine pad chord — voices spread across the full stereo field for the
+// oceanic width, with a generous reverb send.
+static void pad_chord(double t, const int *midis, int nm, double dur, double g) {
+    for (int k = 0; k < nm; k++) { double pan = (k / fmax(1, nm - 1) - 0.5) * 0.85; softsine(busL, busR, midis[k], t, dur, g, pan); softsine(revL, revR, midis[k], t, dur, g * 0.5, pan * 0.6); }
+}
+
+// ── harmony — C minor, a swelling i–VI–III–VII ocean loop ───────────────────
+// per-bar bass roots that the tide walks: Cm, Ab, Eb, Bb.
+static const int C_ROOTS[4] = { 60, 56, 51, 58 };       // C4, Ab3, Eb3, Bb3
+// four 4-note pad voicings, one per chord in the loop (low, wide).
+static const int I_PAD[4]   = { 36, 43, 48, 51 };       // Cm   (C G C Eb)
+static const int VI_PAD[4]  = { 32, 39, 44, 48 };       // Ab   (Ab Eb Ab C)
+static const int III_PAD[4] = { 39, 46, 51, 55 };       // Eb   (Eb Bb Eb G)
+static const int VII_PAD[4] = { 34, 41, 46, 50 };       // Bb   (Bb F Bb D)
+static const int *PADS[4] = { I_PAD, VI_PAD, III_PAD, VII_PAD };
+
+// C natural-minor pentatonic (C Eb F G Bb), mid octave — for arps + bells.
+static const int PENT[5] = { 48, 51, 53, 55, 58 };
+// the high sea-spray droplet palette (C5 Eb5 F5 G5 Bb5 C6).
+static const int DROPS[6] = { 72, 75, 77, 79, 82, 84 };
+// the mid-register CALL palette (left side) and RESPONSE palette (right side)
+// answering across the stereo field — both in C minor pentatonic, an octave
+// apart so the answer rings brighter, higher.
+static const int CALL[4] = { 60, 63, 67, 70 };          // C4 Eb4 G4 Bb4
+static const int RESP[4] = { 67, 70, 72, 75 };          // G4 Bb4 C5 Eb5
+
+// section map. SECBARS drives every loop bound below. At 100 BPM a bar is 2.4s,
+// so this 48-bar form lands at ~115s + reverb tail. Keep wave/outro counts
+// multiples of 4 so the 4-bar phrases (pad loop, tide swell) line up.
+static const char *ORDER[8] = { "horizon", "swell", "crestA", "ebbA", "crestB", "ebbB", "crestC", "shore" };
+static const int SECBARS[8] = { 4, 4, 8, 4, 8, 4, 8, 8 };
+static int START[8];
+static int sec_index(const char *k) { for (int i = 0; i < 8; i++) if (!strcmp(ORDER[i], k)) return i; return 0; }
+
+// ── call-and-response — a mid bell on the LEFT (call) answered on the RIGHT
+// (response), the answer a beat-and-a-half later and a touch quieter. This is
+// the signature gesture of the track. ratio 3.0 = warm round bell.
+static void answer(double t, int call_note, int resp_note, double g, double tideg) {
+    bell(busL, busR, call_note, t, BEAT * 2.2, g * tideg, -0.55, 3.0, 3.2);
+    bell(revL, revR, call_note, t, BEAT * 2.2, g * 0.45 * tideg, -0.4, 3.0, 3.2);
+    double tr = t + BEAT * 1.5;
+    bell(busL, busR, resp_note, tr, BEAT * 2.0, g * 0.78 * tideg, 0.58, 3.5, 3.5);
+    bell(revL, revR, resp_note, tr, BEAT * 0.45 * 2.0, g * 0.40 * tideg, 0.42, 3.5, 3.5);
+}
+
+// ── ornaments ───────────────────────────────────────────────────────────────
+// spray — a quick run of n bright bells fanning outward across the stereo
+// field (sea spray off a crest). pans alternate L/R for a scattering feel.
+static void spray(double t, double base, int n, int step, double span, double g) {
+    for (int i = 0; i < n; i++) { double pan = (i & 1 ? 1 : -1) * (0.3 + 0.5 * rnd()); bell(busL, busR, base + i * step, t + span * i / n, span * 1.5, g * (1.0 - 0.3 * i / n), pan, 4.5, 11.0); }
+}
+
+int main(int argc, char **argv) {
+    const char *out_path = "out/tidetrax-raw.wav";
+    for (int i = 1; i < argc; i++) { if (!strcmp(argv[i], "--out") && i + 1 < argc) out_path = argv[++i]; else if (!strcmp(argv[i], "--bpm") && i + 1 < argc) BPMV = atof(argv[++i]); else if (!strcmp(argv[i], "--swing") && i + 1 < argc) SWING = atof(argv[++i]); }
+    BEAT = 60.0 / BPMV; BAR = BEAT * 4; SX = BEAT / 4;
+    { int c = 0; for (int i = 0; i < 8; i++) { START[i] = c; c += SECBARS[i]; } }
+    int TB = 0; for (int i = 0; i < 8; i++) TB += SECBARS[i];
+    double totalSec = TB * BAR + 7.0; N = (long)(totalSec * SR);
+    busL = calloc(N, 4); busR = calloc(N, 4); revL = calloc(N, 4); revR = calloc(N, 4);
+    fprintf(stderr, "# tidetrax.c · %g BPM · %d bars · %.1fs · C minor oceanic sine bells\n", BPMV, TB, totalSec);
+
+    // ── HORIZON — a single low pad swelling up from silence, distant spray ──
+    { int idx = sec_index("horizon"); int c = START[idx], nb = SECBARS[idx]; double t0 = c * BAR;
+        pad_chord(t0, I_PAD, 4, BAR * nb - 0.05, 0.11);                       // one long swell across the whole intro
+        softsine(busL, busR, 24, t0 + BAR, BAR * (nb - 1) * 0.95, 0.10, 0);   // deep sub tide rolling under
+        // a few far-off droplets near the back, faint
+        for (int b = nb - 3; b < nb; b++) if (b >= 0) droplet(DROPS[(int)(rnd() * 6)], t0 + b * BAR + 3.0 * BEAT, 0.035 * tide(t0 + b * BAR), rnd2() * 0.8);
+        // one first faint call-and-response, far out, to seed the motif
+        answer(t0 + BAR * (nb - 1), CALL[0], RESP[0], 0.06, tide(t0 + BAR * (nb - 1)));
+    }
+
+    // ── SWELL — the water gathers: pad climb + rising pentatonic arp ──
+    { int idx = sec_index("swell"); int c = START[idx], nb = SECBARS[idx], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, VI_PAD, 4, BAR * h - 0.05, 0.13);
+        pad_chord(t0 + BAR * h, III_PAD, 4, BAR * (nb - h) - 0.05, 0.15);
+        // a slowly-rising pentatonic arpeggio drifting up the stereo field
+        int arp[8] = { 48, 51, 53, 55, 58, 60, 63, 67 };
+        for (int s = 0; s < 16; s++) { double tt = t0 + BAR * h + swing_beats(s * 0.5); double tg = tide(tt); bell(busL, busR, arp[s % 8] + (s / 8) * 12, tt, BEAT * 1.6, (0.05 + 0.06 * s / 16.0) * tg, (s & 1 ? 1 : -1) * 0.45, 3.5, 6.0); }
+        // call-and-response begins to answer
+        answer(t0 + BAR * 1, CALL[1], RESP[1], 0.10, tide(t0 + BAR));
+        answer(t0 + BAR * 2.5, CALL[2], RESP[2], 0.10, tide(t0 + BAR * 2.5));
+        spray(t0 + BAR * nb - BEAT * 2, 67, 6, 2, BEAT * 1.8, 0.06);          // spray into the first crest
+    }
+
+    // ── helper for the three crests (the tide LFO does the dynamics) ──
+    const char *crests[3] = { "crestA", "crestB", "crestC" };
+    for (int d = 0; d < 3; d++) {
+        int wi = sec_index(crests[d]); int c = START[wi], nbw = SECBARS[wi]; int big = d == 2;
+        for (int b = 0; b < nbw; b++) {
+            double t0 = (c + b) * BAR; int root = C_ROOTS[b % 4]; int phrase = b % 4 == 0;
+            double tg = tide(t0);                                              // this bar's place in the swell
+            // a rolling sub bass — long soft notes per bar that breathe with the tide
+            softsine(busL, busR, root - 12, t0, BAR * 0.98, (0.09 + 0.05 * tg), 0);
+            // pad sustain every 4 bars (chord follows the ocean loop), swelling with the tide
+            if (phrase) pad_chord(t0, PADS[(b / 4) % 4], 4, BAR * 4 - 0.05, 0.06 + 0.04 * tg);
+            // the signature call-and-response — left calls on beat 1, right answers,
+            // walking up the CALL/RESP palettes through the phrase.
+            int ci = (b % 4);
+            answer(t0, CALL[ci], RESP[ci], big ? 0.13 : 0.10, tg);
+            // a second softer answer on the back half of the bar in the big crest
+            if (big) answer(t0 + BEAT * 2, RESP[ci], CALL[(ci + 1) % 4] + 12, 0.07, tide(t0 + BEAT * 2));
+            // pentatonic plinks riding the crest — denser at high tide
+            int nplinks = (tg > 0.7) ? 2 : 1;
+            for (int k = 0; k < nplinks; k++) if (rnd() < 0.6) bell(busL, busR, PENT[(int)(rnd() * 5)] + 12, t0 + swing_beats((int)(rnd() * 8) * 0.5), BEAT * 0.9, 0.05 * tg, rnd2() * 0.7, 3.5, 6.0);
+            // sea-spray droplets, more at the crest of the wave
+            int ndrops = big ? 3 : (tg > 0.6 ? 2 : 1);
+            for (int k = 0; k < ndrops; k++) if (rnd() < 0.55) droplet(DROPS[(int)(rnd() * 6)], t0 + swing_beats((int)(rnd() * 8) * 0.5), 0.04 * tg, rnd2() * 0.8);
+            // spray fan at phrase ends of the big crest (the wave breaking)
+            if (big && b % 4 == 3) spray(t0 + BEAT * 2.5, 79, 6, -2, BEAT * 1.1, 0.06);
+        }
+        // a high choir-ish sine bed shimmering over the biggest crest
+        if (big) for (int b = 0; b < nbw; b += 2) { double t0 = (c + b) * BAR; int ns[3] = { III_PAD[1] + 12, III_PAD[2] + 12, III_PAD[3] + 12 }; for (int z = 0; z < 3; z++) softsine(revL, revR, ns[z], t0, BAR * 2, 0.035, (z - 1) * 0.6); }
+    }
+
+    // ── EBBS — the tide recedes: spacious pad + half-time sub + lone answers ──
+    const char *ebb[2] = { "ebbA", "ebbB" };
+    for (int z2 = 0; z2 < 2; z2++) {
+        int hi = sec_index(ebb[z2]); int c = START[hi], nb = SECBARS[hi], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, VI_PAD, 4, BAR * h - 0.05, 0.12);
+        pad_chord(t0 + BAR * h, VII_PAD, 4, BAR * (nb - h) - 0.05, 0.12);
+        for (int b = 0; b < nb; b++) {
+            double tb = t0 + b * BAR; double tg = tide(tb);
+            softsine(busL, busR, b < h ? 32 : 34, tb, BAR * 0.9, 0.09, 0);    // half-time sub
+            // sparse, lone call-and-response drifting in the open space
+            if (b % 2 == 0) answer(tb, CALL[(b / 2) % 4], RESP[(b / 2) % 4], 0.09, tg);
+            if (rnd() < 0.5) droplet(DROPS[(int)(rnd() * 6)], tb + 2.5 * BEAT, 0.035 * tg, rnd2() * 0.8);
+        }
+        if (z2 == 1) spray(t0 + BAR * (nb - 2), 60, 8, 2, BEAT * 3.0, 0.05);  // rising spray into crest C
+    }
+
+    // ── SHORE (outro) — the last wave recedes: decaying answers, pad wash,
+    // a final low bell rolling out to sea ──
+    { int idx = sec_index("shore"); int c = START[idx], nb = SECBARS[idx], h = nb / 2; double t0 = c * BAR;
+        pad_chord(t0, I_PAD, 4, BAR * h - 0.05, 0.11);
+        pad_chord(t0 + BAR * h, VI_PAD, 4, BAR * (nb - h) - 0.05, 0.10);
+        for (int b = 0; b < nb; b++) {
+            double tb = t0 + b * BAR; double e = fmax(0.1, 1.0 - (double)b / nb);
+            int root = b < h ? 60 : 56;
+            softsine(busL, busR, root - 24, tb, BAR * 0.9, 0.10 * e, 0);
+            if (b % 2 == 0) answer(tb + BEAT * 0.5, CALL[b % 4], RESP[b % 4], 0.09 * e, 0.8);
+            if (rnd() < 0.5) droplet(DROPS[(int)(rnd() * 6)], tb + 1.5 * BEAT, 0.03 * e, rnd2() * 0.8);
+        }
+        // a final low bell + high shimmer ringing out as the tide goes still
+        bell(busL, busR, 36, t0 + BAR * (nb - 2), 5.0, 0.18, 0, 2.0, 1.0);
+        bell(busL, busR, 60, t0 + BAR * (nb - 2), 5.0, 0.10, 0.3, 3.5, 1.3);
+        bell(revL, revR, 67, t0 + BAR * (nb - 2), 5.0, 0.10, -0.3, 3.5, 1.2);
+    }
+
+    // ── REVERB (Schroeder) — big, wet, oceanic space: longer decay, wetter
+    // mix, darker damping than dewtrax for that cavernous sea-cave wash ──
+    {
+        double decay = 0.87, wet = 0.62, damp = 0.45;
+        int CD[6]; double cds[6] = { 0.0311, 0.0389, 0.0431, 0.0461, 0.0523, 0.0613 };
+        for (int k = 0; k < 6; k++) CD[k] = (int)(cds[k] * SR);
+        int AD[2] = { (int)(0.005 * SR), (int)(0.0017 * SR) }; double apFb = 0.5;
+        float *cbL[6], *cbR[6]; int ciL[6] = {0}, ciR[6] = {0}; double cLPL[6] = {0}, cLPR[6] = {0};
+        for (int k = 0; k < 6; k++) { cbL[k] = calloc(CD[k], 4); cbR[k] = calloc(CD[k], 4); }
+        float *abL[2], *abR[2]; int aiL[2] = {0}, aiR[2] = {0};
+        for (int k = 0; k < 2; k++) { abL[k] = calloc(AD[k], 4); abR[k] = calloc(AD[k], 4); }
+        for (long i = 0; i < N; i++) {
+            double inL = revL[i], inR = revR[i], cL = 0, cR = 0;
+            for (int k = 0; k < 6; k++) {
+                double dL = cbL[k][ciL[k]], dR = cbR[k][ciR[k]]; cL += dL; cR += dR;
+                cLPL[k] = dL * (1 - damp) + cLPL[k] * damp; cLPR[k] = dR * (1 - damp) + cLPR[k] * damp;
+                cbL[k][ciL[k]] = (float)(inL + cLPL[k] * decay); cbR[k][ciR[k]] = (float)(inR + cLPR[k] * decay);
+                ciL[k] = (ciL[k] + 1) % CD[k]; ciR[k] = (ciR[k] + 1) % CD[k];
+            }
+            cL /= 6; cR /= 6;
+            for (int k = 0; k < 2; k++) {
+                double dL = abL[k][aiL[k]], dR = abR[k][aiR[k]];
+                double oL = -apFb * cL + dL, oR = -apFb * cR + dR;
+                abL[k][aiL[k]] = (float)(cL + apFb * oL); abR[k][aiR[k]] = (float)(cR + apFb * oR);
+                aiL[k] = (aiL[k] + 1) % AD[k]; aiR[k] = (aiR[k] + 1) % AD[k];
+                cL = oL; cR = oR;
+            }
+            busL[i] += (float)(cL * wet); busR[i] += (float)(cR * wet);
+        }
+        for (int k = 0; k < 6; k++) { free(cbL[k]); free(cbR[k]); }
+        for (int k = 0; k < 2; k++) { free(abL[k]); free(abR[k]); }
+    }
+
+    // ── normalize + long gentle in/out fades (tide arriving + receding) ──
+    double peak = 0; for (long i = 0; i < N; i++) { double a = fmax(fabs(busL[i]), fabs(busR[i])); if (a > peak) peak = a; }
+    if (peak > 0) { double g = 0.85 / peak; for (long i = 0; i < N; i++) { busL[i] *= (float)g; busR[i] *= (float)g; } }
+    long fin = (long)(3.5 * SR), fout = (long)(5.5 * SR);
+    for (long i = 0; i < fin && i < N; i++) { double g = 0.5 - 0.5 * cos(M_PI * (double)i / fin); busL[i] *= (float)g; busR[i] *= (float)g; }
+    for (long i = 0; i < fout && i < N; i++) { double g = 0.5 - 0.5 * cos(M_PI * (double)i / fout); long idx = N - 1 - i; busL[idx] *= (float)g; busR[idx] *= (float)g; }
+
+    if (!write_wav_f32_stereo(out_path, busL, busR, N)) { fprintf(stderr, "✗ write failed\n"); return 1; }
+    fprintf(stderr, "✓ %s · %.1fs\n", out_path, (double)N / SR);
+    return 0;
+}
diff --git a/pop/momboba/LISTENER-VIDEO.md b/pop/momboba/LISTENER-VIDEO.md
new file mode 100644
index 000000000..28ed3f9e2
--- /dev/null
+++ b/pop/momboba/LISTENER-VIDEO.md
@@ -0,0 +1,278 @@
+# momabobasheep — YouTube Listener Video (10:00 landscape)
+
+**Status:** SPEC (proposed 2026-06-15) · **Target:** one 1920×1080 / 30fps
+landscape video for the full 10:00 master, uploaded to the AC YouTube channel
+as the canonical "play the whole track" page.
+
+> **DECIDED (@jeffrey, 2026-06-15):**
+> - **Build path:** *dry run first* → then the **LUSH pass** (9 distinct
+>   movement scenes, motion throughout). Both done — see §3.5 and §3.6.
+> - **Score ribbon:** quiet ambient, **and NO labels on the tracks** — the
+>   scrolling score is purely abstract felt-tinted notes gliding past the
+>   playhead, with *zero per-note text and no chord glyphs riding on the
+>   ribbon*. Text is confined to the sparse corner chrome only (title /
+>   movement name / progress), and even that stays minimal.
+> - **Scene approach:** 9 distinct felt dioramas, one per movement, cross-cut
+>   on the music's movement boundaries (not the single evolving bench scene).
+
+This is the **landscape twin** of the released 9:16 promo set
+(`momabobasheep-story.mp4` / `-reel.mp4`). Those are 56-second vertical
+highlight reels for Reels/TikTok. This is the long-form *listener* video: the
+whole sleep mix, designed to be left running, that earns its watch-time from a
+**tasteful, quiet score overlay** rather than a wall of generated motion.
+
+The core constraint @jeffrey set: *the track is 10 minutes and video gen is
+expensive, so overlay the track data tastefully with few labels, build out
+still images, and reserve Seedance for where it actually counts — don't break
+the bank.*
+
+---
+
+## 1. The aesthetic (carry the track's concept)
+
+The track already has a narrative: **MoMA + boba + sheep** — jeffrey goes to the
+museum, drinks a boba, and falls asleep counting sheep in the galleries —
+told as a **9-movement Fibonacci-arch night** (drift → settle → sink →
+deepening → dreaming → deep dream → **THE DREAM** (climax, ~golden section) →
+strange REM → dawn). Medium is **needle-felt wool** (`mediums.mjs →
+NEEDLE_FELT_WOOL`), the same felted-diorama look as the cover and reel.
+
+The listener video should feel like **watching that felt night breathe for ten
+minutes**, with the score gliding by underneath like the tape of a music box.
+Warm/dark, never bright (matches the −16 LUFS sleep master and the
+"no brightening pass" mastering call).
+
+---
+
+## 2. Composition — three quiet layers
+
+A listener video is not a motion reel. It is **mostly still, gently alive**.
+Three stacked layers, in back-to-front order:
+
+### Layer A — Background: 9 felt movement stills (FREE, the workhorse)
+One still per movement (felt diorama in the cover's style), drifting under a
+slow **Ken Burns** (`preview-shared.mjs → drawCoverKenBurns`: baseScale ~1.15,
+18s breath, multi-freq wobble) and **cross-dissolving** at each movement
+boundary. This alone carries ~8 of the 10 minutes with zero video-gen spend.
+
+Stills are new landscape gpt-image-2 gens (1536×1024) via a `gen-stills.mjs`
+adapted from `bin/gen-illy.mjs` — the existing 8 reel panels are 9:16 and
+center-cropping them to 16:9 loses the diorama, so generate fresh landscape
+beats. Story beats map cleanly to movements:
+
+| # | Movement (night)      | Still (MoMA-boba-sheep beat)                  | Motion budget |
+|---|-----------------------|-----------------------------------------------|---------------|
+| 1 | drift                 | arrival — felt jeffrey at the museum doors    | still + KB    |
+| 2 | settle                | boba sip in the lobby                         | still + KB    |
+| 3 | sink                  | drifting the galleries, eyes heavy            | still + KB    |
+| 4 | deepening             | waterlily room, awe                           | **loop**      |
+| 5 | dreaming              | first sheep grazing between the paintings     | **loop**      |
+| 6 | deep dream            | the flock, asleep on a felt bench             | still + KB    |
+| 7 | **THE DREAM** (climax)| spilled-boba ASCENSION — the dream itself     | **hero shot** |
+| 8 | strange REM           | melting galleries, sheep adrift               | **loop**      |
+| 9 | dawn                  | morning light, the cup empty, resolve home    | still + KB    |
+
+### Layer B — Motion accents: short Seedance loops (BUDGET-CAPPED)
+Reserve Seedance for the **4 marked rows** above. Each is a short clip
+**ping-pong looped** (`build-canvas.mjs` already does this for the 8s Canvas) to
+fill its whole movement seamlessly — a 5s felt scene ping-ponged = a 10s
+breathing loop that tiles under any movement length, and slow looping reads as
+*intentional* at sleep tempo, not as a GIF. The climax (row 7) gets one longer
+**hero shot** that plays once, un-looped, as the visual payoff. Generated
+through the existing `pop/lib/motion-pipeline.mjs` + `fal-seedance.mjs` (fast
+tier, 720p) and assembled the same way as the reel.
+
+### Layer C — The score overlay ("the video score", tasteful, few labels)
+This is your scorodeon idea, re-pitched for landscape and **dialed way down**.
+`bin/scorodeon-data.mjs` already turns `events.json` → `scorodeon.json`, and
+`pop/bin/scorodeon.mjs` renders the score flying past a centerline. For a
+listener video the score should be **ambient, not the star**:
+
+- A **thin horizontal score ribbon** (notes scrolling right→left past a fixed
+  playhead) across the lower third, at low opacity (~35–45%), tinted to the
+  current movement's felt palette. Landscape orientation = horizontal scroll,
+  unlike the vertical 4K scorodeon.
+- **Few labels, set sparse and small** (YWFT, via `preview-shared.mjs`
+  typography helpers):
+  - top-left: **momabobasheep** title (static, small)
+  - top-right: **current movement name** (cross-fades at boundaries — "the
+    dream", "dawn"…)
+  - the **current chord** glyph near the playhead (F / Dm / Bb / C / Gm / Eb),
+    pulled from `struct.json` chords
+  - a **slim segmented progress bar** + timecode along the very bottom edge
+    (reuse the story-variant chrome)
+- Optional: a faint **figure backlight** (`drawFormBacklight`) pulsing on the
+  audio RMS envelope so the felt scene "breathes" with the marimba.
+
+That's the whole label set — four text elements + chord + progress. Nothing
+karaoke, nothing busy. The data is *present and legible* but stays a quiet
+instrument-panel under the felt.
+
+---
+
+## 3. Budget — three tiers (the whole point)
+
+Seedance 720p: **fast $0.2419/s · standard $0.3024/s** (`fal-seedance.mjs`
+`RATE_PER_SEC`). gpt-image-2 stills are cents each. Pick a tier:
+
+| Tier | Seedance | Billed sec | Seedance $ | Stills | All-in | Feel |
+|------|----------|-----------:|-----------:|-------:|-------:|------|
+| **A — minimal** | none (Ken Burns over 9 stills + reuse paid reel shots as accents) | 0 | $0 | ~9–12 imgs | **~$3** | calm, still, score-led |
+| **B — recommended** | 3 loops ×5s + 1 hero ×10s, fast | 25s | **~$6** | ~12–15 imgs | **~$9–10** | felt breathes at 4 key beats, climax pays off |
+| **C — lush** | loop per movement (8×5s) + hero ×12s, fast | 52s | **~$13** | ~15 imgs | **~$17** | motion throughout, still loop-cheap |
+
+For reference, a naïve "generate all 600s" approach would be **~$145 (fast) /
+~$181 (standard)** — so even Tier C is ~10× cheaper by leaning on stills +
+ping-pong loops + the score overlay for perceived motion.
+
+**Recommendation: Tier B.** Ken Burns + the scrolling score carry the runtime;
+Seedance lights up only the waterlily, first-sheep, REM-melt, and the dream
+climax. ~$10 all-in for a 10-minute video.
+
+---
+
+## 3.5 Dry-run result (2026-06-15)
+
+Built `bin/chrome-listener.mjs` (the landscape twin of `chrome-reel.mjs`) and
+rendered a Tier-A dry pass — **$0 spend**: the *existing* `momabobasheep-cover.png`
+as the background still, the *existing* master audio, and the *existing*
+`momabobasheep.scorodeon.json` score data. No new stills, no Seedance.
+
+It works, and the cover already nails the concept: jeffrey asleep on a museum
+bench, Monet waterlilies behind, boba + glasses + felt sheep in the foreground.
+- Background felt diorama on a slow ken-burns drift (preview-shared).
+- Quiet **label-free** score band in the lower third — every melodic lane
+  merged into one felt-tinted note ribbon (pitch→Y, lane→color, gain→height)
+  gliding past an amber centerline that breathes on the RMS. No per-note text,
+  no chord glyphs, no lane chips — exactly as decided.
+- Sparse corner chrome only: title (top-left), current movement w/ 1.2s
+  cross-fade at boundaries (top-right), progress bar + clock (bottom).
+
+Outputs: `out/listener-frame.png` (frame @360s, the "vivid" climax) and
+`out/momabobasheep-listener-dryrun.mp4` (30s, 432–462s, crossing vivid→morning).
+Both copied to `~/Desktop`. Render config: 1920×1080@30, `--ss 1` for a fast
+dry pass (final bumps to `--ss 2`).
+
+**Commands:**
+```bash
+node pop/momboba/bin/chrome-listener.mjs --frame 360            # one PNG
+node pop/momboba/bin/chrome-listener.mjs --window 432-462 --dryrun  # 30s clip
+node pop/momboba/bin/chrome-listener.mjs --ss 2                 # full 10:00 (final)
+```
+
+**Open look-notes for @jeffrey:** the ribbon currently overlaps the foreground
+felt sheep/bench and reads a touch muddy there — easy knobs: lower `--ribbon`
+opacity, drop the band lower, or thin it. Tune after you watch.
+
+## 3.6 Lush pass — BUILT (2026-06-15)
+
+9 distinct felt movement scenes, motion throughout. Total fal spend **~$12.6**
+(8 movement loops × 5s + the-dream hero × 12s = 52s billed @ fast 720p).
+
+Pipeline, all on this lane:
+- **`pano/`** — `PREAMBLE.txt` + 9 beat prompts (`01-arrival` … `09-resolve`),
+  one per movement, landscape framing.
+- **`bin/gen-panels-listener.mjs`** — 9 stills @ 1536×1024 (gpt-image-2, jeffrey
+  refs) → `pano/out/NN-*.png`. ~2.7 min each on the 8GB machine.
+- **`bin/gen-motion-listener.mjs`** — Seedance 2.0 (fal) over the 9 stills, 16:9
+  720p, all cuts. SHORT generation struct (5s / hero 12s) decouples paid clip
+  length from the long movement playback. → `out/motion/…-shot-N-name.mp4`.
+- **`bin/assemble-listener.mjs`** — ping-pong + tile each clip to its real
+  movement length (from the scorodeon movement boundaries), hard-cut at
+  boundaries → `out/listener-plate.mp4` (600.0s, 1920×1080, silent).
+- **`bin/chrome-listener.mjs --plate <plate>`** — reads plate frames via an
+  ffmpeg RGBA pipe as the moving background, draws the quiet no-label score +
+  corner chrome, muxes the master → `out/momabobasheep-listener.mp4`.
+
+**Gotchas hit + fixed:**
+- the-dream (close-up of jeffrey's felt face) tripped fal's
+  `content_policy_violation` ("likenesses of real people"). Fix = re-gen that
+  still **face turned away / tucked into his arm, seen from above-behind** (the
+  faces-fail-moderation rule); it passed and looks better. After a re-roll,
+  **delete the stale `…mp4.queue.json`** or the pipeline resumes the old failed
+  job instead of submitting the new image.
+
+**Final render command:**
+```bash
+node pop/momboba/bin/gen-panels-listener.mjs        # 9 stills
+node pop/momboba/bin/gen-motion-listener.mjs        # Seedance (~$12.6)
+node pop/momboba/bin/assemble-listener.mjs          # → listener-plate.mp4
+node pop/momboba/bin/chrome-listener.mjs --plate pop/momboba/out/listener-plate.mp4 --desktop
+```
+
+## 4. Build pipeline (reuse what exists)
+
+Almost everything is already in the lane or `pop/lib/`. New work is one stills
+generator and one landscape-chrome compositor; the rest is configuration.
+
+```
+1. node pop/momboba/bin/gen-stills.mjs          # NEW (fork gen-illy.mjs)
+   → out/stills/momabobasheep-mov-{1..9}.png     # 1536×1024 landscape dioramas
+
+2. node pop/momboba/bin/scorodeon-data.mjs       # EXISTS
+   → out/momabobasheep.scorodeon.json            # already generated
+
+3. node pop/momboba/bin/gen-motion-listener.mjs  # NEW (fork gen-motion-…-reel.mjs)
+   → out/motion/listener/<movement>-shot.mp4      # Tier-B: 4 shots, fast/720p
+   (uses pop/lib/motion-pipeline.mjs + fal-seedance.mjs; takes board via
+    pop/bin/audition-motion.mjs to pick the good roll before assembling)
+
+4. node pop/momboba/bin/chrome-listener.mjs       # NEW (fork chrome-reel.mjs)
+   --variant listener                              # landscape 1920×1080@30
+   → out/momabobasheep-listener.mp4                # full 10:00, audio muxed
+   (Ken Burns stills + ping-pong motion loops + horizontal score ribbon +
+    sparse YWFT labels + progress/timecode + RMS backlight, via preview-shared.mjs;
+    encodes through spawnFFmpegEncode, BGRA stdin, x264 -crf 20)
+
+5. node toolchain/youtube/yt.mjs upload \          # EXISTS
+     pop/momboba/out/momabobasheep-listener.mp4 \
+     --title "Momabobasheep" \
+     --description-file pop/momboba/out/momabobasheep.youtube.txt \
+     --tags "ambient,sleep,chillwave,marimba,aesthetic computer,pixsies" \
+     --category 10 --privacy public \
+     --thumbnail out/momabobasheep-cover-thumb.jpg
+   → writes momabobasheep-listener.youtube.json receipt (videoId, watch URL)
+```
+
+**New scripts (3):** `gen-stills.mjs`, `gen-motion-listener.mjs`,
+`chrome-listener.mjs` — each a fork of an existing sibling, so no new
+infrastructure. Everything else (scorodeon data, Seedance client, motion
+pipeline, preview-shared chrome primitives, ffmpeg encode, YouTube upload)
+already exists and is proven on this lane.
+
+---
+
+## 5. YouTube metadata
+
+Per the RELEASES.md convention (Title Case title, hashtag-only description):
+
+- **Title:** `Momabobasheep`
+- **Description file** (`out/momabobasheep.youtube.txt`): one line of hashtags —
+  `#ambient #sleep #chillwave #marimba #aestheticcomputer #pixsies`
+  (optionally a single line above it: *"a ten-minute sleep mix — jeffrey goes
+  to the MoMA, drinks a boba, and falls asleep counting sheep."*)
+- **Category:** 10 (Music) · **Privacy:** public · **Made for kids:** no
+- **Thumbnail:** downscale the 3000² cover → ≤2MB jpg
+- **Chapters** (nice freebie for a 10-min video — YouTube auto-detects
+  `0:00 title` timestamps in the description): emit them from `struct.json`
+  movement boundaries, e.g. `0:00 drift · 1:12 settle · … · 6:0x the dream`.
+  This doubles as on-page navigation and reinforces the night arc.
+
+---
+
+## 6. Open questions for @jeffrey
+
+1. **Tier?** Recommending **B** (~$10). A is ~$3 and pure stills; C is ~$17.
+2. **Score ribbon prominence** — quiet ambient ribbon in the lower third (my
+   default), or a touch more present (taller/brighter)? "Few labels" says keep
+   it quiet.
+3. **Stills count** — 9 (one per movement) is the clean mapping. Want fewer
+   (e.g. 5 hero stills cross-dissolving) to save a couple gpt-image-2 cents and
+   tighten the look?
+4. **Privacy on first upload** — `unlisted` to review the 10-min render before
+   going `public`? (Cheap insurance for a long render.)
+5. **Chapters in description** — yes/no on the auto-chapter timestamps.
+
+Nothing here is built yet — this is the plan. Say the tier and I'll scaffold the
+three fork scripts and do a Tier-A dry run (stills + score, zero Seedance spend)
+so you can see the look before we spend anything on motion.
diff --git a/pop/momboba/bin/assemble-listener.mjs b/pop/momboba/bin/assemble-listener.mjs
new file mode 100644
index 000000000..1f2936f13
--- /dev/null
+++ b/pop/momboba/bin/assemble-listener.mjs
@@ -0,0 +1,146 @@
+#!/usr/bin/env node
+// momboba/bin/assemble-listener.mjs — build the 10-minute BACKGROUND PLATE
+// for the listener video from the 9 Seedance movement clips.
+//
+// Each Seedance clip is only ~5 s (the-dream 12 s). Each MOVEMENT, though,
+// plays for up to ~3 minutes. The old build ping-ponged (forward+reversed) and
+// stream-looped — but the reverse play read as lame (jas, 2026-06-15). So now
+// each movement is cut from DIFFERENT CROPPINGS of its one clip:
+//   1. split the movement into ~clip-length CROP SHOTS (≈ one forward play of
+//      the clip each — no reverse, no mid-shot loop pop; if a shot outruns the
+//      clip the last frame freezes while the crop keeps drifting, so it never
+//      goes static),
+//   2. each crop shot picks a distinct framing from MOVES (zoom + a slow
+//      ken-burns pan across a different region of the felt) — establishing
+//      wide, push into a corner, rise from the bottom, slow detail, etc.,
+//   3. HARD-CUT between croppings AND between movements — the scene changes
+//      exactly when the music's movement changes (cuts > morphs), and every
+//      cut lands on a fresh angle so the looping clip never reads as a loop.
+//      Output is a SILENT 1920×1080 ~600 s plate; chrome-listener.mjs then
+//      draws the score + chrome over it and muxes the real audio.
+//
+// Picks: respects out/motion/takes.json (audition board) like the pipeline,
+// falling back to the shot file, then the newest archived take.
+//
+// Usage:
+//   node pop/momboba/bin/assemble-listener.mjs            # → out/listener-plate.mp4
+//   node pop/momboba/bin/assemble-listener.mjs --out X.mp4
+
+import { readFileSync, writeFileSync, existsSync, readdirSync, mkdirSync, rmSync } from "node:fs";
+import { resolve, dirname } from "node:path";
+import { fileURLToPath } from "node:url";
+import { spawnSync } from "node:child_process";
+
+const HERE = dirname(fileURLToPath(import.meta.url));
+const LANE = resolve(HERE, "..");
+const REPO = resolve(LANE, "..", "..");
+const OUT = `${LANE}/out`;
+const MOTION = `${OUT}/motion`;
+const rel = (p) => p.replace(REPO + "/", "");
+
+const args = process.argv.slice(2);
+const opt = (k, d) => { const i = args.indexOf(`--${k}`); return i >= 0 && args[i + 1] ? args[i + 1] : d; };
+const PLATE = resolve(process.cwd(), opt("out", `${OUT}/listener-plate.mp4`));
+const W = 1920, H = 1080, FPS = 30;
+
+// movement order ↔ motion-shot order (1:1, same index as gen-motion-listener).
+const SHOTS = ["arrival", "boba-sip", "galleries", "waterlily-awe",
+  "first-sheep", "asleep-flock", "the-dream", "morning", "resolve"];
+
+// total runtime comes from the score data (authoritative timing).
+const S = JSON.parse(readFileSync(`${OUT}/momabobasheep.scorodeon.json`, "utf8"));
+const TOTAL = S.dur;                                  // 600
+
+const takesPath = `${MOTION}/takes.json`;
+const takes = existsSync(takesPath) ? JSON.parse(readFileSync(takesPath, "utf8")) : {};
+
+function clipFor(i, name) {
+  if (takes[name]) { const p = resolve(MOTION, takes[name]); if (existsSync(p)) return p; }
+  const shot = `${MOTION}/momabobasheep-listener-shot-${i}-${name}.mp4`;
+  if (existsSync(shot)) return shot;
+  const arch = `${MOTION}/archive`;
+  const base = `momabobasheep-listener-shot-${i}-${name}.v`;
+  const vs = (existsSync(arch) ? readdirSync(arch) : [])
+    .filter((f) => f.startsWith(base))
+    .sort((a, b) => Number(b.match(/\.v(\d+)\.mp4$/)?.[1] ?? 0) - Number(a.match(/\.v(\d+)\.mp4$/)?.[1] ?? 0));
+  return vs.length ? `${arch}/${vs[0]}` : null;
+}
+
+const run = (a) => {
+  const r = spawnSync("ffmpeg", ["-hide_banner", "-loglevel", "error", "-y", ...a],
+    { stdio: ["ignore", "ignore", "pipe"] });
+  if (r.status !== 0) { console.error(`✗ ffmpeg:\n${r.stderr?.toString().slice(-500)}`); process.exit(1); }
+};
+
+const TMP = `${MOTION}/plate-tmp`;
+mkdirSync(TMP, { recursive: true });
+
+// crop framings — each shot rides a different region of the felt at a slow
+// drift (z = zoom; f* = start pan anchor 0..1, t* = end anchor; 0=left/top).
+// Cycled with a per-movement offset so adjacent movements never open the same.
+const MOVES = [
+  { z: 1.08, fx: 0.50, fy: 0.52, tx: 0.50, ty: 0.44 }, // establishing, tiny rise
+  { z: 1.34, fx: 0.22, fy: 0.30, tx: 0.36, ty: 0.42 }, // drift into upper-left
+  { z: 1.50, fx: 0.74, fy: 0.58, tx: 0.60, ty: 0.50 }, // ease in from the right
+  { z: 1.26, fx: 0.50, fy: 0.76, tx: 0.50, ty: 0.56 }, // rise from bottom-center
+  { z: 1.62, fx: 0.46, fy: 0.42, tx: 0.54, ty: 0.48 }, // slow detail push
+  { z: 1.30, fx: 0.72, fy: 0.22, tx: 0.54, ty: 0.36 }, // come down from top-right
+  { z: 1.44, fx: 0.28, fy: 0.64, tx: 0.42, ty: 0.50 }, // up out of lower-left
+];
+
+// one forward play of the clip ≈ one crop shot (no reverse, no loop pop).
+function clipDur(p) {
+  const r = spawnSync("ffprobe", ["-v", "error", "-show_entries", "format=duration",
+    "-of", "default=noprint_wrappers=1:nokey=1", p], { encoding: "utf8" });
+  const d = Number(r.stdout?.trim());
+  return Number.isFinite(d) && d > 0 ? d : 5;
+}
+
+// gather every available clip (movement order), with its real duration.
+const clips = [];
+for (let i = 0; i < SHOTS.length; i++) {
+  const p = clipFor(i, SHOTS[i]);
+  if (p) clips.push({ name: SHOTS[i], path: p, dur: clipDur(p) });
+}
+if (!clips.length) { console.error("✗ no clips found"); process.exit(1); }
+
+// CYCLE through the clips for the whole track (jas, 2026-06-16): each segment
+// is one play of the NEXT clip in the cycle — so a clip never repeats back to
+// back — under a fresh crop each time it comes round (MOVES advances on its own
+// stride; gcd(MOVES, clips)=1 → every clip sees every crop before any repeat).
+// No string/track/warp — just the clips, cropped, cycling.
+let t = 0, ci = 0, si = 0;
+const segs = [];
+while (t < TOTAL - 0.1) {
+  const clip = clips[ci % clips.length]; ci++;
+  const mv = MOVES[si % MOVES.length]; si++;
+  let shotDur = clip.dur;
+  if (t + shotDur > TOTAL) shotDur = TOTAL - t;            // trim the last one
+  if (shotDur < 0.4) break;
+  const SW = Math.round(W * mv.z), SH = Math.round(H * mv.z);
+  const rx = SW - W, ry = SH - H;                          // pan range at this zoom
+  const D = shotDur.toFixed(3);
+  const xE = `${rx}*(${mv.fx}+(${mv.tx}-${mv.fx})*t/${D})`;
+  const yE = `${ry}*(${mv.fy}+(${mv.ty}-${mv.fy})*t/${D})`;
+  const seg = `${TMP}/seg-${String(segs.length).padStart(3, "0")}-${clip.name}.mp4`;
+  // play the clip once, freeze its last frame (clone) if the shot outruns it —
+  // the moving crop keeps it alive — then pan a 1080p window across it.
+  run(["-i", clip.path, "-t", D, "-vf",
+    `fps=${FPS},tpad=stop_mode=clone:stop_duration=60,` +
+    `scale=${SW}:${SH}:force_original_aspect_ratio=increase,crop=${SW}:${SH},setsar=1,` +
+    `crop=${W}:${H}:x=${xE}:y=${yE}`,
+    "-c:v", "libx264", "-preset", "medium", "-crf", "18", "-pix_fmt", "yuv420p", "-r", String(FPS), "-an", seg]);
+  segs.push(seg);
+  t += shotDur;
+}
+console.log(`  ${segs.length} crop-shots cycling ${clips.length} clips → ${t.toFixed(1)}s`);
+
+const listPath = `${TMP}/concat.txt`;
+writeFileSync(listPath, segs.map((s) => `file '${s}'`).join("\n") + "\n");
+console.log(`  concatenating ${segs.length} segments (hard cuts) …`);
+run(["-f", "concat", "-safe", "0", "-i", listPath, "-c", "copy", "-movflags", "+faststart", PLATE]);
+
+rmSync(TMP, { recursive: true, force: true });
+const probe = spawnSync("ffprobe", ["-v", "error", "-show_entries", "format=duration",
+  "-of", "default=noprint_wrappers=1:nokey=1", PLATE], { encoding: "utf8" });
+console.log(`✓ ${rel(PLATE)} · ${Number(probe.stdout?.trim()).toFixed(1)}s · ${W}x${H}@${FPS} silent`);
diff --git a/pop/momboba/bin/chrome-listener.mjs b/pop/momboba/bin/chrome-listener.mjs
new file mode 100644
index 000000000..e6d908628
--- /dev/null
+++ b/pop/momboba/bin/chrome-listener.mjs
@@ -0,0 +1,643 @@
+#!/usr/bin/env node
+// momboba/bin/chrome-listener.mjs — the LANDSCAPE listener video for the
+// full momabobasheep sleep mix (the YouTube "play the whole track" page).
+//
+// This is the long-form twin of bin/chrome-reel.mjs (the 9:16 promo). Where
+// the reel is 56 s of full-motion felt, the listener is a 10-minute video you
+// leave running: a felt still (or motion loop) breathing under a QUIET,
+// LABEL-FREE scrolling score — jas's "video score" idea, dialed way down.
+//
+// Three layers (back → front):
+//   A. background  — a felt diorama still on a slow ken-burns drift
+//      (drawCoverKenBurns from preview-shared). Free; carries the runtime.
+//   B. (future)    — short Seedance loops ping-ponged on key movements.
+//   C. score band  — the scorodeon score (out/*.scorodeon.json) re-pitched as
+//      a single quiet ribbon in the lower third: felt-tinted note pills
+//      scrolling right→left past a fixed centerline. NO labels on the tracks
+//      (jas, 2026-06-15) — no per-note text, no chord glyphs, no lane chips.
+//   D. brand chrome — the pals side-stamps + "momabobasheep" climbing columns
+//      hugging the L/R edges (ported from chrome-reel.mjs), the same mark every
+//      pixsies reel/story wears. NO top-left title, NO bottom progress bar/clock
+//      (jas, 2026-06-15) — just the side stamps + a quiet cross-fading movement
+//      name top-right.
+//
+// Reuses pop/lib/preview-shared.mjs primitives (ken-burns, RMS envelope,
+// YWFT typography, BGRA ffmpeg encode) — same machinery as every pop preview.
+//
+// DRY RUN (no Seedance, no new stills — uses the existing cover):
+//   node pop/momboba/bin/scorodeon-data.mjs                 # ensure score JSON
+//   node pop/momboba/bin/chrome-listener.mjs --frame 360    # one PNG to eyeball
+//   node pop/momboba/bin/chrome-listener.mjs --window 320-410 --dryrun  # ~90s clip
+//
+// FULL (once the look is approved):
+//   node pop/momboba/bin/chrome-listener.mjs --ss 2         # whole 10:00
+//
+// Options:
+//   --bg <img>        background still (default out/momabobasheep-cover.png)
+//   --score <json>    score data (default out/momabobasheep.scorodeon.json)
+//   --audio <mp3>     master (default out/momabobasheep.mp3)
+//   --size WxH        default 1920x1080
+//   --zoom <sec>      seconds of score visible across the width (default 10)
+//   --fps <n>         default 30
+//   --ss <n>          supersample density. NOTE: the ffmpeg encoder is sized
+//                     W*SS × H*SS, so --ss 2 emits a 4K (3840×2160) file — on
+//                     the 8 GB box a full 600 s SS=2 run gets jetsam-killed
+//                     (exit ~144). The plate is already 1080p so SS=2 only
+//                     anti-aliases the vector chrome. Use --ss 1 for the full
+//                     render; --ss 2 only for short --frame / --window checks.
+//   --ribbon <a>      score band opacity 0..1 (default 0.5 — quiet)
+//   --window a-b      render only seconds [a,b] (audio trimmed to match)
+//   --frame <sec>     dump one PNG (out/listener-frame.png) and exit
+//   --dryrun          suffix the output -dryrun (keeps the real name free)
+//   --out <mp4>       explicit output path
+//   --desktop         also copy the result to ~/Desktop
+
+import {
+  readFileSync, writeFileSync, existsSync, mkdtempSync, mkdirSync, rmSync, copyFileSync,
+} from "node:fs";
+import { resolve, dirname, join, basename } from "node:path";
+import { fileURLToPath } from "node:url";
+import { tmpdir, homedir } from "node:os";
+import { spawnSync, spawn } from "node:child_process";
+import { once } from "node:events";
+import { createCanvas, loadImage, ImageData } from "canvas";
+import {
+  decodeAudioMono, computeRmsEnvelope, prerenderTitleChars,
+} from "../../lib/preview-shared.mjs";
+import * as progress from "../../lib/render-progress.mjs";  // Slab menubar heartbeats
+import { makeVerletString, hexToRgb } from "../../lib/cover-engine.mjs";  // /pop string+warp
+
+const HERE = dirname(fileURLToPath(import.meta.url));
+const LANE = resolve(HERE, "..");
+const REPO = resolve(LANE, "..", "..");
+const rel = (p) => p.replace(REPO + "/", "");
+
+const args = process.argv.slice(2);
+const opt = (k, d) => { const i = args.indexOf(`--${k}`); return i >= 0 && args[i + 1] ? args[i + 1] : d; };
+const has = (k) => args.includes(`--${k}`);
+
+// background source: a moving PLATE video (the lush 10-min motion plate from
+// assemble-listener.mjs) OR a single still on a ken-burns drift (dry runs).
+const PLATE = opt("plate", null) ? resolve(process.cwd(), opt("plate", null)) : null;
+const BG    = resolve(process.cwd(), opt("bg",    `${LANE}/out/momabobasheep-cover.png`));
+const SCORE = resolve(process.cwd(), opt("score", `${LANE}/out/momabobasheep.scorodeon.json`));
+const AUDIO = resolve(process.cwd(), opt("audio", `${LANE}/out/momabobasheep.mp3`));
+const needBG = PLATE ? [[PLATE, "plate"]] : [[BG, "background"]];
+for (const [p, what] of [...needBG, [SCORE, "score"], [AUDIO, "audio"]]) {
+  if (!existsSync(p)) { console.error(`✗ missing ${what}: ${rel(p)}`); process.exit(1); }
+}
+
+const [W, H] = opt("size", "1920x1080").split("x").map(Number);
+const ZOOM = parseFloat(opt("zoom", "10"));        // sec of score across the width
+const FPS  = parseInt(opt("fps", "30"), 10);
+const SS   = parseInt(opt("ss", "1"), 10);         // 1 = fast dry run, 2 = final
+const WARP = has("warp") ? parseFloat(opt("warp", "1")) : 0;  // felt warp OFF by default (just the clips)
+const ROT_TURNS = parseFloat(opt("turns", "1"));   // disc rotations over the track
+const BOUNCE = parseFloat(opt("bounce", "0"));     // rotation bounce amount (0 = off, clean linear)
+const WU_STR = parseFloat(opt("bend", "0.55"));    // base string→felt warp strength
+
+const S = JSON.parse(readFileSync(SCORE, "utf8"));
+const DUR = S.dur;
+
+// ── render window (whole track unless --window a-b) ──────────────────────
+let winStart = 0, winEnd = DUR;
+const wflag = opt("window", null);
+if (wflag) {
+  const [a, b] = wflag.split("-").map(Number);
+  winStart = Math.max(0, a); winEnd = Math.min(DUR, b);
+}
+const frameOnly = opt("frame", null) != null ? parseFloat(opt("frame", "0")) : null;
+
+// ── note data — every melodic onset becomes a PLUCK on the verlet string ──
+// (pitch → height on the string, gain → pluck force, lane colour → string
+// tint at that point). No visible track ribbon any more (jas, 2026-06-15) —
+// the music lives in how it bends the string, /pop-video style.
+const notes = [];
+for (const l of S.lanes) {
+  for (const e of l.events) {
+    if (e.pitch == null) continue;                 // beds/ribbons sit this out
+    notes.push({ t: e.t, dur: e.dur, pitch: e.pitch, g: e.g ?? 0.2, color: l.color });
+  }
+}
+notes.sort((a, b) => a.t - b.t);
+let pLo = Infinity, pHi = -Infinity;
+for (const n of notes) { if (n.pitch < pLo) pLo = n.pitch; if (n.pitch > pHi) pHi = n.pitch; }
+const pSpan = Math.max(1, pHi - pLo);
+
+const fmt = (t) => `${Math.floor(t / 60)}:${String(Math.floor(t % 60)).padStart(2, "0")}`;
+
+const TMP = mkdtempSync(join(tmpdir(), "listener-"));
+const cover = PLATE ? null : await loadImage(BG);
+
+// ── audio: trim to the window so env + mux line up with the frames ───────
+let audioPath = AUDIO;
+if (winStart > 0 || winEnd < DUR) {
+  audioPath = join(TMP, "win.wav");
+  const r = spawnSync("ffmpeg", ["-hide_banner", "-loglevel", "error", "-y",
+    "-ss", String(winStart), "-t", String(winEnd - winStart),
+    "-i", AUDIO, audioPath], { stdio: "inherit" });
+  if (r.status !== 0) { console.error("✗ audio trim failed"); process.exit(1); }
+}
+const winDur = winEnd - winStart;
+const { audio, sr } = decodeAudioMono(audioPath);   // mono 4 kHz over the window
+const env = computeRmsEnvelope(audio, sr, FPS, winDur);
+
+// fast shimmer of the envelope (env minus its ½-s mean) — drives the gentle
+// ambient "current" that keeps the string flowing through quiet stretches.
+const envFast = new Float32Array(env.length);
+{
+  const win = Math.max(1, Math.round(FPS * 0.5));
+  let acc = 0;
+  for (let i = 0; i < env.length; i++) {
+    acc += env[i];
+    if (i >= win) acc -= env[i - win];
+    envFast[i] = Math.max(0, env[i] - acc / Math.min(i + 1, win));
+  }
+}
+
+// ── canvas ───────────────────────────────────────────────────────────────
+const canvas = createCanvas(W * SS, H * SS);
+const ctx = canvas.getContext("2d");
+ctx.scale(SS, SS);
+
+// ── the /pop verlet string — a plucked physical thread down the centre that
+// the music tugs (organic, watery) and that bends the felt under it. ───────
+const PLAYHEAD_X = Math.round(W / 2);
+const _vs = makeVerletString(ctx, { W, H, playheadX: PLAYHEAD_X, duration: DUR });
+
+// warpUnderString — snapshot the felt, then redraw a tall strip around the
+// playhead in row-bands, each sheared horizontally by the string's local
+// deflection (sin² window → seamless edges). The picture stays upright but
+// slumps left/right where the string is bent — the chillwave "string-vibe"
+// watery flow. LEAN version: no rotated buffer (that 2200² per-frame copy was
+// the memory hog that thrashed the 8 GB box); the visible string still
+// rotates via withRotation, the warp itself stays upright.
+const WU_HALF = 170, WU_W = WU_HALF * 2, WU_STEP = 6, WU_BANDS = 14, WU_BW = WU_W / WU_BANDS;
+const wuWin = new Float64Array(WU_BANDS);
+for (let b = 0; b < WU_BANDS; b++) wuWin[b] = Math.sin(Math.PI * ((b + 0.5) / WU_BANDS)) ** 2;
+const WU_DSZ = Math.ceil(Math.hypot(W, H)) + 4;
+const wuSnap = createCanvas(W, H), wuSnapC = wuSnap.getContext("2d");
+const wuCR = createCanvas(WU_DSZ, WU_DSZ), wuCRC = wuCR.getContext("2d");
+const ROT_CX = Math.round(W / 2), ROT_CY = Math.round(H / 2);
+function warpUnderString(theta, strength) {
+  const { devPeak } = _vs.deflection();
+  if (Math.abs(devPeak) < 0.6) return;             // string ~straight → skip
+  // snapshot the felt, counter-rotate by −θ so the redraw under +θ keeps the
+  // CONTENT upright while the warp strip rides the rotated string.
+  wuSnapC.clearRect(0, 0, W, H);
+  wuSnapC.drawImage(canvas, 0, 0, W * SS, H * SS, 0, 0, W, H);  // logical snapshot
+  wuCRC.setTransform(1, 0, 0, 1, 0, 0); wuCRC.clearRect(0, 0, WU_DSZ, WU_DSZ);
+  wuCRC.translate(WU_DSZ / 2, WU_DSZ / 2); wuCRC.rotate(-theta); wuCRC.translate(-W / 2, -H / 2);
+  wuCRC.drawImage(wuSnap, 0, 0); wuCRC.setTransform(1, 0, 0, 1, 0, 0);
+  const sox = (WU_DSZ - W) / 2, soy = (WU_DSZ - H) / 2;
+  const x0 = Math.round(PLAYHEAD_X - WU_HALF);
+  ctx.save();
+  ctx.translate(ROT_CX, ROT_CY); ctx.rotate(theta); ctx.translate(-ROT_CX, -ROT_CY);
+  for (let y = 0; y < H; y += WU_STEP) {
+    const dx = (_vs.needleXAt(y) - PLAYHEAD_X) * strength;
+    for (let b = 0; b < WU_BANDS; b++) {
+      const sx = b * WU_BW, shift = dx * wuWin[b];
+      ctx.drawImage(wuCR, sox + x0 + sx, soy + y, WU_BW + 1, WU_STEP,
+        x0 + sx + shift, y, WU_BW + 1, WU_STEP);
+    }
+  }
+  ctx.restore();
+}
+
+// advance the string from the music: pluck on every note onset (organic
+// accents) + a slow ambient current so it always flows like water.
+let noteCursor = 0;
+function pluckFromMusic(now, fi) {
+  while (noteCursor < notes.length && notes[noteCursor].t <= now) {
+    const n = notes[noteCursor++];
+    if (n.t < winStart) continue;                  // pre-window: consume, don't pluck
+    const yy = H * 0.16 + (1 - (n.pitch - pLo) / pSpan) * H * 0.68;
+    const sign = (Math.floor(n.t * 7) % 2) ? 1 : -1;
+    _vs.pluck(yy, (7 + n.g * 18) * WARP, sign, hexToRgb(n.color));
+  }
+  const eF = envFast[Math.min(envFast.length - 1, fi)] ?? 0;
+  const ay = H * (0.30 + 0.40 * (0.5 + 0.5 * Math.sin(now * 0.23 + 1.0)));
+  _vs.pluck(ay, (3 + eF * 8) * WARP, Math.sin(now * 0.41) >= 0 ? 1 : -1);
+}
+
+// ── the TRACK: /pop waveform note-blocks scrolling in lanes, crossing the
+// string. Each note is sampled from the mix into little vertical waveform
+// bars; they ghost in from the right, FLASH bright as they cross the
+// playhead string (in sync with the pluck), then glow as "played". The bars
+// ride the string's local bend so they slump with it. (preview-score-yt's
+// drawLanes, adapted to the scorodeon lanes; no groove rotation — upright.) ──
+const PX_PER_SEC = parseFloat(opt("speed", "700")); // scroll speed past the string — ZOOMED in, elements fly by
+// higher-res mono JUST for the lane waveform shape — the 4 kHz env buffer is
+// too smoothed, so notes read as flat blocks; 22 kHz shows real waveform.
+const WAVE_SR = 22050;
+const { audio: waveAudio } = decodeAudioMono(audioPath, WAVE_SR);
+// push each lane colour AWAY from grey so the rows read as their own hue.
+const satRgb = ([r, g, b], amt) => {
+  const l = 0.3 * r + 0.59 * g + 0.11 * b;
+  return [r + (r - l) * amt, g + (g - l) * amt, b + (b - l) * amt]
+    .map((v) => Math.max(0, Math.min(255, Math.round(v))));
+};
+const LANES = S.lanes
+  .map((l) => ({ name: l.name, rgb: satRgb(hexToRgb(l.color), 0.6), events: l.events.filter((e) => e.pitch != null).sort((a, b) => a.t - b.t) }))
+  .filter((l) => l.events.length);
+const LANE_TOP = H * 0.13, LANE_BOTTOM = H * 0.87;
+const SLOT_H = (LANE_BOTTOM - LANE_TOP) / LANES.length;  // one row's vertical slot
+const GROOVE_R = parseFloat(opt("groove", String(Math.round(Math.min(W, H) * 0.95))));  // record-arc radius
+const DOTS = !has("bars");                           // render samples as tiny dots (default)
+const DOT_SZ = parseFloat(opt("dot", "2.6"));        // tiny-dot size
+const laneCenterY = {};
+LANES.forEach((L, i) => { laneCenterY[L.name] = LANE_TOP + (i + 0.5) * SLOT_H; });
+
+function drawLanes(now) {
+  const halfSpan = (W * 0.62) / PX_PER_SEC;
+  ctx.save();
+  ctx.globalCompositeOperation = "screen";
+  for (const L of LANES) {
+    const yC = laneCenterY[L.name];
+    const [lr, lg, lb] = L.rgb;
+    // NOTE: the track does NOT follow the string bend — the warp only deforms
+    // the felt underneath (jas, 2026-06-15). The waveforms stay clean.
+    for (const ev of L.events) {
+      if (ev.t > now + halfSpan) break;                  // sorted — rest are future
+      const dur = ev.dur || 0.25;
+      if (ev.t + dur < now - halfSpan) continue;
+      const visDur = Math.min(dur, 0.30);                // cap sustain width
+      const ex = PLAYHEAD_X + (ev.t - now) * PX_PER_SEC;
+      const ew = Math.max(4, visDur * PX_PER_SEC);
+      const fullH = SLOT_H * 0.62;                        // NORMALIZED row height
+      const cols = Math.max(6, Math.floor(ew / 2.5));     // MORE data samples
+      const blockW = Math.max(1, ew / cols - 1.2);        // THIN lines + space between
+      const startSamp = Math.max(0, Math.floor((ev.t - winStart) * WAVE_SR));
+      const endSamp = Math.min(waveAudio.length - 1, Math.floor((ev.t - winStart + visDur) * WAVE_SR));
+      // NORMALIZE to THIS note's own peak so every note fills the row evenly
+      // (quiet notes no longer read as flat slivers).
+      let notePeak = 1e-5;
+      for (let s = startSamp; s <= endSamp; s++) { const a = Math.abs(waveAudio[s]); if (a > notePeak) notePeak = a; }
+      const norm = 1 / notePeak;
+      const spc = (endSamp - startSamp) / cols;
+      for (let c = 0; c < cols; c++) {
+        const s0 = startSamp + Math.floor(c * spc), s1 = Math.min(endSamp, startSamp + Math.floor((c + 1) * spc));
+        let pk = 0; for (let s = s0; s < s1; s++) { const a = Math.abs(waveAudio[s]); if (a > pk) pk = a; }
+        pk = Math.min(1, pk * norm);                      // 0..1 within the note
+        const dt = now - (ev.t + (c / cols) * visDur);
+        let alpha = 0.30, bright = 0;
+        if (dt >= 0 && dt < 0.06) { alpha = 1.0; bright = 0.32; }   // CROSSING — flash
+        else if (dt >= 0.06) { alpha = 0.9; bright = 0.42; }        // PLAYED — glowy
+        const fr = Math.round(lr + (255 - lr) * bright);            // keep the HUE
+        const fg = Math.round(lg + (255 - lg) * bright);
+        const fb = Math.round(lb + (255 - lb) * bright);
+        const half = Math.max(DOTS ? 0 : 2, (pk * fullH) / 2);
+        const bx = ex + (c / cols) * ew;
+        // GROOVE CURVE — rotate each block about the disc centre by its
+        // distance from the string, so the rows bow into record-groove arcs.
+        const aGroove = (bx - PLAYHEAD_X) / GROOVE_R;
+        ctx.save();
+        ctx.translate(ROT_CX, ROT_CY); ctx.rotate(aGroove); ctx.translate(-ROT_CX, -ROT_CY);
+        ctx.fillStyle = `rgba(${fr},${fg},${fb},${alpha.toFixed(3)})`;
+        if (DOTS) {                                       // tiny dots tracing the waveform envelope
+          ctx.fillRect(bx, yC - half - DOT_SZ / 2, DOT_SZ, DOT_SZ);
+          ctx.fillRect(bx, yC + half - DOT_SZ / 2, DOT_SZ, DOT_SZ);
+        } else {
+          ctx.fillRect(bx, yC - half, blockW, half * 2);
+        }
+        ctx.restore();
+      }
+    }
+  }
+  ctx.restore();
+  ctx.globalCompositeOperation = "source-over";
+}
+
+// ── D. pals side-stamp identity (ported from chrome-reel.mjs) ─────────────
+// Two purple-pals logos hugging the L/R edges (rotated ±90°, drowsy wiggle +
+// LED pulse on the swells) with "momabobasheep" as per-character climbing
+// columns — the same brand mark every pixsies reel/story wears.
+const envAtT = (t) =>
+  env[Math.max(0, Math.min(env.length - 1, Math.floor((t - winStart) * FPS)))] ?? 0;
+
+// per-movement felt tint (warm night); brightened toward white by progress
+const MOVE_TINTS = {
+  dusk: [150, 168, 196], drowse: [196, 162, 126], descend: [176, 110, 78],
+  deep: [92, 128, 182], dream: [150, 132, 196], still: [184, 176, 160],
+  vivid: [160, 136, 200], morning: [206, 168, 120], resolve: [150, 150, 176],
+};
+const assetsDir = join(TMP, "chrome-assets");
+mkdirSync(assetsDir, { recursive: true });
+
+const TITLE = S.title.charAt(0).toUpperCase() + S.title.slice(1);  // "Momabobasheep"
+const { chars: titleChars, totalWidth: titleTotalW } = await prerenderTitleChars({
+  text: TITLE, ptSize: 96, palette: ["#FFFFFF"], shadowColor: null, assetsDir,
+});
+const PALS_S = 118, PALS_HALF = PALS_S / 2;
+const EDGE_X = 58;                                   // logical px from the edge
+const CHAR_SCALE = (H * 0.30) / Math.max(1, titleTotalW);
+const CHAR_SPAN = titleTotalW * CHAR_SCALE;
+const BOUNCE_BUF = 20;
+// staggered on Y so the two side marks aren't parallel: LEFT lower, RIGHT higher
+const LCHARS_CY = H * 0.74, RCHARS_CY = H * 0.34;    // left badge dropped lower
+// pals sits BEFORE the first char on each side. Left column reads top→bottom
+// (start at top → pals above); right column reads bottom→top (start at bottom
+// → pals below). Right was at the top = AFTER the title; flip it under.
+const LPALS_CY = LCHARS_CY - CHAR_SPAN / 2 - BOUNCE_BUF - PALS_HALF;
+const RPALS_CY = RCHARS_CY + CHAR_SPAN / 2 + BOUNCE_BUF + PALS_HALF;
+
+const PALS_WM_SIZE = 200;
+let palsImg = null, palsBlur = null;
+{
+  const svg = `${REPO}/system/public/purple-pals.svg`;
+  const png = `${assetsDir}/pals.png`, blurPng = `${assetsDir}/pals-blur.png`;
+  const r = spawnSync("rsvg-convert", ["-w", String(PALS_WM_SIZE * 2), "-h", String(PALS_WM_SIZE * 2), "-o", png, svg]);
+  if (r.status === 0 && existsSync(png)) {
+    palsImg = await loadImage(png);
+    const rb = spawnSync("magick", [png, "-channel", "A", "-blur", "0x1.5", "+channel", blurPng]);
+    palsBlur = (rb.status === 0 && existsSync(blurPng)) ? await loadImage(blurPng) : palsImg;
+  }
+}
+if (!palsImg) console.error("⚠ pals watermark failed to rasterize — chrome will skip it");
+
+// offscreen tinting canvases (used purely as image sources)
+const wmCanvas = createCanvas(8, 8), wmCtx = wmCanvas.getContext("2d");
+const charTintCanvas = createCanvas(2, 2), charTintCtx = charTintCanvas.getContext("2d");
+
+function sectionRgb(now) {
+  const m = S.movements?.find((x) => now >= x.t0 && now < x.t1) ?? S.movements?.at(-1);
+  const [r, g, b] = MOVE_TINTS[m?.name] ?? [180, 180, 180];
+  const lp = m ? Math.max(0, Math.min(1, (now - m.t0) / Math.max(0.001, m.t1 - m.t0))) : 0;
+  const k = 0.28 * lp;
+  return [Math.round(r + (255 - r) * k), Math.round(g + (255 - g) * k), Math.round(b + (255 - b) * k)];
+}
+function palsTinted(rgb, src) {
+  const ww = src.width, wh = src.height;
+  wmCanvas.width = ww; wmCanvas.height = wh;
+  wmCtx.clearRect(0, 0, ww, wh);
+  wmCtx.globalCompositeOperation = "source-over"; wmCtx.drawImage(src, 0, 0);
+  wmCtx.globalCompositeOperation = "source-in";
+  wmCtx.fillStyle = `rgb(${rgb[0]},${rgb[1]},${rgb[2]})`; wmCtx.fillRect(0, 0, ww, wh);
+  wmCtx.globalCompositeOperation = "source-over";
+  return wmCanvas;
+}
+function tintCharGlyph(img, rgb) {
+  const w = img.width, h = img.height;
+  charTintCanvas.width = w; charTintCanvas.height = h;
+  charTintCtx.globalCompositeOperation = "source-over";
+  charTintCtx.clearRect(0, 0, w, h); charTintCtx.drawImage(img, 0, 0);
+  charTintCtx.globalCompositeOperation = "source-in";
+  charTintCtx.fillStyle = `rgb(${rgb[0]},${rgb[1]},${rgb[2]})`; charTintCtx.fillRect(0, 0, w, h);
+  charTintCtx.globalCompositeOperation = "source-over";
+  return charTintCanvas;
+}
+
+function drawWatermark(now, e0) {
+  if (!palsImg) return;
+  const s = PALS_S, TAU = Math.PI * 2, u = now / DUR;
+  const col = sectionRgb(now);
+  const glow = Math.min(1, e0) ** 2;
+  const ledCol = [
+    Math.round(col[0] + (255 - col[0]) * glow * 0.6),
+    Math.round(col[1] + (255 - col[1]) * glow * 0.6),
+    Math.round(col[2] + (255 - col[2]) * glow * 0.6),
+  ];
+  const wig = 9 * Math.sin(TAU * 26 * u + 0.7) + 3 * Math.sin(TAU * 9 * u);
+  const bob = 2.2 * Math.sin(TAU * 17 * u + 2.1) + 1.1 * Math.sin(TAU * 31 * u);
+  const swiv = 0.04 * Math.sin(TAU * 19 * u) + 0.02 * Math.sin(TAU * 38 * u + 1.4);
+  const spots = [
+    { cx: EDGE_X - wig, cy: LPALS_CY + bob, rot: Math.PI / 2 + swiv },
+    { cx: W - EDGE_X + wig, cy: RPALS_CY - bob, rot: -Math.PI / 2 - swiv },
+  ];
+  const passes = [["multiply", 0.78], ["color-burn", 0.42], ["overlay", 0.58], ["source-over", 0.06]];
+  for (const sp of spots) {
+    ctx.save();
+    ctx.translate(sp.cx, sp.cy); ctx.rotate(sp.rot);
+    palsTinted([0, 0, 0], palsImg);                  // soft drop shadow
+    ctx.globalCompositeOperation = "source-over"; ctx.globalAlpha = 0.24;
+    ctx.drawImage(wmCanvas, -s / 2 + 3, -s / 2 + 4, s, s);
+    palsTinted(col, palsBlur);                       // 4-pass felt seep
+    for (const [op, a] of passes) {
+      ctx.globalCompositeOperation = op; ctx.globalAlpha = a;
+      ctx.drawImage(wmCanvas, -s / 2, -s / 2, s, s);
+    }
+    ctx.globalCompositeOperation = "source-over"; ctx.globalAlpha = 0.30;
+    ctx.drawImage(wmCanvas, -s / 2, -s / 2, s, s);
+    if (glow > 0.001) {                              // LED pulse on the swells
+      palsTinted(ledCol, palsBlur);
+      ctx.globalCompositeOperation = "screen"; ctx.globalAlpha = 0.14 + 0.7 * glow;
+      ctx.drawImage(wmCanvas, -s / 2, -s / 2, s, s);
+      palsTinted(ledCol, palsImg);
+      ctx.globalCompositeOperation = "source-over"; ctx.globalAlpha = 0.16 + 0.42 * glow;
+      ctx.drawImage(wmCanvas, -s / 2, -s / 2, s, s);
+    }
+    ctx.restore();
+  }
+  ctx.globalCompositeOperation = "source-over"; ctx.globalAlpha = 1;
+  drawPalsTitleChars(now);
+}
+
+function drawPalsTitleChars(now) {
+  const TAU = Math.PI * 2, u = now / DUR;
+  const wig = 8 * Math.sin(TAU * 30 * u + 3.6) + 3 * Math.sin(TAU * 12 * u + 1.1);
+  const span = CHAR_SPAN;
+  const palsRgb = sectionRgb(now);
+  const spots = [
+    { charsCx: EDGE_X + 4 - wig, cy: LCHARS_CY, rot: Math.PI / 2 },
+    { charsCx: W - EDGE_X - 4 + wig, cy: RCHARS_CY, rot: -Math.PI / 2 },
+  ];
+  const startX = -span / 2;
+  for (const sp of spots) {
+    ctx.save();
+    ctx.translate(sp.charsCx, sp.cy); ctx.rotate(sp.rot);
+    for (let i = 0; i < titleChars.length; i++) {
+      const ch = titleChars[i];
+      if (!ch.img) continue;
+      const x = startX + ch.prefixWidth * CHAR_SCALE;
+      const dw = ch.img.width * CHAR_SCALE, dh = ch.img.height * CHAR_SCALE;
+      const charEnv = envAtT(now - i * 0.03);
+      const lift = 3 * Math.sin(now * 3.0 + i * 0.8) * (0.3 + charEnv);
+      const y = -dh / 2 + lift;
+      const charRot = 0.025 * Math.sin(now * 3.1 + i * 1.15);
+      ctx.save();
+      ctx.translate(x + dw / 2, y + dh / 2); ctx.rotate(charRot);
+      ctx.translate(-(x + dw / 2), -(y + dh / 2));
+      const sh = 0.5 + 0.5 * Math.sin(now * 3.2 - i * 0.7);
+      const charRgb = [
+        Math.round(palsRgb[0] + (255 - palsRgb[0]) * sh * 0.35),
+        Math.round(palsRgb[1] + (255 - palsRgb[1]) * sh * 0.35),
+        Math.round(palsRgb[2] + (255 - palsRgb[2]) * sh * 0.35),
+      ];
+      ctx.globalCompositeOperation = "source-over"; ctx.globalAlpha = 0.24;
+      ctx.drawImage(tintCharGlyph(ch.img, [0, 0, 0]), x + 3, y + 4, dw, dh);
+      for (const [op, a] of [["multiply", 0.78], ["color-burn", 0.42], ["overlay", 0.58], ["source-over", 0.06]]) {
+        ctx.globalCompositeOperation = op; ctx.globalAlpha = a;
+        ctx.drawImage(tintCharGlyph(ch.img, charRgb), x, y, dw, dh);
+      }
+      ctx.globalCompositeOperation = "source-over"; ctx.globalAlpha = 0.46;
+      ctx.drawImage(tintCharGlyph(ch.img, palsRgb), x, y, dw, dh);
+      if (charEnv > 0.45) {                           // shimmer glint on swells
+        ctx.globalCompositeOperation = "screen";
+        ctx.globalAlpha = 0.14 + 0.46 * Math.min(1, (charEnv - 0.45) / 0.55);
+        ctx.drawImage(tintCharGlyph(ch.img, charRgb), x, y, dw, dh);
+      }
+      ctx.restore();
+    }
+    ctx.restore();
+  }
+  ctx.globalCompositeOperation = "source-over"; ctx.globalAlpha = 1;
+}
+
+let envBounce = 0, rotSpring = 0;                     // smooth-rotation easing state
+function drawFrame(now, fi, plate) {
+  const e0 = env[Math.min(env.length - 1, fi)] ?? 0;
+
+  // advance the verlet string from the music (organic, watery flow)
+  pluckFromMusic(now, fi);
+  _vs.step();
+
+  // ── A. background — the felt motion plate, drawn upright ───────────────
+  if (plate) ctx.putImageData(plate, 0, 0);
+  else drawCoverKB(now, e0);
+
+  // ── B. the rotating disc — felt bends under the string, and the track
+  //       (waveform note-blocks) + string spin together as one record ────
+  // bouncy + smooth: steady base drift + an underdamped spring the music
+  // nudges (overshoots & settles) + a slow sine bob — not a stiff clock.
+  let rotMod = 0;                                        // bounce OFF by default
+  if (BOUNCE) {
+    envBounce += (e0 - envBounce) * 0.04;
+    rotSpring += (envBounce - rotSpring) * 0.08;
+    rotMod = (rotSpring * 0.5 + 0.02 * Math.sin(now * 0.4)) * BOUNCE;
+  }
+  const theta = (now / DUR) * Math.PI * 2 * ROT_TURNS + rotMod;
+  if (WARP) warpUnderString(theta, WU_STR * WARP);        // felt still bends
+  // string + track removed (jas, 2026-06-16) — the (invisible) plucked string
+  // keeps deforming the felt; toggle the overlay back on with --overlay.
+  if (has("overlay")) _vs.withRotation(theta, () => { drawLanes(now); _vs.draw(); });
+
+  // ── C. pals side-stamps + climbing title columns (the brand mark) ──────
+  drawWatermark(now, e0);
+}
+
+// ken-burns wrapper — square cover into landscape, gentle and sleepy
+function drawCoverKB(now, e0) {
+  // inline (preview-shared.drawCoverKenBurns expects device-px canvas; our
+  // ctx is logical-scaled, so call it against the logical W/H via a shim)
+  drawKB(ctx, cover, now, {
+    baseScale: 1.06, breathAmp: 0.05, breathPeriodSec: 24,
+    env: e0, wobbleAmp: 10, envWobbleAmp: 12,
+  });
+}
+
+// a logical-space ken-burns (mirrors preview-shared, sized to W×H not canvas px)
+function drawKB(c, img, t, o) {
+  const baseScale = o.baseScale, breathAmp = o.breathAmp, breathT = o.breathPeriodSec;
+  const e = o.env ?? 0, wAmp = o.wobbleAmp, wEnv = o.envWobbleAmp;
+  const coverScale = Math.max(W / img.width, H / img.height);
+  const breath = breathAmp * (0.5 - 0.5 * Math.cos(t * (2 * Math.PI / breathT)));
+  const zoom = baseScale + breath;
+  const bw = img.width * coverScale * zoom, bh = img.height * coverScale * zoom;
+  const wx = wAmp * Math.sin(t * 0.5) + wAmp * 0.4 * Math.cos(t * 0.9) + e * wEnv * Math.sin(t * 1.6);
+  const wy = wAmp * 0.7 * Math.cos(t * 0.6) + e * wEnv * 0.7 * Math.cos(t * 1.3);
+  let dx = (W - bw) / 2 + wx, dy = (H - bh) / 2 + wy;
+  dx = Math.min(0, Math.max(W - bw, dx));
+  dy = Math.min(0, Math.max(H - bh, dy));
+  c.fillStyle = "#0b0712"; c.fillRect(0, 0, W, H);
+  c.drawImage(img, dx, dy, bw, bh);
+}
+
+// ── plate frame source (the lush motion background) ──────────────────────
+const PLATE_W = W * SS, PLATE_H = H * SS, PLATE_BYTES = PLATE_W * PLATE_H * 4;
+
+// decode the plate to raw RGBA frames at device resolution, from winStart.
+function openPlateStream() {
+  return spawn("ffmpeg", ["-hide_banner", "-loglevel", "error",
+    ...(winStart > 0 ? ["-ss", String(winStart)] : []),
+    "-i", PLATE, "-f", "rawvideo", "-pix_fmt", "rgba",
+    "-s", `${PLATE_W}x${PLATE_H}`, "-r", String(FPS), "-"],
+    { stdio: ["ignore", "pipe", "ignore"] });
+}
+
+// a frame reader over a paused stream: returns the next frame as ImageData,
+// or null at end-of-stream (caller holds the last frame to the finish).
+function makeFrameReader(stream) {
+  let buf = Buffer.alloc(0), ended = false;
+  stream.on("end", () => { ended = true; });
+  return async function next() {
+    while (buf.length < PLATE_BYTES) {
+      const chunk = stream.read();
+      if (chunk) { buf = Buffer.concat([buf, chunk]); continue; }
+      if (ended) return null;
+      await once(stream, "readable").catch(() => { ended = true; });
+    }
+    const frame = buf.subarray(0, PLATE_BYTES);
+    buf = buf.subarray(PLATE_BYTES);
+    return new ImageData(new Uint8ClampedArray(frame), PLATE_W, PLATE_H);
+  };
+}
+
+// one plate frame at absolute time t (for --frame).
+function plateFrameAt(t) {
+  const r = spawnSync("ffmpeg", ["-hide_banner", "-loglevel", "error",
+    "-ss", String(t), "-i", PLATE, "-frames:v", "1",
+    "-f", "rawvideo", "-pix_fmt", "rgba", "-s", `${PLATE_W}x${PLATE_H}`, "-"],
+    { encoding: "buffer", maxBuffer: PLATE_BYTES + 4096 });
+  if (r.status !== 0 || !r.stdout || r.stdout.length < PLATE_BYTES) return null;
+  return new ImageData(new Uint8ClampedArray(r.stdout.subarray(0, PLATE_BYTES)), PLATE_W, PLATE_H);
+}
+
+// ── --frame: dump one PNG and exit ───────────────────────────────────────
+if (frameOnly != null) {
+  const localFi = Math.round((frameOnly - winStart) * FPS);
+  drawFrame(frameOnly, Math.max(0, localFi), PLATE ? plateFrameAt(frameOnly) : null);
+  const fp = `${LANE}/out/listener-frame.png`;
+  writeFileSync(fp, canvas.toBuffer("image/png"));
+  rmSync(TMP, { recursive: true, force: true });
+  console.log(`✓ frame @${frameOnly}s → ${rel(fp)}`);
+  process.exit(0);
+}
+
+// ── encode ───────────────────────────────────────────────────────────────
+let OUT = opt("out", null);
+if (!OUT) {
+  const suffix = has("dryrun") ? "-listener-dryrun" : "-listener";
+  OUT = `${LANE}/out/momabobasheep${suffix}.mp4`;
+}
+OUT = resolve(process.cwd(), OUT);
+
+const total = Math.ceil(winDur * FPS);
+console.log(`▸ listener · ${S.title} · ${W * SS}x${H * SS}@${FPS} (${SS}x) · zoom ${ZOOM}s · window ${fmt(winStart)}–${fmt(winEnd)} · ${total} frames`);
+progress.begin({ type: "video", label: `${TITLE} listener · ${total} frames` });  // → Slab bar
+// custom encode so we can run a SHARPENING post-pass (unsharp ≈ lanczos edge
+// sharpen) over the overlaid UI — crisps the thin waveform lines + string.
+const SHARP = has("nosharp") ? null : parseFloat(opt("sharp", "1.3"));
+const enc = spawn("ffmpeg", ["-hide_banner", "-loglevel", "error", "-y",
+  "-f", "rawvideo", "-pix_fmt", "bgra", "-s", `${W * SS}x${H * SS}`, "-r", String(FPS), "-i", "-",
+  "-i", audioPath,
+  ...(SHARP ? ["-vf", `unsharp=5:5:${SHARP}:5:5:${(SHARP * 0.5).toFixed(2)}`] : []),  // whole-frame luma+chroma
+  "-c:v", "libx264", "-preset", "faster", "-crf", "19", "-threads", "0",
+  "-c:a", "aac", "-b:a", "192k", "-pix_fmt", "yuv420p", "-shortest", "-movflags", "+faststart", OUT],
+  { stdio: ["pipe", "inherit", "inherit"] });
+const plateProc = PLATE ? openPlateStream() : null;
+const nextPlate = plateProc ? makeFrameReader(plateProc.stdout) : null;
+let lastPlate = null;
+const t0 = Date.now();
+for (let fi = 0; fi < total; fi++) {
+  let plate = null;
+  if (nextPlate) { plate = await nextPlate(); if (plate) lastPlate = plate; else plate = lastPlate; }
+  drawFrame(winStart + fi / FPS, fi, plate);
+  if (!enc.stdin.write(canvas.toBuffer("raw"))) await once(enc.stdin, "drain");
+  progress.update(((fi + 1) / total) * 100, { done: fi + 1, total });
+  if (total >= 10 && fi % Math.floor(total / 10) === 0)
+    console.log(`  ${Math.round((fi / total) * 100)}% · ${((Date.now() - t0) / 1000).toFixed(0)}s`);
+}
+enc.stdin.end();
+if (plateProc) { try { plateProc.kill(); } catch { /* already gone */ } }
+await new Promise((res, rej) => { enc.on("close", (c) => (c === 0 ? res() : rej(new Error(`ffmpeg exit ${c}`)))); });
+progress.end();
+rmSync(TMP, { recursive: true, force: true });
+console.log(`✓ ${rel(OUT)} (${((Date.now() - t0) / 1000).toFixed(0)}s)`);
+if (has("desktop")) {
+  const d = join(homedir(), "Desktop", basename(OUT));
+  copyFileSync(OUT, d);
+  console.log(`✓ → ${d}`);
+}
+process.exit(0);  // force-exit: a lingering plate/encode pipe child can keep
+                  // the event loop alive at 0% CPU after a successful render
+                  // (the zombies that piled up + thrashed the 8 GB box).
diff --git a/pop/momboba/bin/gen-motion-listener.mjs b/pop/momboba/bin/gen-motion-listener.mjs
new file mode 100644
index 000000000..aea74e025
--- /dev/null
+++ b/pop/momboba/bin/gen-motion-listener.mjs
@@ -0,0 +1,106 @@
+#!/usr/bin/env node
+// momboba/bin/gen-motion-listener.mjs — the LANDSCAPE listener motion pass.
+// Seedance 2.0 over the 9 felt movement stills (pano/out/NN-*.png), 16:9.
+// Thin lane driver over pop/lib/motion-pipeline.mjs — the SHOTS table is the
+// creative surface; pricing, generation, take archiving and picks live there.
+//
+// KEY DIFFERENCE from the reel: generation length ≠ playback length. Each
+// movement plays for up to ~3 minutes in the final video, but we only PAY to
+// generate a short (5 s; the-dream hero 12 s) gentle loopable clip per
+// movement. bin/assemble-listener.mjs ping-pongs + tiles each clip to its
+// real movement length. So the GENERATION struct below uses short sections
+// purely to clamp motion-pipeline's per-shot Seedance duration (it bills
+// ceil(section length), clamped [4,15] — line 58 of motion-pipeline.mjs).
+//
+//   8 movements × 5 s + the-dream × 12 s = 52 s billed ≈ $12.58 @ fast 720p.
+//
+// All CUTS — no morphs (cross-scene morphs invent doubled figures; the sleepy
+// pace wants cuts anyway). Each clip is tiny + slow + returns near its start
+// so the ping-pong loop is seamless.
+//
+// Usage:
+//   node pop/momboba/bin/gen-motion-listener.mjs --dry-run    # prompts + cost
+//   node pop/momboba/bin/gen-motion-listener.mjs              # gen missing shots
+//   node pop/momboba/bin/gen-motion-listener.mjs --only the-dream --force
+//   node pop/bin/audition-motion.mjs --lane momboba --slug momabobasheep-listener
+
+import { writeFileSync } from "node:fs";
+import { resolve, dirname } from "node:path";
+import { fileURLToPath } from "node:url";
+import { runMotionCli, parseFlags } from "../../lib/motion-pipeline.mjs";
+import { NEEDLE_FELT_WOOL_MOTION, FRAMING_YT_LANDSCAPE_MOTION } from "../../lib/mediums.mjs";
+
+const HERE = dirname(fileURLToPath(import.meta.url));
+const LANE = resolve(HERE, "..");
+const OUT = `${LANE}/out`;
+const PANO = `${LANE}/pano/out`;
+
+const MEDIUM_MOTION = [
+  `Hushed museum light. Sleepy lullaby pacing — every motion tiny, slow, and tender; nothing sudden anywhere. The shot opens and closes in nearly the same pose so it can loop gently.`,
+  FRAMING_YT_LANDSCAPE_MOTION,
+  NEEDLE_FELT_WOOL_MOTION,
+].join("\n\n");
+
+// movement → panel. names match pano/NN-<name>.txt and the struct below.
+const PANEL = {
+  arrival: `${PANO}/01-arrival.png`,
+  "boba-sip": `${PANO}/02-boba-sip.png`,
+  galleries: `${PANO}/03-galleries.png`,
+  "waterlily-awe": `${PANO}/04-waterlily-awe.png`,
+  "first-sheep": `${PANO}/05-first-sheep.png`,
+  "asleep-flock": `${PANO}/06-asleep-flock.png`,
+  "the-dream": `${PANO}/07-the-dream.png`,
+  morning: `${PANO}/08-morning.png`,
+  resolve: `${PANO}/09-resolve.png`,
+};
+
+// the GENERATION struct — short sections only to size each Seedance shot.
+// the-dream is the 12 s hero; everything else is a 5 s loopable breath.
+const GEN = [
+  ["arrival", 5], ["boba-sip", 5], ["galleries", 5], ["waterlily-awe", 5],
+  ["first-sheep", 5], ["asleep-flock", 5], ["the-dream", 12], ["morning", 5],
+  ["resolve", 5],
+];
+let acc = 0;
+const structPath = `${LANE}/pano/motion-struct.json`;
+writeFileSync(structPath, JSON.stringify({
+  totalSec: GEN.reduce((a, [, d]) => a + d, 0),
+  sections: GEN.map(([name, d]) => { const s = { name, startSec: acc, endSec: acc + d }; acc += d; return s; }),
+}, null, 2));
+
+// The still carries the LOOK; the prompt carries only MOTION — tiny + slow.
+const SHOTS = {
+  arrival: { motion:
+`The felt jeffrey doll walks slowly toward the museum doors with small unhurried puppet strides, the camera following at a gentle walking drift. The tiny felted boba stays firmly wrapped in his fingers — full milk-tea, dark wool pearls at the bottom — and never leaves his grip, never floats. Soft dusk light. Hopeful, calm, sleepy.` },
+  "boba-sip": { motion:
+`Close-ish on the felt jeffrey doll taking one long slow happy sip from the fat pastel straw — cheeks hollowing a hair, eyes half-lidded, the dark wool tapioca pearls stirring gently inside the pale cup. Both felt hands cradle the cup. Behind him the soft hanging mobile turns very slowly. The camera holds nearly still, drifting in by a breath.` },
+  galleries: { motion:
+`The felt jeffrey doll strolls at a slowing dawdle down the long gallery corridor, boba held snug in his hand, head turning softly from one framed abstract felt artwork to the next, posture loosening. The camera tracks alongside at his slowing pace. Quiet top-light; nothing else in the corridor moves.` },
+  "waterlily-awe": { motion:
+`The felt jeffrey doll stands tiny and still before the monumental felted water-lily tapestry, head tilting slowly back in awe, the boba dangling securely from his curled fingers. The vast wall of wool blues and greens shimmers almost imperceptibly, fibers catching the dim light. The camera rises very slowly up the tapestry, keeping the little doll anchored low in frame. Reverent, hushed.` },
+  "first-sheep": { motion:
+`The single needle-felted sheep peeks in from the gallery doorway at the frame edge with one slow careful step, woolly head turning toward the drowsy felt jeffrey doll slumped on the bench, whose head droops a little lower. A tiny curious lean from the sheep, a deeper slump from the doll. The camera holds wide and still — the moment before counting begins.` },
+  "asleep-flock": { motion:
+`The felt jeffrey doll lies fully asleep along the felt bench, his side rising and falling in a slow sleep-breath rhythm. Around him on the wide felt floor the small flock of needle-felted sheep barely stir — one shifts its weight, one lowers its woolly head to graze. The monumental water-lily tapestry glows softly above. The camera holds still. Deeply tender.` },
+  "the-dream": { motion:
+`Inside the painting: the felt jeffrey doll floats curled-up and asleep on the giant wool lily pad at centre, rocking almost imperceptibly as the felted pond ripples outward in slow wool waves of blue, green and lilac all around him. Above, two or three woolly sheep drift slowly across the felt sky like clouds. The camera drifts upward and away with the sheep, weightless and dreamy. The richest, slowest, happiest moment of the night.` },
+  morning: { motion:
+`Pale dawn light slowly warms the felt gallery from grey toward soft peach. The felt jeffrey doll begins to stir — lifting his tousled wool head a little, blinking awake behind his red felt glasses. The tipped-over empty boba cup rests beside him; one felt sheep settles down nearby. The camera holds nearly still. Tender, calm, waking.` },
+  resolve: { motion:
+`A final calm wide view: the felt jeffrey doll sits up at the end of the long bench, rested and softly smiling, the empty boba cup cradled in his lap, breathing slow and easy. The felt sheep are curled down asleep across the floor, barely stirring. Warm even daylight. The camera is almost perfectly still. Settled, content, home.` },
+};
+
+const cfg = {
+  slug: "momabobasheep-listener",
+  laneDir: LANE,
+  structPath,
+  panelFor: (name) => PANEL[name],
+  shots: SHOTS,
+  mediumMotion: MEDIUM_MOTION,
+  ratio: "16:9",
+  resolution: "720p",
+  audio: `${OUT}/momabobasheep.mp3`,
+  finalOut: `${OUT}/momabobasheep-listener-motion.mp4`, // unused (custom assembly)
+};
+
+await runMotionCli(cfg, parseFlags());
diff --git a/pop/momboba/bin/gen-panels-listener.mjs b/pop/momboba/bin/gen-panels-listener.mjs
new file mode 100644
index 000000000..b7b5744fc
--- /dev/null
+++ b/pop/momboba/bin/gen-panels-listener.mjs
@@ -0,0 +1,91 @@
+#!/usr/bin/env node
+// gen-panels-listener.mjs — generate the 9 LANDSCAPE felt-diorama stills
+// for the momabobasheep YouTube listener video (one per movement) via
+// gpt-image-2 with jeffrey identity refs. Wide 1536x1024 (16:9-ish), the
+// landscape twin of gen-reel.mjs (which makes the 9:16 reel panels).
+//
+// Prompts: pop/momboba/pano/NN-*.txt — each is PREAMBLE.txt + the beat.
+// Output:  pop/momboba/pano/out/NN-*.png (+ ~/Desktop mirror)
+//
+// Run:  node pop/momboba/bin/gen-panels-listener.mjs           # skips existing
+//       node pop/momboba/bin/gen-panels-listener.mjs --force   # regen all
+//       node pop/momboba/bin/gen-panels-listener.mjs --only 07 # one movement
+
+import { readFileSync, writeFileSync, readdirSync, mkdirSync, existsSync, copyFileSync } from "node:fs";
+import { resolve, dirname, basename, join } from "node:path";
+import { fileURLToPath } from "node:url";
+import { homedir } from "node:os";
+
+const HERE = dirname(fileURLToPath(import.meta.url));
+const LANE = resolve(HERE, "..");
+const REPO = resolve(LANE, "..", "..");
+const PANO = join(LANE, "pano");
+const OUT = join(PANO, "out");
+mkdirSync(OUT, { recursive: true });
+
+const FORCE = process.argv.includes("--force");
+const _af = (k) => { const i = process.argv.indexOf(k); return i >= 0 ? process.argv[i + 1] : null; };
+const ONLY = _af("--only");
+const SIZE = "1536x1024";                          // wide landscape
+
+// identity refs — same set as gen-illy.mjs / gen-reel.mjs
+const SHOOT_DIR = `${REPO}/portraits/jeffrey/corpus/shoot-2k`;
+const ARCHIVE_DIR = `${REPO}/portraits/jeffrey/ig-archive/whistlegraph`;
+const REFS = [
+  `${SHOOT_DIR}/jeffery-av--07.jpg`,
+  `${SHOOT_DIR}/jeffery-av--01.jpg`,
+  `${SHOOT_DIR}/jeffery-av--04.jpg`,
+  `${ARCHIVE_DIR}/2018-12-02_Bq4ckGFFNtW.jpg`,
+  `${ARCHIVE_DIR}/2020-09-02_CEpxlO2FOvD.jpg`,
+  `${ARCHIVE_DIR}/2021-07-10_CRI095Vl7AO_1.jpg`,
+  `${ARCHIVE_DIR}/2025-01-25_DFQ2lHPzN_W.jpg`,
+].filter(existsSync);
+
+function loadOpenAIKey() {
+  if (process.env.OPENAI_API_KEY) return process.env.OPENAI_API_KEY;
+  const vault = `${REPO}/aesthetic-computer-vault/.devcontainer/envs/devcontainer.env`;
+  if (existsSync(vault)) {
+    for (const line of readFileSync(vault, "utf8").split("\n"))
+      if (line.startsWith("OPENAI_API_KEY=")) return line.slice(15).trim().replace(/^['"]|['"]$/g, "");
+  }
+  throw new Error("OPENAI_API_KEY not found");
+}
+const apiKey = loadOpenAIKey();
+const preamble = readFileSync(join(PANO, "PREAMBLE.txt"), "utf8").trim();
+
+const beats = readdirSync(PANO).filter((f) => /^\d\d-.*\.txt$/.test(f)).sort();
+for (const f of beats) {
+  if (ONLY && !f.startsWith(ONLY)) continue;
+  const png = join(OUT, f.replace(".txt", ".png"));
+  if (existsSync(png) && !FORCE) { console.log(`· cached ${basename(png)}`); continue; }
+  const prompt = `${preamble}\n\n${readFileSync(join(PANO, f), "utf8").trim()}`;
+  console.log(`▸ ${f} · ${SIZE} · ${REFS.length} refs`);
+  const t0 = Date.now();
+  const fd = new FormData();
+  fd.append("model", "gpt-image-2");
+  fd.append("prompt", prompt);
+  fd.append("size", SIZE);
+  fd.append("quality", "high");
+  fd.append("n", "1");
+  for (const ref of REFS) {
+    fd.append("image[]", new Blob([readFileSync(ref)], { type: "image/jpeg" }), ref.split("/").pop());
+  }
+  // network hiccups must not kill the batch — retry each beat up to 3×
+  let b64 = null;
+  for (let attempt = 1; attempt <= 3 && !b64; attempt++) {
+    try {
+      const res = await fetch("https://api.openai.com/v1/images/edits", {
+        method: "POST", headers: { Authorization: `Bearer ${apiKey}` }, body: fd,
+      });
+      if (!res.ok) { console.error(`  ✗ OpenAI ${res.status} (attempt ${attempt}): ${(await res.text()).slice(0, 200)}`); continue; }
+      b64 = (await res.json()).data?.[0]?.b64_json ?? null;
+    } catch (err) {
+      console.error(`  ✗ ${err.code ?? err.message} (attempt ${attempt})`);
+    }
+  }
+  if (!b64) { console.error(`✗ ${f} failed after 3 attempts — skipping`); continue; }
+  writeFileSync(png, Buffer.from(b64, "base64"));
+  copyFileSync(png, join(homedir(), "Desktop", `momabobasheep-pano-${basename(png)}`));
+  console.log(`✓ ${((Date.now() - t0) / 1000).toFixed(0)}s → ${png.replace(REPO + "/", "")}`);
+}
+console.log("done");
diff --git a/pop/momboba/pano/01-arrival.txt b/pop/momboba/pano/01-arrival.txt
new file mode 100644
index 000000000..0e8aafde3
--- /dev/null
+++ b/pop/momboba/pano/01-arrival.txt
@@ -0,0 +1,8 @@
+movement 1 — DUSK / ARRIVAL. wide landscape: the felt jeffrey doll
+walks up the felt sidewalk toward a grand modern-art museum entrance
+at the right of frame — a tall minimalist felt facade in warm greys
+with big blank glass doors (felt-framed, no text, no banners), a few
+felt street trees. the long sidewalk and a soft pale dusk-wool sky
+fill the open left of the frame. he carries a tiny felted boba tea
+(pale milk-tea cup, domed top, fat pastel straw, dark wool pearls at
+the bottom) in one hand, mid-stride, hopeful. soft dimming daylight.
diff --git a/pop/momboba/pano/02-boba-sip.txt b/pop/momboba/pano/02-boba-sip.txt
new file mode 100644
index 000000000..60deec171
--- /dev/null
+++ b/pop/momboba/pano/02-boba-sip.txt
@@ -0,0 +1,8 @@
+movement 2 — DROWSE / THE SIP. wide landscape: the felt jeffrey doll
+stands in a tall white felt museum lobby, taking a long happy sip
+from his tiny felted boba — fat pastel straw to his mouth, eyes
+half-lidded with satisfaction, little dark wool tapioca pearls
+visible through the pale cup. he is set left-of-centre; the rest of
+the wide atrium opens out to the right — one big soft hanging felt
+mobile turning in the out-of-focus distance, a tall felt pillar.
+hushed warm lobby light, lots of calm empty wool space.
diff --git a/pop/momboba/pano/03-galleries.txt b/pop/momboba/pano/03-galleries.txt
new file mode 100644
index 000000000..0db79a1cb
--- /dev/null
+++ b/pop/momboba/pano/03-galleries.txt
@@ -0,0 +1,8 @@
+movement 3 — DESCEND / WANDERING THE GALLERIES. wide landscape: the
+felt jeffrey doll strolls through a long felt gallery corridor that
+recedes across the whole width of the frame, boba in hand, looking up
+at framed ABSTRACT FELT artworks on the walls — soft color-field
+rectangles in muted wool (rust, indigo, cream), each in a thin felt
+frame, no text anywhere. his stride is slowing, posture starting to
+soften, eyelids lowering. quiet top-light spilling down the long
+empty corridor.
diff --git a/pop/momboba/pano/04-waterlily-awe.txt b/pop/momboba/pano/04-waterlily-awe.txt
new file mode 100644
index 000000000..b39251aac
--- /dev/null
+++ b/pop/momboba/pano/04-waterlily-awe.txt
@@ -0,0 +1,8 @@
+movement 4 — DEEP / THE POND ROOM. wide landscape: the felt jeffrey
+doll stands tiny at the lower left before a MONUMENTAL felted
+water-lily tapestry that fills the entire wide wall edge to edge —
+soft impressionist blues, greens and lilac wool blended like
+brushstrokes, a sleeping pond in wool. he gazes up in awe, boba
+dangling loosely from one hand, head tilted back. a long backless
+felt gallery bench waits in front of the tapestry, running across the
+width. dim, reverent gallery light.
diff --git a/pop/momboba/pano/05-first-sheep.txt b/pop/momboba/pano/05-first-sheep.txt
new file mode 100644
index 000000000..dcc029b64
--- /dev/null
+++ b/pop/momboba/pano/05-first-sheep.txt
@@ -0,0 +1,9 @@
+movement 5 — DREAM / THE FIRST SHEEP. wide landscape: the felt
+jeffrey doll sits slumped and drowsy on the long felt bench at centre
+before the vast felted water-lily tapestry, head drooping, red felt
+glasses slipping down his little wool nose, the half-finished felted
+boba standing on the bench beside him. a single needle-felted SHEEP —
+wonderfully woolly off-white body, little dark grey felt face and
+slim legs — peeks in from the gallery doorway at the right frame
+edge, looking toward him. the moment reads: the counting is about to
+begin. dim, hushed.
diff --git a/pop/momboba/pano/06-asleep-flock.txt b/pop/momboba/pano/06-asleep-flock.txt
new file mode 100644
index 000000000..2bdd5b824
--- /dev/null
+++ b/pop/momboba/pano/06-asleep-flock.txt
@@ -0,0 +1,9 @@
+movement 6 — STILL / ASLEEP AMONG THE FLOCK (the cover scene, wide).
+the felt jeffrey doll lies fully asleep along the long felt gallery
+bench at centre, one arm folded under his head, red felt glasses
+folded by his hand, finished felted boba standing beside his head.
+scattered across the wide felt floor around the bench, a small flock
+of needle-felted sheep — four or five, some grazing, one turned
+toward him as if just counted — spread out across the width of the
+frame. the monumental felted water-lily tapestry fills the wall
+above. dim, tender, deeply hushed.
diff --git a/pop/momboba/pano/07-the-dream.txt b/pop/momboba/pano/07-the-dream.txt
new file mode 100644
index 000000000..774323ad6
--- /dev/null
+++ b/pop/momboba/pano/07-the-dream.txt
@@ -0,0 +1,12 @@
+movement 7 — VIVID / THE DREAM (the climax, wide). inside the
+painting: the felt jeffrey doll floats curled-up and asleep ON the
+felted water-lily pond itself — resting on a giant soft wool lily pad
+at centre among felted blossoms. seen from ABOVE AND BEHIND, his face
+turned away from the camera and tucked down into the crook of his
+felt arm — only the back and side of his tousled brown wool head and
+his curled sleeping body read, NO front-facing face, no clear
+portrait. blues and greens and lilac wool ripple outward across the
+whole wide frame. above and to the sides, two or three woolly sheep
+drift slowly across a felt sky like clouds. everything soft,
+weightless, luminous, the richest most saturated wool of the whole
+night — deeply asleep, the happiest dream.
diff --git a/pop/momboba/pano/08-morning.txt b/pop/momboba/pano/08-morning.txt
new file mode 100644
index 000000000..5438c0e2d
--- /dev/null
+++ b/pop/momboba/pano/08-morning.txt
@@ -0,0 +1,9 @@
+movement 8 — MORNING. wide landscape: the same long felt gallery
+bench at centre, but now pale dawn light spills in from tall felt
+windows along the left wall, warming the wool from grey to soft
+peach. the felt jeffrey doll is just beginning to stir — still lying
+down but lifting his tousled wool head a little, red felt glasses
+back on, blinking awake. the empty felted boba cup lies tipped on its
+side beside him, a few stray wool pearls spilled. one or two felt
+sheep linger, settling. the water-lily tapestry glows softly in the
+new light. tender, calm, waking.
diff --git a/pop/momboba/pano/09-resolve.txt b/pop/momboba/pano/09-resolve.txt
new file mode 100644
index 000000000..dd1894c3f
--- /dev/null
+++ b/pop/momboba/pano/09-resolve.txt
@@ -0,0 +1,8 @@
+movement 9 — RESOLVE / HOME. wide landscape: a final calm wide view
+of the quiet gallery — the felt jeffrey doll sits up at one end of
+the long felt bench, rested and softly smiling, the empty felted boba
+cup cradled in his lap, his small felt shoulder bag back across his
+body. the felt sheep have curled down to sleep themselves, dotted
+peacefully across the wide felt floor. warm even daylight fills the
+pond room; the monumental water-lily tapestry glows gently behind.
+settled, content, home. the whole scene at rest.
diff --git a/pop/momboba/pano/PREAMBLE.txt b/pop/momboba/pano/PREAMBLE.txt
new file mode 100644
index 000000000..a627ed1dc
--- /dev/null
+++ b/pop/momboba/pano/PREAMBLE.txt
@@ -0,0 +1,22 @@
+a real photograph of a hand-crafted NEEDLE-FELTED WOOL diorama, in
+wide horizontal LANDSCAPE orientation (16:9) — shot like a quiet
+documentation photo of a miniature art piece. visible wool fibers
+everywhere, fuzzy edges, tiny felting imperfections that prove human
+hands. NOT a 3d render, NOT clay, NOT plastic — soft matted wool
+throughout. crisp focus, gentle dim lighting, soft felt shadows.
+
+compose for a 16:9 frame: the felt jeffrey doll set a little off to
+one side, generous quiet negative space across the rest of the wide
+scene so the wool environment can breathe — the kind of calm, roomy
+widescreen framing you can leave on screen for ten minutes.
+
+the recurring character: a needle-felted wool doll of the man in the
+reference photos — recognizably him in doll form, about 30,
+medium-length brown wool hair, tousled, soft red felt glasses. his
+doll wears a tiny felt version of the ACTUAL clothing he is wearing
+in the reference photos — match the real clothing faithfully in felt,
+do not invent new garments.
+
+scene rules: no text, no wordmarks, no wall labels, no readable logos
+anywhere. no screens, no phones. sleepy, hushed, tender, a little
+funny.
diff --git a/pop/momboba/pano/motion-struct.json b/pop/momboba/pano/motion-struct.json
new file mode 100644
index 000000000..01e694fb5
--- /dev/null
+++ b/pop/momboba/pano/motion-struct.json
@@ -0,0 +1,50 @@
+{
+  "totalSec": 52,
+  "sections": [
+    {
+      "name": "arrival",
+      "startSec": 0,
+      "endSec": 5
+    },
+    {
+      "name": "boba-sip",
+      "startSec": 5,
+      "endSec": 10
+    },
+    {
+      "name": "galleries",
+      "startSec": 10,
+      "endSec": 15
+    },
+    {
+      "name": "waterlily-awe",
+      "startSec": 15,
+      "endSec": 20
+    },
+    {
+      "name": "first-sheep",
+      "startSec": 20,
+      "endSec": 25
+    },
+    {
+      "name": "asleep-flock",
+      "startSec": 25,
+      "endSec": 30
+    },
+    {
+      "name": "the-dream",
+      "startSec": 30,
+      "endSec": 42
+    },
+    {
+      "name": "morning",
+      "startSec": 42,
+      "endSec": 47
+    },
+    {
+      "name": "resolve",
+      "startSec": 47,
+      "endSec": 52
+    }
+  ]
+}
\ No newline at end of file
diff --git a/pop/nullabye/README.md b/pop/nullabye/README.md
new file mode 100644
index 000000000..372fb9767
--- /dev/null
+++ b/pop/nullabye/README.md
@@ -0,0 +1,78 @@
+# nullabye
+
+A lullaby with no instruments in it — every sound is carved out of
+cancelled pink noise with EQ automation. Part of the *pixsies* body.
+
+## The technique
+
+Study after Andy Brewer's ["this song has no instruments in it"](https://youtu.be/_Rk-hmIMv6I):
+
+1. Duplicate a pink-noise track and invert the phase of the copy.
+   Summed, they null to **perfect silence**.
+2. Put an EQ on the copy. Anywhere the EQ deviates from flat, the
+   cancellation breaks — what you hear is the *difference signal*.
+3. A narrow peaking bell at a note frequency therefore becomes a
+   breathy pitched voice pulled out of the hiss. Automate 24 bells
+   and you have a 24-voice "noise-sine" polysynth.
+
+Two properties make this more than a parlor trick:
+
+- **Pink noise + constant-Q bells = equal voice energy at any pitch**
+  (pink is equal energy per octave; a constant-Q band covers a constant
+  fraction of an octave). Bass notes and whistle notes come out at the
+  same loudness for free.
+- **High-Q bells ring** (ring time ≈ Q/πf), so the filters supply
+  natural attack/release tails without any amplitude envelope on the
+  audio path — the "instrument" has built-in articulation.
+
+We honor the original's constraint: the renderer allocates from a pool
+of **at most 24 EQ points** and throws if the score ever wants a 25th.
+nullabye uses 15, peaking at 10 sounding simultaneously.
+
+## Run
+
+```bash
+node pop/nullabye/bin/render-nullabye.mjs            # → out/nullabye.mp3
+node pop/nullabye/bin/render-nullabye.mjs --proof    # flat EQ ⇒ bit-exact silence
+```
+
+`--proof` renders with every band forced flat and asserts the output is
+bit-exact digital zero — the cancellation is real, not just quiet.
+
+## nuellaby — the complexity-arch cut
+
+Second cut in the lane (`bin/render-nuellaby.mjs` → `out/nuellaby.mp3`,
+exactly 2:00 — 38 bars at 76 BPM is 120.0 s on the nose): the EQ rack
+**doubles 2 → 4 → 8 → 16 → 32 → 64 → 128, then folds back down
+64 → 32 → 16 → 8 → 4 → 2 and empties** — band count as the
+musical-complexity arc itself. Up in 4-bar chord cycles (2 bars for the
+sparse openers), down in quick 2-bar halvings (arch form; the ×128 bloom
+is the keystone, with a 12-partial harmonic choir + 21-band diatonic halo).
+
+The spectrum is carved into zones, each owned by its own layers:
+sub (pitch-dropping 110→42 Hz kick, bass roots) · bass (drones, tom
+fills, floor pad) · low-mid (chord pads, detuned doubles) · mid (lead
+whistle, harmony, choir) · upper-mid (octave lead, arps, snare-shh) ·
+presence (sparkles, rim clicks, risers) · air (closed/open hats, shaker
+16ths, ticks, veils).
+
+New engine idea: **lanes** — persistent monophonic EQ points that
+consecutive notes reuse (the bell drags to a new frequency, clipping the
+old ring), so each stage's band count is the honest number of points on
+the rack. A per-stage cap audit throws if any stage exceeds its power of
+two; measured arch: `2/2 4/4 8/8 16/16 30/32 51/64 92/128 49 29 15 8 4 2`.
+`--proof` works here too (92 lanes flat ⇒ bit-exact silence).
+
+## The song (nullabye)
+
+76 BPM, 4/4, C major, 24 bars (≈ 1:19). Chord cycle C / Am9 / Fmaj9 / Gadd9.
+
+- **breaths** (bars 0–3) — wide low-Q bells swell in and out of the
+  null so the trick is audible before the song starts.
+- **lullaby-a** (4–11) — Q 28 chord pads, Q 55 whistle lead (±0.12%
+  L/R detune), heartbeat kick (Q 4.5 bell at 54 Hz) from bar 8.
+- **lullaby-b** (12–19) — adds half-note bass roots, 8.2 kHz hat
+  ticks, Q 70 high sparkles on offbeats.
+- **veil-lifts** (20–23) — one wide bell sweeps 250 Hz → 6 kHz letting
+  the raw noise wash through, a last lone whistle, then the EQ goes
+  flat and the song ends in literal silence.
diff --git a/pop/nullabye/bin/render-nuellaby.mjs b/pop/nullabye/bin/render-nuellaby.mjs
new file mode 100644
index 000000000..c7dd7b440
--- /dev/null
+++ b/pop/nullabye/bin/render-nuellaby.mjs
@@ -0,0 +1,534 @@
+#!/usr/bin/env node
+// render-nuellaby.mjs — the accumulation cut: no stages, no doubling.
+// EQ points are added ONE AT A TIME, roughly one per beat, until the whole
+// rack (84 points) is sounding — then they leave again, last-in-first-out,
+// about two per beat. The lead whistle and the bass are the first two
+// points in and the last two out. Boléro logic, carved from cancelled noise.
+//
+// Same trick as render-nullabye.mjs (after Andy Brewer's "this song has no
+// instruments in it", https://youtu.be/_Rk-hmIMv6I): two copies of pink
+// noise, one phase-inverted — perfect silence — and every note is a peaking
+// EQ bell breaking the cancellation. No oscillator anywhere in this file.
+//
+// LANES: a lane is one persistent EQ point on the rack; consecutive notes
+// on a lane reuse it monophonically. Every lane has a fixed ROSTER rank —
+// the order points join in — and a note only sounds if the count curve
+// N(t) has reached its rank. Arpeggios assemble note by note, the twinkle
+// cloud accretes twinkle by twinkle, the choir gains one partial at a time.
+//
+// The spectrum is carved into zones, each owned by a few layers:
+//   SUB        40–90      kick (110→42 Hz pitch-drop bell), bass roots
+//   BASS       90–250     drones (root+fifth)
+//   LOW-MID    250–500    chord pads, detuned doubles
+//   MID        500–1k     lead whistle, harmony 3rd, choir low partials
+//   UPPER-MID  1–2.5k     octave lead, arpeggios, octave pads
+//   PRESENCE   2.5–5k     sparkles, choir highs
+//   AIR        5–13k      hats (closed+open), offbeat shaker, veils
+//
+// Count curve (in beats; 38 bars × 4 = 152 beats = 120.0 s exactly):
+//   0–8     hold 2          the duet establishes
+//   8–92    2 → 84          accumulating: ~1 new point per beat
+//   92–100  hold 84         the bloom crowns
+//   100–140 84 → 2          shedding: ~2 points leave per beat
+//   140–152 2 → empty       lone whistle, downward veil, literal silence
+//
+// A breath swells whenever the count crosses a power of two — a quiet nod
+// to the doubling this cut grew out of.
+//
+// Run:
+//   node pop/nullabye/bin/render-nuellaby.mjs
+//   node pop/nullabye/bin/render-nuellaby.mjs --proof   # flat ⇒ bit-exact silence
+
+import { writeFileSync, mkdirSync, unlinkSync } from "node:fs";
+import { dirname, resolve } from "node:path";
+import { fileURLToPath } from "node:url";
+import { homedir } from "node:os";
+import { spawnSync } from "node:child_process";
+
+const HERE = dirname(fileURLToPath(import.meta.url));
+const SR = 48_000;
+const BLOCK = 64;
+
+const _argi = (k) => { const i = process.argv.indexOf(k); return i >= 0 ? process.argv[i + 1] : null; };
+const PROOF = process.argv.includes("--proof");
+
+const BPM = 76;
+const BEAT = 60 / BPM;
+const BAR = 4 * BEAT;
+const TOTAL_BARS = 38; // 38 × 240/76 s = 120.0 s — exactly 2:00
+const totalSec = PROOF ? 6 : TOTAL_BARS * BAR;
+const ns = Math.ceil(totalSec * SR);
+
+const t = (bar, beat = 0) => bar * BAR + beat * BEAT;
+
+// ── the roster: every EQ point, in the order they join ────────────────
+// foundation first, then the bloom layers interleaved across registers so
+// the texture grows evenly instead of register by register
+const ROSTER = [
+  "lead", "bass", "veil", "breath", "padR", "pad5", "kick", "hat", "pad3",
+  "pad9", "harm", "hatOpen", "leadOct", "spark0", "spark1",
+  "arp0", "droneR", "arp1", "arp2", "droneF",
+  "padOct0", "padOct1", "shaker", "spark2",
+];
+{
+  // IMPORTANT: the EQ chain is SERIAL, so two bells near the same frequency
+  // ADD their dB (pad 19 + double 13 + double 13 = +45 — the old detuned
+  // doubles and root-partial choir both blew up this way). every group here
+  // owns frequencies nothing else sustains.
+  const groups = [
+    Array.from({ length: 16 }, (_, j) => `cloud${j}`),
+    Array.from({ length: 21 }, (_, j) => `halo${j}`),
+    Array.from({ length: 4 }, (_, j) => `choir${j}`),   // spice partials only
+    Array.from({ length: 4 }, (_, j) => `airOct${j}`),
+    Array.from({ length: 3 }, (_, j) => `arpB${j}`),
+    Array.from({ length: 13 }, (_, j) => `cloud2_${j}`),
+  ];
+  let k = 0;
+  while (groups.some((g) => g.length)) {
+    if (groups[k].length) ROSTER.push(groups[k].shift());
+    k = (k + 1) % groups.length;
+  }
+}
+const N_MAX = ROSTER.length; // 84
+const RANK = new Map(ROSTER.map((n, i) => [n, i]));
+
+// ── the count curve: how many points are on the rack at time `time` ───
+function pointsAt(time) {
+  const beat = time / BEAT;
+  if (beat < 8) return 2;
+  if (beat < 92) return 2 + ((beat - 8) / 84) * (N_MAX - 2); // accumulating
+  if (beat < 100) return N_MAX;                              // the bloom
+  if (beat < 140) return N_MAX - ((beat - 100) / 40) * (N_MAX - 2); // shedding
+  return 2;
+}
+
+// ── note table (Hz) ───────────────────────────────────────────────────
+const HZ = {
+  A1: 55.0, C2: 65.41, F2: 87.31, G2: 98.0, A2: 110.0, C3: 130.81,
+  F3: 174.61, G3: 196.0, A3: 220.0, B3: 246.94,
+  C4: 261.63, D4: 293.66, E4: 329.63, F4: 349.23, G4: 392.0, A4: 440.0, B4: 493.88,
+  C5: 523.25, D5: 587.33, E5: 659.26, F5: 698.46, G5: 783.99, A5: 880.0, B5: 987.77,
+  C6: 1046.5, D6: 1174.66, E6: 1318.51, G6: 1567.98, A6: 1760.0,
+  C7: 2093.0, D7: 2349.32, E7: 2637.02,
+};
+
+// ── the key journey: the whole system transposes with the arch ────────
+// rising C → Eb → F into the bloom, falling back home through the
+// shedding. every voice is a frequency, so a key change is one multiply.
+// percussion lanes live in noise zones and stay put.
+const KEYS = [1, 1, 1.1892, 1.1892, 1.3348, 1.3348, 1.1892, 1, 1]; // per 4-bar phrase
+const keyAt = (t0) => KEYS[Math.min(KEYS.length - 1, Math.floor(t0 / (4 * BAR)))];
+const PERC = new Set(["kick", "hat", "hatOpen", "shaker"]);
+
+// ── lanes: persistent monophonic EQ points, gated by roster rank ──────
+const lanes = new Map(); // name → { events: [] }
+
+function note(lane, t0, { freq, freqEnd = null, peakDb, q, atk, hold, rel }) {
+  const rank = RANK.get(lane);
+  if (rank !== undefined && t0 < t(36) && rank >= pointsAt(t0)) return; // not on the rack yet / already left
+  if (!PERC.has(lane)) {
+    const k = keyAt(t0);
+    freq *= k;
+    if (freqEnd) freqEnd *= k;
+  }
+  if (PROOF) peakDb = 0;
+  let L = lanes.get(lane);
+  if (!L) { L = { events: [] }; lanes.set(lane, L); }
+  const prev = L.events[L.events.length - 1];
+  if (prev && prev.end > t0) { prev.cut = t0; prev.end = t0; } // mono: clip the old ring
+  const end = t0 + atk + hold + rel;
+  L.events.push({ t0, freq, freqEnd, peakDb, q, atk, hold, rel, end, cut: null });
+}
+
+function envOf(e, time) {
+  const dt = time - e.t0;
+  if (dt < 0 || dt >= e.atk + e.hold + e.rel) return 0;
+  let v;
+  if (dt < e.atk) v = dt / e.atk;
+  else if (dt < e.atk + e.hold) v = 1;
+  else v = 1 - (dt - e.atk - e.hold) / e.rel;
+  if (e.cut !== null) v *= Math.min(1, Math.max(0, (e.cut - time) / 0.03));
+  return v;
+}
+
+// ── score ─────────────────────────────────────────────────────────────
+// C major, chord cycle C / Am9 / Fmaj9 / Gadd9 on bar % 4 — the harmony
+// never notices the rack growing and shrinking around it.
+const CHORDS = [
+  { tones: [HZ.C4, HZ.E4, HZ.G4], ninth: HZ.D5, root: HZ.C2, arp: [HZ.C5, HZ.E5, HZ.G5] },
+  { tones: [HZ.A3, HZ.C4, HZ.E4], ninth: HZ.B4, root: HZ.A1, arp: [HZ.A4, HZ.C5, HZ.E5] },
+  { tones: [HZ.F3, HZ.A3, HZ.C4], ninth: HZ.G4, root: HZ.F2, arp: [HZ.F4, HZ.A4, HZ.C5] },
+  { tones: [HZ.G3, HZ.B3, HZ.D4], ninth: HZ.A4, root: HZ.G2, arp: [HZ.G4, HZ.B4, HZ.D5] },
+];
+
+// melodies — [freq, startBeat, durBeats] per bar
+const M1 = [
+  [[HZ.E5, 0, 1.5], [HZ.G5, 1.5, 0.5], [HZ.A5, 2, 2]],
+  [[HZ.G5, 0, 1], [HZ.E5, 1, 1], [HZ.D5, 2, 2]],
+  [[HZ.C5, 0, 1.5], [HZ.D5, 1.5, 0.5], [HZ.E5, 2, 1], [HZ.G5, 3, 1]],
+  [[HZ.D5, 0, 3]],
+];
+const M2 = [
+  [[HZ.E5, 0, 1.5], [HZ.G5, 1.5, 0.5], [HZ.A5, 2, 2]],
+  [[HZ.G5, 0, 1], [HZ.A5, 1, 1], [HZ.C6, 2, 2]],
+  [[HZ.A5, 0, 1.5], [HZ.G5, 1.5, 0.5], [HZ.E5, 2, 1], [HZ.C5, 3, 1]],
+  [[HZ.D5, 0, 2], [HZ.E5, 2, 2]],
+];
+const M3 = [ // soaring, for the bloom
+  [[HZ.G5, 0, 4]],
+  [[HZ.A5, 0, 2], [HZ.C6, 2, 2]],
+  [[HZ.A5, 0, 2], [HZ.G5, 2, 2]],
+  [[HZ.E5, 0, 4]],
+];
+// melody runs on its own 4-bar phrase grid — the tune is continuous while
+// the architecture accumulates and sheds around it (bloom phrase = M3)
+const MELODY_TRACK = [M1, M2, M1, M2, M1, M3, M2, M1, M2];
+const THIRD_BELOW = new Map([
+  [HZ.E5, HZ.C5], [HZ.G5, HZ.E5], [HZ.A5, HZ.F5], [HZ.D5, HZ.B4], [HZ.C5, HZ.A4], [HZ.C6, HZ.A5],
+]);
+
+const lead = (lane, bar, beat, freq, beats, db = 26) =>
+  note(lane, t(bar, beat), { freq, peakDb: db, q: 55, atk: 0.06, hold: beats * BEAT - 0.06, rel: 0.45 });
+const pad = (lane, bar, freq, db = 19, q = 28) =>
+  note(lane, t(bar), { freq, peakDb: db, q, atk: 0.8, hold: BAR - 2.0, rel: 1.2 });
+
+// tiny deterministic LCG for the twinkle clouds
+const lcg = (seed) => { let s = seed >>> 0; return () => (s = (s * 1664525 + 1013904223) >>> 0) / 4294967296; };
+
+const HALO = []; // diatonic C-major wash, C4 → B6 registers
+for (const oct of [1, 2, 4])
+  for (const f of [HZ.C4, HZ.D4, HZ.E4, HZ.F4, HZ.G4, HZ.A4, HZ.B4])
+    if (f * oct <= HZ.E7 + 1) HALO.push(f * oct);
+const PENT_HI = [HZ.C6, HZ.D6, HZ.E6, HZ.G6, HZ.A6, HZ.C7, HZ.D7, HZ.E7];
+const PENT_MID = [HZ.C5, HZ.D5, HZ.E5, HZ.G5, HZ.A5];
+
+// every bar emits the FULL arrangement; the roster gate inside note()
+// decides what actually sounds. pattern density follows the local count.
+for (let bar = 0; bar < 36; bar++) {
+  const ch = CHORDS[bar % 4];
+  const mline = MELODY_TRACK[Math.floor(bar / 4)][bar % 4];
+  const n0 = pointsAt(t(bar)); // local density, for pattern choices
+
+  // the founding duet
+  for (const [f, beat, beats] of mline)
+    lead("lead", bar, beat, f, beats, n0 > N_MAX * 0.9 ? 29 : 26);
+  // bass layers different frequencies as it wakes: whole-note root while
+  // sparse, then a root–fifth–root–octave walk through the low end
+  if (n0 < 10) note("bass", t(bar), { freq: ch.root, peakDb: 26, q: 10, atk: 0.03, hold: BAR - 0.6, rel: 0.4 });
+  else [[0, 1], [1, 1.5], [2, 1], [3, 2]].forEach(([beat, mul]) =>
+    note("bass", t(bar, beat), { freq: ch.root * mul, peakDb: mul > 1.6 ? 20 : 26, q: 10, atk: 0.02, hold: 0.9 * BEAT, rel: 0.25 }));
+
+  // the veil — a wide bell barely open across the WHOLE track, swelling
+  // with the count: the noise-whisper never stops, sound runs throughout
+  note("veil", t(bar), { freq: ch.root * 8, peakDb: 3.5 + 4.5 * (n0 / N_MAX), q: 0.55, atk: 0.4, hold: BAR - 0.4, rel: 0.8 });
+
+  // pads
+  pad("padR", bar, ch.tones[0]); pad("pad5", bar, ch.tones[2]);
+  pad("pad3", bar, ch.tones[1]); pad("pad9", bar, ch.ninth, 17);
+  pad("padOct0", bar, ch.tones[0] * 2, 14); pad("padOct1", bar, ch.tones[1] * 2, 14);
+
+  // kick — pitch-dropping bell, the classic shape carved from noise.
+  // +31 dB, not more: the residue scales ~(10^(dB/40)−1)× band noise, and
+  // past ~32 dB its transient owns the peak normalizer.
+  for (const beat of [0, 2])
+    note("kick", t(bar, beat), { freq: 110, freqEnd: 42, peakDb: beat ? 29 : 31, q: 2.2, atk: 0.003, hold: 0.012, rel: 0.18 });
+  if (n0 >= 24) // ghost kick once the groove is thick enough to want it
+    note("kick", t(bar, 3.5), { freq: 90, freqEnd: 46, peakDb: 25, q: 2.5, atk: 0.003, hold: 0.01, rel: 0.12 });
+
+  // hats — backbeat ticks while sparse, driving eighths once the rack fills
+  const hatBeats = n0 >= 14 ? [0.5, 1, 1.5, 2.5, 3] : [1, 3];
+  for (const beat of hatBeats)
+    note("hat", t(bar, beat), { freq: 9000, peakDb: beat % 1 ? 23 : 21, q: 2.5, atk: 0.002, hold: 0.008, rel: 0.05 });
+  note("hatOpen", t(bar, 3.5), { freq: 7600, peakDb: 21, q: 2, atk: 0.002, hold: 0.02, rel: 0.28 });
+
+  // harmony 3rd + octave lead
+  for (const [f, beat, beats] of mline) {
+    const h = THIRD_BELOW.get(f);
+    if (h) lead("harm", bar, beat, h, beats, 20);
+    lead("leadOct", bar, beat, f * 2, beats, 14);
+  }
+
+  // glints
+  const glint = [HZ.E6, HZ.G6, HZ.D6, HZ.E6][bar % 4];
+  note(`spark${bar % 2}`, t(bar, bar % 2 ? 3.5 : 1.5), { freq: glint, peakDb: 18, q: 70, atk: 0.01, hold: 0.06, rel: 0.18 });
+  if (bar % 2) note("spark2", t(bar, 2.75), { freq: HZ.D7, peakDb: 16, q: 70, atk: 0.01, hold: 0.05, rel: 0.16 });
+
+  // arpeggio — assembles note by note as its three lanes join the rack
+  const steps = [0, 1, 2, 1, 0, 1, 2, 1];
+  for (let k = 0; k < 8; k++)
+    note(`arp${k % 3}`, t(bar, k * 0.5), { freq: ch.arp[steps[k]], peakDb: 15, q: 60, atk: 0.015, hold: 0.12, rel: 0.2 });
+
+  // drones + shaker
+  note("droneR", t(bar), { freq: ch.root * 2, peakDb: 15, q: 14, atk: 0.5, hold: BAR - 1.3, rel: 0.8 });
+  note("droneF", t(bar), { freq: ch.root * 3, peakDb: 13, q: 14, atk: 0.5, hold: BAR - 1.3, rel: 0.8 });
+  for (const beat of [0.5, 2.5])
+    note("shaker", t(bar, beat), { freq: 11500, peakDb: 10, q: 4, atk: 0.004, hold: 0.012, rel: 0.05 });
+
+  // twinkle cloud — accretes one lane at a time (offsets sorted per lane;
+  // a lane is monophonic, late-then-early insertion would clip the earlier note)
+  for (let j = 0; j < 16; j++) {
+    const rnd = lcg(j * 7919 + bar * 104729);
+    const f = PENT_HI[(j + bar) % PENT_HI.length];
+    const offs = [Math.floor(rnd() * 8) * 0.5, Math.floor(rnd() * 8) * 0.5].sort((a, z) => a - z);
+    for (const beat of offs)
+      note(`cloud${j}`, t(bar, beat), { freq: f, peakDb: 12, q: 70, atk: 0.012, hold: 0.08, rel: 0.22 });
+  }
+  for (let j = 0; j < 13; j++) {
+    const rnd = lcg(j * 31337 + bar * 49157);
+    const f = PENT_MID[(j + bar) % PENT_MID.length];
+    note(`cloud2_${j}`, t(bar, Math.floor(rnd() * 8) * 0.5), { freq: f, peakDb: 10, q: 60, atk: 0.015, hold: 0.1, rel: 0.25 });
+  }
+
+  // air octave — chord tones two octaves up, a register nothing sustains
+  [...ch.tones.map((f) => f * 4), ch.ninth * 2].forEach((f, i) =>
+    pad(`airOct${i}`, bar, f, 10, 30));
+
+  // second arpeggio — offbeat 16ths an octave up once its lanes join
+  for (let k = 0; k < 8; k++)
+    note(`arpB${k % 3}`, t(bar, 0.25 + k * 0.5), { freq: ch.arp[steps[k]] * 2, peakDb: 12, q: 60, atk: 0.012, hold: 0.08, rel: 0.16 });
+
+  // choir — ONLY the spice partials (7, 11, 13, 14): every other partial
+  // of the root is already owned by the bass / drones / pads, and serial
+  // bells at the same frequency add their dB
+  [7, 11, 13, 14].forEach((p, i) =>
+    note(`choir${i}`, t(bar), { freq: ch.root * p, peakDb: 9 - i * 0.5, q: 35, atk: 0.7, hold: BAR - 1.6, rel: 0.9 }));
+
+  // halo — the diatonic wash
+  HALO.forEach((f, i) =>
+    note(`halo${i}`, t(bar), { freq: f, peakDb: 7.5, q: 25, atk: 0.9, hold: BAR - 2.1, rel: 1.2 }));
+}
+
+// breaths — one swell each time the count crosses a power of two, rising
+// center on the way up, falling on the way down
+{
+  const crossings = [];
+  for (const p2 of [4, 8, 16, 32, 64, N_MAX]) {
+    crossings.push([8 + ((p2 - 2) / (N_MAX - 2)) * 84, p2]); // accumulating
+    if (p2 !== N_MAX) crossings.push([100 + ((N_MAX - p2) / (N_MAX - 2)) * 40, p2]); // shedding
+  }
+  crossings.sort((a, z) => a[0] - z[0]);
+  for (const [beatPos, p2] of crossings)
+    note("breath", beatPos * BEAT, { freq: 380 * Math.pow(1.7, Math.log2(p2) - 3), peakDb: 8.5, q: 0.9, atk: 1.0, hold: 0.2, rel: 1.2 });
+}
+
+// empty — bars 36–37: the rack is bare again. lone whistle on the tonic,
+// a veil sweeping DOWN, then flat EQ — the song ends in literal silence.
+lead("lead", 36, 0, HZ.C5, 6, 24);
+note("breath", t(36, 2), { freq: 4500, freqEnd: 230, peakDb: 8, q: 0.8, atk: 1.6, hold: 0.6, rel: 2.4 });
+
+// ── log the shape ─────────────────────────────────────────────────────
+{
+  const SPARK = "▁▂▃▄▅▆▇█";
+  const line = Array.from({ length: TOTAL_BARS }, (_, b) =>
+    SPARK[Math.min(7, Math.floor((pointsAt(t(b) + BAR / 2) / N_MAX) * 8))]).join("");
+  console.log(`→ nuellaby · ${TOTAL_BARS} bars · C major @ ${BPM} BPM · ${N_MAX} EQ points, ~1 added per beat`);
+  console.log(`   ${line}  (points per bar, ${lanes.size} lanes sounding)`);
+}
+
+// ── render (same dual-noise null engine as nullabye) ──────────────────
+const bands = [...lanes.values()];
+for (const b of bands) b.events.sort((x, y) => x.t0 - y.t0);
+
+// --bake: write the score for the C engine (pop/nullabye/c/nullnoise.c)
+// and exit. composition stays here in JS; the DSP runs in C.
+{
+  const bakeIdx = process.argv.indexOf("--bake");
+  if (bakeIdx >= 0) {
+    const bakePath = process.argv[bakeIdx + 1] || resolve(HERE, "..", "out", "nuellaby.score.txt");
+    const L = [];
+    L.push(`sr ${SR}`, `dur ${totalSec}`, `detune 1.0012 0.9988`, `seed ${0xBEEF} ${0xC0FFEE}`);
+    L.push(`normpeak 0.88`, `fadein 0.004`, `fadeout 1.6`);
+    const RIDE_BARS = 36; // leave the coda's fade alone (matches the JS ride)
+    L.push(`ridewin ${BAR} ${RIDE_BARS}`);
+    for (let b = 0; b < RIDE_BARS; b++)
+      L.push(String(-26.5 + 8 * Math.sqrt(pointsAt(t(b) + BAR / 2) / N_MAX)));
+    for (const band of bands) {
+      L.push(`band ${band.events.length}`);
+      for (const e of band.events)
+        L.push([e.t0, e.freq, e.freqEnd ?? 0, e.peakDb, e.q, e.atk, e.hold, e.rel, e.cut ?? -1].join(" "));
+    }
+    mkdirSync(dirname(bakePath), { recursive: true });
+    writeFileSync(bakePath, L.join("\n") + "\n");
+    console.log(`✓ baked ${bands.length} bands → ${bakePath}`);
+    process.exit(0);
+  }
+}
+
+function makePink(seed) {
+  let s = seed >>> 0;
+  const rnd = () => ((s = (s * 1664525 + 1013904223) >>> 0) / 4294967296) * 2 - 1;
+  let b0 = 0, b1 = 0, b2 = 0, b3 = 0, b4 = 0, b5 = 0, b6 = 0;
+  return () => {
+    const w = rnd();
+    b0 = 0.99886 * b0 + w * 0.0555179;
+    b1 = 0.99332 * b1 + w * 0.0750759;
+    b2 = 0.969 * b2 + w * 0.153852;
+    b3 = 0.8665 * b3 + w * 0.3104856;
+    b4 = 0.55 * b4 + w * 0.5329522;
+    b5 = -0.7616 * b5 - w * 0.016898;
+    const out = (b0 + b1 + b2 + b3 + b4 + b5 + b6 + w * 0.5362) * 0.11;
+    b6 = w * 0.115926;
+    return out;
+  };
+}
+
+const out = [new Float32Array(ns), new Float32Array(ns)];
+const DETUNE = [1.0012, 0.9988];
+
+for (let ch = 0; ch < 2; ch++) {
+  const pink = makePink(ch ? 0xC0FFEE : 0xBEEF);
+  const dry = new Float32Array(BLOCK);
+  const wet = new Float32Array(BLOCK);
+  const st = bands.map(() => ({ z1: 0, z2: 0, cursor: 0, b0: 1, b1: 0, b2: 0, a1: 0, a2: 0 }));
+
+  for (let blockStart = 0; blockStart < ns; blockStart += BLOCK) {
+    const n = Math.min(BLOCK, ns - blockStart);
+    const time = blockStart / SR;
+    for (let i = 0; i < n; i++) wet[i] = dry[i] = pink();
+
+    for (let bi = 0; bi < bands.length; bi++) {
+      const band = bands[bi], s = st[bi];
+      while (s.cursor < band.events.length && time > band.events[s.cursor].end + 0.4) {
+        s.cursor++; s.z1 = 0; s.z2 = 0;
+      }
+      const e = band.events[s.cursor];
+      if (!e || time < e.t0 - 0.05) continue;
+
+      const env = envOf(e, time);
+      const db = e.peakDb * env;
+      const ringing = Math.abs(s.z1) + Math.abs(s.z2) > 1e-9;
+      if (db <= 0.01 && !ringing) continue;
+
+      let freq = e.freq;
+      if (e.freqEnd) {
+        const p = Math.min(1, Math.max(0, (time - e.t0) / (e.end - e.t0)));
+        freq = e.freq * Math.pow(e.freqEnd / e.freq, p);
+      }
+      const A = Math.pow(10, db / 40);
+      const w0 = (2 * Math.PI * Math.min(freq * DETUNE[ch], SR * 0.45)) / SR;
+      const alpha = Math.sin(w0) / (2 * e.q);
+      const cosw = Math.cos(w0);
+      const a0 = 1 + alpha / A;
+      s.b0 = (1 + alpha * A) / a0;
+      s.b1 = (-2 * cosw) / a0;
+      s.b2 = (1 - alpha * A) / a0;
+      s.a1 = (-2 * cosw) / a0;
+      s.a2 = (1 - alpha / A) / a0;
+      let { z1, z2 } = s;
+      for (let i = 0; i < n; i++) {
+        const x = wet[i];
+        const y = s.b0 * x + z1;
+        z1 = s.b1 * x - s.a1 * y + z2;
+        z2 = s.b2 * x - s.a2 * y;
+        wet[i] = y;
+      }
+      s.z1 = z1; s.z2 = z2;
+    }
+
+    const o = out[ch];
+    for (let i = 0; i < n; i++) o[blockStart + i] = wet[i] - dry[i];
+  }
+}
+
+if (PROOF) {
+  let peak = 0;
+  for (const ch of out) for (let i = 0; i < ns; i++) peak = Math.max(peak, Math.abs(ch[i]));
+  console.log(peak === 0
+    ? `✓ proof: all ${bands.length} bands flat → output is bit-exact silence (peak = 0)`
+    : `✗ proof failed: peak = ${peak}`);
+  process.exit(peak === 0 ? 0 : 1);
+}
+
+// ── loudness ride: even out the accumulation ──────────────────────────
+// raw loudness tracks band count (~43 dB between the duet and the bloom);
+// measure per-bar RMS and ride it onto a gentle target that follows the
+// count curve — present at 2 points, crowning (not crushing) at 84.
+{
+  const LAST_TRIM_BAR = 36; // leave the coda's fade alone
+  const gains = [];
+  for (let b = 0; b < LAST_TRIM_BAR; b++) {
+    const a = Math.floor(t(b) * SR), z = Math.min(ns, Math.floor(t(b + 1) * SR));
+    let sum = 0;
+    for (const chB of out) for (let j = a; j < z; j++) sum += chB[j] * chB[j];
+    const rms = 10 * Math.log10(sum / Math.max(1, (z - a) * 2) + 1e-20);
+    // gentle: −26.5 at the duet → −18.5 at the bloom. with the veil bed
+    // running throughout, the floor never drops out
+    const target = -26.5 + 8 * Math.sqrt(pointsAt(t(b) + BAR / 2) / N_MAX);
+    gains.push(Math.max(-60, Math.min(30, target - rms)));
+  }
+  const sm = gains.map((_, i) => { // 3-bar smoothing against per-bar pumping
+    const lo = Math.max(0, i - 1), hi = Math.min(gains.length - 1, i + 1);
+    let s = 0; for (let k = lo; k <= hi; k++) s += gains[k];
+    return s / (hi - lo + 1);
+  });
+  console.log(`   ride: per-bar trims ${Math.min(...sm).toFixed(1)}…${Math.max(...sm).toFixed(1)} dB onto the count curve`);
+  if (process.argv.includes("--ride-debug"))
+    gains.forEach((gn, b) => console.log(`   bar ${String(b).padStart(2)}: trim ${gn.toFixed(1)} dB`));
+  for (let i = 0; i < ns; i++) { // linear interp between bar centers
+    const pos = i / SR / BAR - 0.5;
+    const b0 = Math.max(0, Math.min(sm.length - 1, Math.floor(pos)));
+    const b1 = Math.min(sm.length - 1, b0 + 1);
+    const f = Math.max(0, Math.min(1, pos - b0));
+    const gdb = sm[b0] * (1 - f) + sm[b1] * f;
+    const lin = Math.pow(10, gdb / 20);
+    out[0][i] *= lin; out[1][i] *= lin;
+  }
+}
+
+// ── normalize + edge fades ────────────────────────────────────────────
+let peak = 0;
+for (const ch of out) for (let i = 0; i < ns; i++) peak = Math.max(peak, Math.abs(ch[i]));
+const g = peak > 0 ? 0.88 / peak : 1;
+const fadeIn = Math.floor(0.004 * SR), fadeOut = Math.floor(1.6 * SR);
+for (const ch of out) {
+  for (let i = 0; i < ns; i++) ch[i] *= g;
+  for (let i = 0; i < fadeIn; i++) ch[i] *= i / fadeIn;
+  for (let i = 0; i < fadeOut; i++) ch[ns - 1 - i] *= i / fadeOut;
+}
+
+// ── write out ─────────────────────────────────────────────────────────
+function expandHome(p) {
+  if (!p) return p;
+  if (p === "~") return homedir();
+  if (p.startsWith("~/")) return resolve(homedir(), p.slice(2));
+  return p;
+}
+const outPath = expandHome(_argi("--out")) || resolve(HERE, "..", "out", "nuellaby.mp3");
+mkdirSync(dirname(outPath), { recursive: true });
+const rawPath = `${outPath}.f32.raw`;
+const buf = Buffer.alloc(ns * 2 * 4);
+for (let i = 0; i < ns; i++) {
+  buf.writeFloatLE(out[0][i], i * 8);
+  buf.writeFloatLE(out[1][i], i * 8 + 4);
+}
+writeFileSync(rawPath, buf);
+
+const MASTER = [
+  "highpass=f=30",
+  "acompressor=threshold=-22dB:ratio=2.2:attack=25:release=220:makeup=2.0:knee=8",
+  "treble=g=0.8:f=9000",
+  "alimiter=limit=0.96:attack=5:release=80",
+].join(",");
+const ff = spawnSync("ffmpeg", ["-hide_banner", "-y", "-loglevel", "error",
+  "-f", "f32le", "-ar", String(SR), "-ac", "2", "-i", rawPath,
+  "-af", MASTER, "-c:a", "libmp3lame", "-q:a", "2", outPath], { stdio: "inherit" });
+if (!process.argv.includes("--keep-raw")) { try { unlinkSync(rawPath); } catch {} }
+if (ff.status !== 0) { console.error("✗ ffmpeg failed"); process.exit(1); }
+console.log(`✓ ${outPath} (pop-mastered · ${(ns / SR).toFixed(1)} s)`);
+
+// ── struct.json ───────────────────────────────────────────────────────
+{
+  const struct = {
+    _comment: "Section map for nuellaby (the accumulation cut). 4/4, 76 BPM, C major. 84 EQ points added ~1/beat, bloom, then shed ~2/beat. Landmarks derived from the count curve.",
+    meter: 4, bpm: BPM, scale: "major", rootMidi: 60,
+    totalSec: +(ns / SR).toFixed(6), prerollSec: 0,
+    sections: [
+      { name: "accumulating", startSec: 0, endSec: +(92 * BEAT).toFixed(6) },
+      { name: "bloom", startSec: +(92 * BEAT).toFixed(6), endSec: +(100 * BEAT).toFixed(6) },
+      { name: "shedding", startSec: +(100 * BEAT).toFixed(6), endSec: +t(36).toFixed(6) },
+      { name: "empty", startSec: +t(36).toFixed(6), endSec: +(ns / SR).toFixed(6) },
+    ],
+  };
+  writeFileSync(resolve(HERE, "..", "out", "nuellaby.struct.json"),
+    JSON.stringify(struct, null, 2) + "\n");
+}
diff --git a/pop/nullabye/bin/render-nullabye.mjs b/pop/nullabye/bin/render-nullabye.mjs
new file mode 100644
index 000000000..1863d68e5
--- /dev/null
+++ b/pop/nullabye/bin/render-nullabye.mjs
@@ -0,0 +1,334 @@
+#!/usr/bin/env node
+// render-nullabye.mjs — a lullaby carved entirely out of cancelled noise.
+//
+// Technique study after Andy Brewer's "this song has no instruments in it"
+// (https://youtu.be/_Rk-hmIMv6I): take pink noise, duplicate it, invert the
+// phase of the copy — the sum is perfect silence. Put an EQ on the copy and
+// every deviation from flat breaks the cancellation; what you hear is the
+// *difference*. A narrow peaking bell at a note frequency becomes a breathy,
+// pitched voice pulled out of the hiss. The whole song is EQ automation —
+// there is no oscillator anywhere in this file.
+//
+// Honoring the original constraint: at most 24 EQ points (bands) exist.
+// A small allocator hands notes to free bands and refuses a 25th voice.
+// Pink noise + constant-Q bells = equal energy per voice at any pitch,
+// which is the quiet genius of the source video.
+//
+// Voices (all the same instrument — a bell in the veil):
+//   pads     — Q 28 chord tones, slow swells          (the choir)
+//   lead     — Q 55 whistle melody, ±0.12% L/R detune (the whistler)
+//   bass     — Q 10 low roots, half-note pulse        (the heartbeat root)
+//   kick     — Q 4.5 @ 54 Hz, 130 ms                  (the heartbeat)
+//   hat      — Q 5 @ 8.2 kHz ticks                    (the eyelash)
+//   sparkle  — Q 70 high offbeat glints               (the mobile overhead)
+//   veil     — Q 0.8 sweep, the one moment the raw noise shows through
+//
+// Run:
+//   node pop/nullabye/bin/render-nullabye.mjs
+//   node pop/nullabye/bin/render-nullabye.mjs --out ~/nullabye.mp3
+//   node pop/nullabye/bin/render-nullabye.mjs --proof   # flat EQ ⇒ bit-exact silence
+//
+// 76 BPM 4/4 → beat ≈ 0.789 s, bar ≈ 3.158 s. 24 bars ≈ 76 s + tail.
+
+import { writeFileSync, mkdirSync, unlinkSync } from "node:fs";
+import { dirname, resolve } from "node:path";
+import { fileURLToPath } from "node:url";
+import { homedir } from "node:os";
+import { spawnSync } from "node:child_process";
+
+const HERE = dirname(fileURLToPath(import.meta.url));
+const SR = 48_000;
+const BLOCK = 64; // coefficient-update granularity (~1.3 ms)
+
+const _argi = (k) => { const i = process.argv.indexOf(k); return i >= 0 ? process.argv[i + 1] : null; };
+const PROOF = process.argv.includes("--proof");
+
+const BPM = 76;
+const BEAT = 60 / BPM;
+const BAR = 4 * BEAT;
+const TOTAL_BARS = 24;
+const totalSec = PROOF ? 6 : TOTAL_BARS * BAR + 3.0; // + tail for the last ring
+const ns = Math.ceil(totalSec * SR);
+
+const t = (bar, beat = 0) => bar * BAR + beat * BEAT;
+
+// ── note table (Hz — the EQ thinks in frequency, so we do too) ────────
+const HZ = {
+  F1: 43.65, A1: 55.0, C2: 65.41, F2: 87.31, G2: 98.0, A2: 110.0,
+  F3: 174.61, G3: 196.0, A3: 220.0, B3: 246.94,
+  C4: 261.63, D4: 293.66, E4: 329.63, G4: 392.0, A4: 440.0, B4: 493.88,
+  C5: 523.25, D5: 587.33, E5: 659.26, G5: 783.99, A5: 880.0,
+  C6: 1046.5, D6: 1174.66, E6: 1318.51, G6: 1567.98,
+};
+
+// ── the 24-band pool ──────────────────────────────────────────────────
+const MAX_BANDS = 24;
+const GUARD = 0.15; // s between notes on the same band (let the ring drain)
+const bands = []; // { freeAt, events: [...] }
+let peakConcurrent = 0;
+
+function note(t0, { freq, freqEnd = null, peakDb, q, atk, hold, rel }) {
+  if (PROOF) peakDb = 0; // flat EQ — the silence proof
+  const end = t0 + atk + hold + rel;
+  let band = null;
+  for (const b of bands) if (b.freeAt <= t0) { band = b; break; }
+  if (!band) {
+    if (bands.length >= MAX_BANDS)
+      throw new Error(`25th EQ point requested at t=${t0.toFixed(2)}s — the video only had 24, so do we`);
+    band = { freeAt: 0, events: [] };
+    bands.push(band);
+  }
+  band.freeAt = end + GUARD;
+  band.events.push({ t0, freq, freqEnd, peakDb, q, atk, hold, rel, end });
+  const live = bands.filter((b) => b.events.some((e) => e.t0 <= t0 && t0 < e.end)).length;
+  if (live > peakConcurrent) peakConcurrent = live;
+}
+
+// envelope in dB-space: linear attack, hold, linear release (sounds exp)
+function envOf(e, time) {
+  const dt = time - e.t0;
+  if (dt < 0 || dt >= e.atk + e.hold + e.rel) return 0;
+  if (dt < e.atk) return dt / e.atk;
+  if (dt < e.atk + e.hold) return 1;
+  return 1 - (dt - e.atk - e.hold) / e.rel;
+}
+
+// ── score ─────────────────────────────────────────────────────────────
+// C major lullaby. Chord cycle C / Am / F / G, one bar each.
+const CHORDS = [
+  [HZ.C4, HZ.E4, HZ.G4, HZ.D5],  // Cmaj9
+  [HZ.A3, HZ.C4, HZ.E4, HZ.B4],  // Am9
+  [HZ.F3, HZ.A3, HZ.C4, HZ.G4],  // Fmaj9
+  [HZ.G3, HZ.B3, HZ.D4, HZ.A4],  // Gadd9
+];
+const BASS_ROOTS = [HZ.C2, HZ.A1, HZ.F2, HZ.G2];
+
+const pad = (bar, freq, db = 20) =>
+  note(t(bar), { freq, peakDb: db, q: 28, atk: 0.8, hold: BAR - 2.0, rel: 1.2 });
+const lead = (bar, beat, freq, beats, db = 26) =>
+  note(t(bar, beat), { freq, peakDb: db, q: 55, atk: 0.06, hold: beats * BEAT - 0.06, rel: 0.35 });
+const bass = (bar, beat, freq) =>
+  note(t(bar, beat), { freq, peakDb: 26, q: 10, atk: 0.02, hold: 0.9 * BEAT, rel: 0.25 });
+const kick = (bar, beat, db = 30) =>
+  note(t(bar, beat), { freq: 54, peakDb: db, q: 4.5, atk: 0.004, hold: 0.02, rel: 0.13 });
+const hat = (bar, beat, db = 15) =>
+  note(t(bar, beat), { freq: 8200, peakDb: db, q: 5, atk: 0.003, hold: 0.01, rel: 0.07 });
+const sparkle = (bar, beat, freq, db = 20) =>
+  note(t(bar, beat), { freq, peakDb: db, q: 70, atk: 0.01, hold: 0.06, rel: 0.18 });
+
+// intro — bars 0–3: the veil breathes. wide bells swell in and out of the
+// null so the listener hears the trick before they hear the song.
+const BREATHS = [[0, 420], [1, 640], [2, 960], [3, 1440]];
+for (const [bar, freq] of BREATHS)
+  note(t(bar, 0.5), { freq, peakDb: 8.5, q: 0.9, atk: 1.1, hold: 0.3, rel: 1.3 });
+for (const f of CHORDS[0]) pad(3, f, 14); // first chord ghosts in early
+
+// pads — bars 4–20, one chord per bar
+for (let bar = 4; bar <= 20; bar++)
+  for (const f of CHORDS[bar % 4]) pad(bar, f, bar === 20 ? 17 : 20);
+
+// melody — A section (bars 4–11)
+const PHRASE_A = [
+  [[HZ.E5, 0, 1.5], [HZ.G5, 1.5, 0.5], [HZ.A5, 2, 2]],
+  [[HZ.G5, 0, 1], [HZ.E5, 1, 1], [HZ.D5, 2, 2]],
+  [[HZ.C5, 0, 1.5], [HZ.D5, 1.5, 0.5], [HZ.E5, 2, 1], [HZ.G5, 3, 1]],
+  [[HZ.D5, 0, 3]],
+  [[HZ.E5, 0, 1.5], [HZ.G5, 1.5, 0.5], [HZ.A5, 2, 2]],
+  [[HZ.G5, 0, 1], [HZ.A5, 1, 1], [HZ.C6, 2, 2]],
+  [[HZ.A5, 0, 1.5], [HZ.G5, 1.5, 0.5], [HZ.E5, 2, 1], [HZ.C5, 3, 1]],
+  [[HZ.D5, 0, 4]],
+];
+PHRASE_A.forEach((barNotes, i) =>
+  barNotes.forEach(([f, b, d]) => lead(4 + i, b, f, d)));
+
+// melody — B section (bars 12–19): restate, then close upward
+const PHRASE_B = [
+  ...PHRASE_A.slice(0, 4),
+  [[HZ.E5, 0, 1.5], [HZ.G5, 1.5, 0.5], [HZ.A5, 2, 2]],
+  [[HZ.C6, 0, 2], [HZ.A5, 2, 2]],
+  [[HZ.G5, 0, 1.5], [HZ.E5, 1.5, 0.5], [HZ.D5, 2, 1], [HZ.C5, 3, 1]],
+  [[HZ.D5, 0, 2], [HZ.E5, 2, 2]], // hangs on E into the final C — home
+];
+PHRASE_B.forEach((barNotes, i) =>
+  barNotes.forEach(([f, b, d]) => lead(12 + i, b, f, d)));
+
+// heartbeat — soft kick from bar 8, full from 12
+for (let bar = 8; bar <= 19; bar++) {
+  kick(bar, 0, bar < 12 ? 26 : 30);
+  kick(bar, 2, bar < 12 ? 24 : 28);
+}
+
+// bass + hats + sparkles — B section only
+for (let bar = 12; bar <= 19; bar++) {
+  const root = BASS_ROOTS[bar % 4];
+  bass(bar, 0, root);
+  bass(bar, 2, root);
+  hat(bar, 1.5);
+  hat(bar, 3.5, 13);
+  const glint = [HZ.E6, HZ.G6, HZ.D6, HZ.E6][bar % 4];
+  sparkle(bar, bar % 2 ? 3.5 : 1.5, glint);
+}
+
+// outro — bars 20–23: the veil lifts (one wide sweeping bell lets the raw
+// noise wash through), a last lone whistle, then the EQ goes flat and the
+// nulled noise swallows everything. the song ends in *literal* silence.
+note(t(20, 2), { freq: 250, freqEnd: 6000, peakDb: 9, q: 0.8, atk: 2.2, hold: 0.8, rel: 2.6 });
+lead(21, 0, HZ.E5, 2, 21);
+lead(22, 0, HZ.C5, 2, 17);
+
+// ── render: two pink-noise tracks, one EQ'd + inverted, summed ────────
+// per channel: residue = chain(noise) − noise. flat chain ⇒ exact zero.
+for (const b of bands) b.events.sort((x, y) => x.t0 - y.t0);
+console.log(`→ nullabye · ${TOTAL_BARS} bars · C major @ ${BPM} BPM · ${bands.length}/${MAX_BANDS} EQ points · peak ${peakConcurrent} voices sounding`);
+
+// deterministic noise (LCG → Paul Kellett pink filter)
+function makePink(seed) {
+  let s = seed >>> 0;
+  const rnd = () => ((s = (s * 1664525 + 1013904223) >>> 0) / 4294967296) * 2 - 1;
+  let b0 = 0, b1 = 0, b2 = 0, b3 = 0, b4 = 0, b5 = 0, b6 = 0;
+  return () => {
+    const w = rnd();
+    b0 = 0.99886 * b0 + w * 0.0555179;
+    b1 = 0.99332 * b1 + w * 0.0750759;
+    b2 = 0.969 * b2 + w * 0.153852;
+    b3 = 0.8665 * b3 + w * 0.3104856;
+    b4 = 0.55 * b4 + w * 0.5329522;
+    b5 = -0.7616 * b5 - w * 0.016898;
+    const out = (b0 + b1 + b2 + b3 + b4 + b5 + b6 + w * 0.5362) * 0.11;
+    b6 = w * 0.115926;
+    return out;
+  };
+}
+
+const out = [new Float32Array(ns), new Float32Array(ns)];
+const DETUNE = [1.0012, 0.9988]; // ±0.12% L/R — the shimmer in the veil
+
+for (let ch = 0; ch < 2; ch++) {
+  const pink = makePink(ch ? 0xC0FFEE : 0xBEEF);
+  const dry = new Float32Array(BLOCK);
+  const wet = new Float32Array(BLOCK);
+  // biquad state + per-band event cursor
+  const st = bands.map(() => ({ z1: 0, z2: 0, cursor: 0, b0: 1, b1: 0, b2: 0, a1: 0, a2: 0 }));
+
+  for (let blockStart = 0; blockStart < ns; blockStart += BLOCK) {
+    const n = Math.min(BLOCK, ns - blockStart);
+    const time = blockStart / SR;
+    for (let i = 0; i < n; i++) wet[i] = dry[i] = pink();
+
+    for (let bi = 0; bi < bands.length; bi++) {
+      const band = bands[bi], s = st[bi];
+      // advance past finished events (keep 0.4 s to drain the ring)
+      while (s.cursor < band.events.length && time > band.events[s.cursor].end + 0.4) {
+        s.cursor++; s.z1 = 0; s.z2 = 0;
+      }
+      const e = band.events[s.cursor];
+      if (!e || time < e.t0 - 0.05) continue; // idle band: identity, skip
+
+      const env = envOf(e, time);
+      const db = e.peakDb * env;
+      const ringing = Math.abs(s.z1) + Math.abs(s.z2) > 1e-9;
+      if (db <= 0.01 && !ringing) continue;
+
+      let freq = e.freq;
+      if (e.freqEnd) { // exp glide across the event
+        const p = Math.min(1, Math.max(0, (time - e.t0) / (e.end - e.t0)));
+        freq = e.freq * Math.pow(e.freqEnd / e.freq, p);
+      }
+      // RBJ peaking EQ
+      const A = Math.pow(10, db / 40);
+      const w0 = (2 * Math.PI * Math.min(freq * DETUNE[ch], SR * 0.45)) / SR;
+      const alpha = Math.sin(w0) / (2 * e.q);
+      const cosw = Math.cos(w0);
+      const a0 = 1 + alpha / A;
+      s.b0 = (1 + alpha * A) / a0;
+      s.b1 = (-2 * cosw) / a0;
+      s.b2 = (1 - alpha * A) / a0;
+      s.a1 = (-2 * cosw) / a0;
+      s.a2 = (1 - alpha / A) / a0;
+      // transposed direct form II over the block
+      let { z1, z2 } = s;
+      for (let i = 0; i < n; i++) {
+        const x = wet[i];
+        const y = s.b0 * x + z1;
+        z1 = s.b1 * x - s.a1 * y + z2;
+        z2 = s.b2 * x - s.a2 * y;
+        wet[i] = y;
+      }
+      s.z1 = z1; s.z2 = z2;
+    }
+
+    // the trick itself: EQ'd copy minus the original. flat ⇒ silence.
+    const o = out[ch];
+    for (let i = 0; i < n; i++) o[blockStart + i] = wet[i] - dry[i];
+  }
+}
+
+// ── proof mode: flat EQ must null to bit-exact digital zero ───────────
+if (PROOF) {
+  let peak = 0;
+  for (const ch of out) for (let i = 0; i < ns; i++) peak = Math.max(peak, Math.abs(ch[i]));
+  console.log(peak === 0
+    ? "✓ proof: all 24 bands flat → output is bit-exact silence (peak = 0)"
+    : `✗ proof failed: peak = ${peak}`);
+  process.exit(peak === 0 ? 0 : 1);
+}
+
+// ── normalize + edge fades ────────────────────────────────────────────
+let peak = 0;
+for (const ch of out) for (let i = 0; i < ns; i++) peak = Math.max(peak, Math.abs(ch[i]));
+const g = peak > 0 ? 0.88 / peak : 1;
+const fadeIn = Math.floor(0.004 * SR), fadeOut = Math.floor(1.6 * SR);
+for (const ch of out) {
+  for (let i = 0; i < ns; i++) ch[i] *= g;
+  for (let i = 0; i < fadeIn; i++) ch[i] *= i / fadeIn;
+  for (let i = 0; i < fadeOut; i++) ch[ns - 1 - i] *= i / fadeOut;
+}
+
+// ── write out ─────────────────────────────────────────────────────────
+function expandHome(p) {
+  if (!p) return p;
+  if (p === "~") return homedir();
+  if (p.startsWith("~/")) return resolve(homedir(), p.slice(2));
+  return p;
+}
+const outPath = expandHome(_argi("--out")) || resolve(HERE, "..", "out", "nullabye.mp3");
+mkdirSync(dirname(outPath), { recursive: true });
+const rawPath = `${outPath}.f32.raw`;
+const buf = Buffer.alloc(ns * 2 * 4);
+for (let i = 0; i < ns; i++) {
+  buf.writeFloatLE(out[0][i], i * 8);
+  buf.writeFloatLE(out[1][i], i * 8 + 4);
+}
+writeFileSync(rawPath, buf);
+
+// master chain — gentle: the material is all noise, so easy on the air band
+// and a soft knee so the breaths keep breathing.
+const MASTER = [
+  "highpass=f=30",
+  "acompressor=threshold=-22dB:ratio=2.2:attack=25:release=220:makeup=2.0:knee=8",
+  "treble=g=0.8:f=9000",
+  "alimiter=limit=0.96:attack=5:release=80",
+].join(",");
+const ff = spawnSync("ffmpeg", ["-hide_banner", "-y", "-loglevel", "error",
+  "-f", "f32le", "-ar", String(SR), "-ac", "2", "-i", rawPath,
+  "-af", MASTER, "-c:a", "libmp3lame", "-q:a", "2", outPath], { stdio: "inherit" });
+try { unlinkSync(rawPath); } catch {}
+if (ff.status !== 0) { console.error("✗ ffmpeg failed"); process.exit(1); }
+console.log(`✓ ${outPath} (pop-mastered · ${(ns / SR).toFixed(1)} s)`);
+
+// ── struct.json — section map for any future visualizer ───────────────
+{
+  const struct = {
+    _comment: "Section map for nullabye (the cancelled-noise lullaby). 4/4, 76 BPM → bar ≈ 3.158 s. C major. Derived from render-nullabye.mjs.",
+    meter: 4, bpm: BPM, scale: "major", rootMidi: 60,
+    totalSec: +(ns / SR).toFixed(6), prerollSec: 0,
+    sections: [
+      { name: "breaths", startSec: 0, endSec: +t(4).toFixed(6) },
+      { name: "lullaby-a", startSec: +t(4).toFixed(6), endSec: +t(12).toFixed(6) },
+      { name: "lullaby-b", startSec: +t(12).toFixed(6), endSec: +t(20).toFixed(6) },
+      { name: "veil-lifts", startSec: +t(20).toFixed(6), endSec: +(ns / SR).toFixed(6) },
+    ],
+  };
+  writeFileSync(resolve(HERE, "..", "out", "nullabye.struct.json"),
+    JSON.stringify(struct, null, 2) + "\n");
+}
diff --git a/pop/nullabye/c/build.sh b/pop/nullabye/c/build.sh
new file mode 100755
index 000000000..44a961620
--- /dev/null
+++ b/pop/nullabye/c/build.sh
@@ -0,0 +1,10 @@
+#!/usr/bin/env bash
+# build.sh — compile nullnoise.c. No -ffast-math so the numerics stay
+# stable across machines and match the JS reference (render-nuellaby.mjs).
+set -euo pipefail
+HERE="$(cd -- "$(dirname -- "$0")" && pwd)"
+cc -O3 -std=c11 -Wall -Wextra \
+   -o "$HERE/nullnoise" \
+   "$HERE/nullnoise.c" \
+   -lm
+echo "→ $HERE/nullnoise"
diff --git a/pop/nullabye/c/compare.mjs b/pop/nullabye/c/compare.mjs
new file mode 100644
index 000000000..75f38415a
--- /dev/null
+++ b/pop/nullabye/c/compare.mjs
@@ -0,0 +1,51 @@
+#!/usr/bin/env node
+// compare.mjs — A/B the C engine (nullnoise) against the JS reference
+// (render-nuellaby.mjs) on the same score. Both render pre-master f32;
+// we diff per-sample. Expected: near bit-exact (libm-ulp drift only,
+// well under -100 dB RMS).
+//
+// Usage:  node pop/nullabye/c/compare.mjs
+
+import { readFileSync, mkdirSync } from "node:fs";
+import { spawnSync } from "node:child_process";
+import { dirname, resolve } from "node:path";
+import { fileURLToPath } from "node:url";
+
+const HERE = dirname(fileURLToPath(import.meta.url));
+const LANE = resolve(HERE, "..");
+const OUT = resolve(LANE, "out");
+mkdirSync(OUT, { recursive: true });
+
+const run = (label, cmd, args) => {
+  console.log(`[compare] ${label}`);
+  const r = spawnSync(cmd, args, { stdio: "inherit" });
+  if (r.status !== 0) { console.error(`✗ ${label} failed`); process.exit(1); }
+};
+
+// 1 — JS reference render, keeping the pre-master raw
+run("JS render", "node", [resolve(LANE, "bin/render-nuellaby.mjs"), "--keep-raw"]);
+const jsRaw = resolve(OUT, "nuellaby.mp3.f32.raw");
+
+// 2 — bake the score + C engine render
+run("bake", "node", [resolve(LANE, "bin/render-nuellaby.mjs"), "--bake", resolve(OUT, "nuellaby.score.txt")]);
+run("C render", "node", [resolve(HERE, "run-c.mjs"), resolve(OUT, "nuellaby.score.txt"), "--raw", resolve(OUT, "nuellaby-c.f32.raw")]);
+const cRaw = resolve(OUT, "nuellaby-c.f32.raw");
+
+// 3 — diff
+const a = new Float32Array(readFileSync(jsRaw).buffer.slice(0));
+const b = new Float32Array(readFileSync(cRaw).buffer.slice(0));
+const n = Math.min(a.length, b.length);
+if (a.length !== b.length) console.log(`  length mismatch: js ${a.length} vs c ${b.length} samples`);
+let sumSq = 0, sumRefSq = 0, peakDiff = 0, peakAt = 0;
+for (let i = 0; i < n; i++) {
+  const d = a[i] - b[i];
+  sumSq += d * d;
+  sumRefSq += a[i] * a[i];
+  if (Math.abs(d) > peakDiff) { peakDiff = Math.abs(d); peakAt = i; }
+}
+const rmsDiffDb = 10 * Math.log10(sumSq / n + 1e-30);
+const refDb = 10 * Math.log10(sumRefSq / n + 1e-30);
+console.log(`  ref level   : ${refDb.toFixed(1)} dBFS RMS`);
+console.log(`  diff        : ${rmsDiffDb.toFixed(1)} dBFS RMS (${(rmsDiffDb - refDb).toFixed(1)} dB below ref)`);
+console.log(`  peak diff   : ${peakDiff.toExponential(2)} at sample ${peakAt} (t=${(peakAt / 2 / 48000).toFixed(2)}s)`);
+console.log(rmsDiffDb - refDb < -60 ? "✓ engines match (diff > 60 dB down)" : "✗ engines DIVERGE — investigate");
diff --git a/pop/nullabye/c/nullnoise b/pop/nullabye/c/nullnoise
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diff --git a/pop/nullabye/c/nullnoise.c b/pop/nullabye/c/nullnoise.c
new file mode 100644
index 000000000..5cfcc00c4
--- /dev/null
+++ b/pop/nullabye/c/nullnoise.c
@@ -0,0 +1,305 @@
+// nullnoise.c — the cancelled-noise engine, in C. Generic: renders any
+// baked score (see --bake in the lane renderers), so nuellaby, teknull
+// and any future carved-noise track share this one binary.
+//
+// THE LAW OF THIS LANE: two copies of pink noise, one phase-inverted —
+// perfect silence — and every sound is a peaking EQ bell breaking the
+// cancellation. residue = chain(noise) − noise. There is no oscillator
+// anywhere in this file; a flat chain renders bit-exact digital zero
+// (verify with --proof).
+//
+// Numerics mirror the JS reference (render-nuellaby.mjs) op for op:
+// float (f32) wet/dry/out buffers, double biquad state and coefficients,
+// the same LCG → Paul Kellett pink filter, the same RBJ peaking bells,
+// per-64-sample-block coefficient updates, the same per-window loudness
+// ride. Differences vs JS come only from libm ulps.
+//
+// Build:  ./build.sh
+// Run:    ./nullnoise <score.txt> --raw out.f32     (f32le stereo 48k)
+//         ./nullnoise <score.txt> --proof           (flat ⇒ silence check)
+//
+// Score format (text, one item per line):
+//   sr / dur / detuneL / detuneR / seedL / seedR — globals
+//   normpeak / fadein / fadeout                   — finalize params
+//   ridewin <len> <count> then <count> target-dB lines — loudness ride
+//   band <eventCount> then per-event lines:
+//     t0 freq freqEnd(0=none) peakDb q atk hold rel cut(-1=none)
+//   bands appear in chain order; events per band are time-sorted.
+
+#define _POSIX_C_SOURCE 200809L
+#include <stdio.h>
+#include <stdlib.h>
+#include <stdint.h>
+#include <string.h>
+#include <math.h>
+
+#define BLOCK 64
+
+typedef struct {
+    double t0, freq, freqEnd, peakDb, q, atk, hold, rel, end, cut;
+    int hasGlide, hasCut;
+} Event;
+
+typedef struct {
+    Event *ev;
+    int n;
+    int cursor;
+    int group; // which noise pair this band's chain runs on
+    double z1, z2;
+} Band;
+
+static void die(const char *msg) { fprintf(stderr, "nullnoise: %s\n", msg); exit(1); }
+
+// ── pink noise: LCG → Paul Kellett filter, byte-for-byte the JS one ───
+typedef struct {
+    uint32_t s;
+    double b0, b1, b2, b3, b4, b5, b6;
+} Pink;
+
+static void pink_init(Pink *p, uint32_t seed) { memset(p, 0, sizeof *p); p->s = seed; }
+
+static inline double pink_next(Pink *p) {
+    p->s = p->s * 1664525u + 1013904223u;
+    double w = ((double)p->s / 4294967296.0) * 2.0 - 1.0;
+    p->b0 = 0.99886 * p->b0 + w * 0.0555179;
+    p->b1 = 0.99332 * p->b1 + w * 0.0750759;
+    p->b2 = 0.969   * p->b2 + w * 0.153852;
+    p->b3 = 0.8665  * p->b3 + w * 0.3104856;
+    p->b4 = 0.55    * p->b4 + w * 0.5329522;
+    p->b5 = -0.7616 * p->b5 - w * 0.016898;
+    double out = (p->b0 + p->b1 + p->b2 + p->b3 + p->b4 + p->b5 + p->b6 + w * 0.5362) * 0.11;
+    p->b6 = w * 0.115926;
+    return out;
+}
+
+// envelope in dB-space: linear attack / hold / release, optional cut fade
+static inline double env_of(const Event *e, double time) {
+    double dt = time - e->t0;
+    if (dt < 0 || dt >= e->atk + e->hold + e->rel) return 0;
+    double v;
+    if (dt < e->atk) v = dt / e->atk;
+    else if (dt < e->atk + e->hold) v = 1;
+    else v = 1 - (dt - e->atk - e->hold) / e->rel;
+    if (e->hasCut) {
+        double f = (e->cut - time) / 0.03;
+        if (f < 0) f = 0; if (f > 1) f = 1;
+        v *= f;
+    }
+    return v;
+}
+
+int main(int argc, char **argv) {
+    const char *scorePath = NULL, *rawPath = NULL;
+    int proof = 0;
+    for (int i = 1; i < argc; i++) {
+        if (!strcmp(argv[i], "--raw") && i + 1 < argc) rawPath = argv[++i];
+        else if (!strcmp(argv[i], "--proof")) proof = 1;
+        else scorePath = argv[i];
+    }
+    if (!scorePath) die("usage: nullnoise <score.txt> [--raw out.f32] [--proof]");
+
+    // ── parse the score ───────────────────────────────────────────────
+    FILE *f = fopen(scorePath, "r");
+    if (!f) die("cannot open score");
+    int sr = 48000;
+    double dur = 0, detune[2] = { 1.0, 1.0 };
+    // groups: independent noise pairs, each with its own serial chain.
+    // residues sum in PARALLEL — a second group can reuse frequencies the
+    // first already boosts without the serial dB-addition blowup.
+    enum { MAXG = 8 };
+    uint32_t gseed[MAXG][2] = { { 0xBEEF, 0xC0FFEE } };
+    int nGroups = 1, curGroup = 0;
+    double normpeak = 0.88, fadein = 0.004, fadeout = 1.6;
+    double rideLen = 0; int rideN = 0; double *rideTarget = NULL;
+    Band *bands = NULL; int nBands = 0, capBands = 0;
+
+    char key[64];
+    while (fscanf(f, "%63s", key) == 1) {
+        if (!strcmp(key, "sr")) { if (fscanf(f, "%d", &sr) != 1) die("bad sr"); }
+        else if (!strcmp(key, "dur")) { if (fscanf(f, "%lf", &dur) != 1) die("bad dur"); }
+        else if (!strcmp(key, "detune")) { if (fscanf(f, "%lf %lf", &detune[0], &detune[1]) != 2) die("bad detune"); }
+        else if (!strcmp(key, "seed")) { if (fscanf(f, "%u %u", &gseed[0][0], &gseed[0][1]) != 2) die("bad seed"); }
+        else if (!strcmp(key, "group")) {
+            if (nGroups >= MAXG) die("too many groups");
+            if (fscanf(f, "%u %u", &gseed[nGroups][0], &gseed[nGroups][1]) != 2) die("bad group");
+            curGroup = nGroups++;
+        }
+        else if (!strcmp(key, "normpeak")) { if (fscanf(f, "%lf", &normpeak) != 1) die("bad normpeak"); }
+        else if (!strcmp(key, "fadein")) { if (fscanf(f, "%lf", &fadein) != 1) die("bad fadein"); }
+        else if (!strcmp(key, "fadeout")) { if (fscanf(f, "%lf", &fadeout) != 1) die("bad fadeout"); }
+        else if (!strcmp(key, "ridewin")) {
+            if (fscanf(f, "%lf %d", &rideLen, &rideN) != 2) die("bad ridewin");
+            rideTarget = malloc(sizeof(double) * rideN);
+            for (int i = 0; i < rideN; i++)
+                if (fscanf(f, "%lf", &rideTarget[i]) != 1) die("bad ride target");
+        } else if (!strcmp(key, "band")) {
+            int n; if (fscanf(f, "%d", &n) != 1) die("bad band");
+            if (nBands == capBands) {
+                capBands = capBands ? capBands * 2 : 32;
+                bands = realloc(bands, sizeof(Band) * capBands);
+            }
+            Band *b = &bands[nBands++];
+            memset(b, 0, sizeof *b);
+            b->ev = malloc(sizeof(Event) * n);
+            b->n = n;
+            b->group = curGroup;
+            for (int i = 0; i < n; i++) {
+                Event *e = &b->ev[i];
+                if (fscanf(f, "%lf %lf %lf %lf %lf %lf %lf %lf %lf",
+                           &e->t0, &e->freq, &e->freqEnd, &e->peakDb, &e->q,
+                           &e->atk, &e->hold, &e->rel, &e->cut) != 9)
+                    die("bad event");
+                e->hasGlide = e->freqEnd > 0;
+                e->hasCut = e->cut >= 0;
+                e->end = e->hasCut ? e->cut : e->t0 + e->atk + e->hold + e->rel;
+                if (proof) e->peakDb = 0;
+            }
+        } else die("unknown score key");
+    }
+    fclose(f);
+    if (dur <= 0 || nBands == 0) die("empty score");
+
+    long ns = (long)ceil(dur * sr);
+    float *out[2];
+    out[0] = calloc(ns, sizeof(float));
+    out[1] = calloc(ns, sizeof(float));
+    float dry[BLOCK], wet[BLOCK], acc[BLOCK];
+
+    // ── render: per channel, per group: EQ'd copy minus the original;
+    //    group residues sum in parallel ──────────────────────────────────
+    for (int ch = 0; ch < 2; ch++) {
+        Pink pinks[MAXG];
+        for (int g = 0; g < nGroups; g++) pink_init(&pinks[g], gseed[g][ch]);
+        for (int bi = 0; bi < nBands; bi++) { bands[bi].cursor = 0; bands[bi].z1 = 0; bands[bi].z2 = 0; }
+
+        for (long blockStart = 0; blockStart < ns; blockStart += BLOCK) {
+            int n = (int)(ns - blockStart < BLOCK ? ns - blockStart : BLOCK);
+            double time = (double)blockStart / sr;
+            memset(acc, 0, sizeof(float) * n);
+            for (int g = 0; g < nGroups; g++) {
+            for (int i = 0; i < n; i++) wet[i] = dry[i] = (float)pink_next(&pinks[g]);
+
+            for (int bi = 0; bi < nBands; bi++) {
+                Band *b = &bands[bi];
+                if (b->group != g) continue;
+                while (b->cursor < b->n && time > b->ev[b->cursor].end + 0.4) {
+                    b->cursor++; b->z1 = 0; b->z2 = 0;
+                }
+                if (b->cursor >= b->n) continue;
+                Event *e = &b->ev[b->cursor];
+                if (time < e->t0 - 0.05) continue;
+
+                double env = env_of(e, time);
+                double db = e->peakDb * env;
+                int ringing = fabs(b->z1) + fabs(b->z2) > 1e-9;
+                if (db <= 0.01 && !ringing) continue;
+
+                double freq = e->freq;
+                if (e->hasGlide) {
+                    // span uses e->end (which a mono-cut may have shortened)
+                    // to match the JS reference exactly
+                    double p = (time - e->t0) / (e->end - e->t0);
+                    if (p < 0) p = 0; if (p > 1) p = 1;
+                    freq = e->freq * pow(e->freqEnd / e->freq, p);
+                }
+                // RBJ peaking EQ — gain A breaks the cancellation
+                double A = pow(10.0, db / 40.0);
+                double fd = freq * detune[ch];
+                double fmax = sr * 0.45;
+                if (fd > fmax) fd = fmax;
+                double w0 = 2.0 * M_PI * fd / sr;
+                double alpha = sin(w0) / (2.0 * e->q);
+                double cosw = cos(w0);
+                double a0 = 1.0 + alpha / A;
+                double b0c = (1.0 + alpha * A) / a0;
+                double b1c = (-2.0 * cosw) / a0;
+                double b2c = (1.0 - alpha * A) / a0;
+                double a1c = (-2.0 * cosw) / a0;
+                double a2c = (1.0 - alpha / A) / a0;
+                double z1 = b->z1, z2 = b->z2;
+                for (int i = 0; i < n; i++) {
+                    double x = wet[i];
+                    double y = b0c * x + z1;
+                    z1 = b1c * x - a1c * y + z2;
+                    z2 = b2c * x - a2c * y;
+                    wet[i] = (float)y;
+                }
+                b->z1 = z1; b->z2 = z2;
+            }
+
+            for (int i = 0; i < n; i++) acc[i] += wet[i] - dry[i];
+            } // groups
+
+            float *o = out[ch];
+            for (int i = 0; i < n; i++) o[blockStart + i] = acc[i];
+        }
+    }
+
+    // ── proof: flat chain must null to bit-exact digital zero ─────────
+    if (proof) {
+        double peak = 0;
+        for (int ch = 0; ch < 2; ch++)
+            for (long i = 0; i < ns; i++)
+                if (fabs(out[ch][i]) > peak) peak = fabs(out[ch][i]);
+        if (peak == 0) { printf("ok proof: %d bands flat -> bit-exact silence (peak = 0)\n", nBands); return 0; }
+        printf("FAIL proof: peak = %g\n", peak); return 1;
+    }
+
+    // ── loudness ride: per-window RMS onto baked targets ──────────────
+    if (rideN > 0) {
+        double *gains = malloc(sizeof(double) * rideN);
+        for (int w = 0; w < rideN; w++) {
+            long a = (long)(w * rideLen * sr);
+            long z = (long)((w + 1) * rideLen * sr);
+            if (z > ns) z = ns;
+            double sum = 0;
+            for (int ch = 0; ch < 2; ch++)
+                for (long j = a; j < z; j++) sum += (double)out[ch][j] * out[ch][j];
+            long cnt = (z - a) * 2; if (cnt < 1) cnt = 1;
+            double rms = 10.0 * log10(sum / cnt + 1e-20);
+            double g = rideTarget[w] - rms;
+            if (g < -60) g = -60; if (g > 30) g = 30;
+            gains[w] = g;
+        }
+        double *sm = malloc(sizeof(double) * rideN); // 3-window smoothing
+        for (int w = 0; w < rideN; w++) {
+            int lo = w > 0 ? w - 1 : 0, hi = w < rideN - 1 ? w + 1 : rideN - 1;
+            double s = 0; for (int k = lo; k <= hi; k++) s += gains[k];
+            sm[w] = s / (hi - lo + 1);
+        }
+        for (long i = 0; i < ns; i++) { // linear interp between window centers
+            double pos = (double)i / sr / rideLen - 0.5;
+            int w0i = (int)floor(pos);
+            if (w0i < 0) w0i = 0; if (w0i > rideN - 1) w0i = rideN - 1;
+            int w1i = w0i + 1 < rideN ? w0i + 1 : rideN - 1;
+            double fr = pos - w0i; if (fr < 0) fr = 0; if (fr > 1) fr = 1;
+            double gdb = sm[w0i] * (1 - fr) + sm[w1i] * fr;
+            float lin = (float)pow(10.0, gdb / 20.0);
+            out[0][i] *= lin; out[1][i] *= lin;
+        }
+        free(gains); free(sm);
+    }
+
+    // ── normalize + edge fades ────────────────────────────────────────
+    double peak = 0;
+    for (int ch = 0; ch < 2; ch++)
+        for (long i = 0; i < ns; i++)
+            if (fabs(out[ch][i]) > peak) peak = fabs(out[ch][i]);
+    double g = peak > 0 ? normpeak / peak : 1.0;
+    long fi = (long)(fadein * sr), fo = (long)(fadeout * sr);
+    for (int ch = 0; ch < 2; ch++) {
+        for (long i = 0; i < ns; i++) out[ch][i] = (float)(out[ch][i] * g);
+        for (long i = 0; i < fi && i < ns; i++) out[ch][i] *= (float)i / fi;
+        for (long i = 0; i < fo && i < ns; i++) out[ch][ns - 1 - i] *= (float)i / fo;
+    }
+
+    // ── write interleaved f32le stereo ────────────────────────────────
+    FILE *o = rawPath ? fopen(rawPath, "wb") : stdout;
+    if (!o) die("cannot open output");
+    float *inter = malloc(sizeof(float) * 2 * ns);
+    for (long i = 0; i < ns; i++) { inter[2 * i] = out[0][i]; inter[2 * i + 1] = out[1][i]; }
+    fwrite(inter, sizeof(float), 2 * ns, o);
+    if (rawPath) fclose(o);
+    fprintf(stderr, "nullnoise: %d bands, %.1f s -> %s\n", nBands, (double)ns / sr, rawPath ? rawPath : "stdout");
+    return 0;
+}
diff --git a/pop/nullabye/c/run-c.mjs b/pop/nullabye/c/run-c.mjs
new file mode 100644
index 000000000..c7692912c
--- /dev/null
+++ b/pop/nullabye/c/run-c.mjs
@@ -0,0 +1,69 @@
+#!/usr/bin/env node
+// run-c.mjs — render a baked cancelled-noise score through the C engine
+// (nullnoise.c) and master to mp3. The composition lives in the lane
+// renderers (render-nuellaby.mjs --bake, pop/teknull/bin/...); this is
+// the shared DSP + finalize path.
+//
+// Usage:
+//   node pop/nullabye/c/run-c.mjs <score.txt> --out <out.mp3> [--master lullaby|techno]
+//   node pop/nullabye/c/run-c.mjs <score.txt> --raw <out.f32>   (engine output only)
+
+import { spawnSync } from "node:child_process";
+import { existsSync, mkdirSync, unlinkSync, statSync } from "node:fs";
+import { dirname, resolve } from "node:path";
+import { fileURLToPath } from "node:url";
+
+const HERE = dirname(fileURLToPath(import.meta.url));
+const ENGINE = resolve(HERE, "nullnoise");
+
+const args = process.argv.slice(2);
+const score = args.find((a) => !a.startsWith("--"));
+const _argi = (k) => { const i = args.indexOf(k); return i >= 0 ? args[i + 1] : null; };
+const outMp3 = _argi("--out");
+const rawOnly = _argi("--raw");
+const masterPreset = _argi("--master") || "lullaby";
+if (!score || (!outMp3 && !rawOnly)) {
+  console.error("usage: run-c.mjs <score.txt> --out <mp3> [--master lullaby|techno] | --raw <f32>");
+  process.exit(1);
+}
+
+// build the engine if missing or stale
+const cSrc = resolve(HERE, "nullnoise.c");
+if (!existsSync(ENGINE) || statSync(cSrc).mtimeMs > statSync(ENGINE).mtimeMs) {
+  console.log("[run-c] building nullnoise…");
+  const b = spawnSync("bash", [resolve(HERE, "build.sh")], { stdio: "inherit" });
+  if (b.status !== 0) process.exit(1);
+}
+
+const rawPath = rawOnly || `${outMp3}.f32.raw`;
+mkdirSync(dirname(rawPath), { recursive: true });
+const r = spawnSync(ENGINE, [score, "--raw", rawPath], { stdio: "inherit" });
+if (r.status !== 0) { console.error("✗ nullnoise failed"); process.exit(1); }
+if (rawOnly) process.exit(0);
+
+// master chains — lullaby mirrors render-nuellaby.mjs; techno hits harder
+const MASTERS = {
+  lullaby: [
+    "highpass=f=30",
+    "acompressor=threshold=-22dB:ratio=2.2:attack=25:release=220:makeup=2.0:knee=8",
+    "treble=g=0.8:f=9000",
+    "alimiter=limit=0.96:attack=5:release=80",
+  ],
+  techno: [
+    "highpass=f=24", // let the 30–40 Hz boom through; alimiter guards
+    "acompressor=threshold=-18dB:ratio=3.2:attack=8:release=120:makeup=3.5:knee=4",
+    "equalizer=f=45:t=q:w=1.2:g=4", // the deeeeep shelf under the kick
+    "bass=g=3:f=60",
+    "treble=g=1.6:f=8500",
+    "alimiter=limit=0.97:attack=3:release=50",
+  ],
+};
+const chain = MASTERS[masterPreset];
+if (!chain) { console.error(`unknown master preset: ${masterPreset}`); process.exit(1); }
+
+const ff = spawnSync("ffmpeg", ["-hide_banner", "-y", "-loglevel", "error",
+  "-f", "f32le", "-ar", "48000", "-ac", "2", "-i", rawPath,
+  "-af", chain.join(","), "-c:a", "libmp3lame", "-q:a", "2", outMp3], { stdio: "inherit" });
+try { unlinkSync(rawPath); } catch {}
+if (ff.status !== 0) { console.error("✗ ffmpeg failed"); process.exit(1); }
+console.log(`✓ ${outMp3} (C engine · ${masterPreset}-mastered)`);
diff --git a/pop/out/pop-library.json b/pop/out/pop-library.json
new file mode 100644
index 000000000..8867bc226
--- /dev/null
+++ b/pop/out/pop-library.json
@@ -0,0 +1,1416 @@
+{
+  "generated": "2026-06-15T17:11:43.457Z",
+  "count": 91,
+  "tracks": [
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/momboba/out/momabobasheep.mp3",
+      "title": "momabobasheep",
+      "lane": "momboba",
+      "backend": "C engine",
+      "status": "RELEASED",
+      "updated": "2026-06-12T03:15:25.590Z",
+      "revisions": 4,
+      "bytes": 25933009,
+      "durationSec": 600,
+      "bpm": null,
+      "key": null,
+      "releaseDate": "2026-06-12",
+      "links": {
+        "spotify": null,
+        "apple": null,
+        "youtube": null,
+        "distrokid": "https://distrokid.com/dashboard/album/?albumuuid=2456D650-9AEC-4C1A-831BCE628047AF6C>."
+      }
+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/big-pictures/out/amaythingra.mp3",
+      "title": "amaythingra",
+      "lane": "big-pictures",
+      "backend": "C engine",
+      "status": "RELEASED",
+      "updated": "2026-06-04T15:56:59.874Z",
+      "revisions": 15,
+      "bytes": 10921965,
+      "durationSec": 273,
+      "bpm": 120,
+      "key": "G major",
+      "releaseDate": "2026-06-03",
+      "links": {
+        "spotify": "https://open.spotify.com/track/4hVFWMISa235ybIEfOYuwt",
+        "apple": "https://music.apple.com/us/album/amaythingra/6776359148?i=6776359150",
+        "youtube": "https://youtu.be/2FwOYCXS4UA",
+        "distrokid": null
+      }
+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/marimba/out/marimbaba.mp3",
+      "title": "marimbaba",
+      "lane": "marimba",
+      "backend": "marimba synth (JS)",
+      "status": "RELEASED",
+      "updated": "2026-05-23T03:50:50.812Z",
+      "revisions": 9,
+      "bytes": 1946733,
+      "durationSec": 83.6,
+      "bpm": 56,
+      "key": "F major",
+      "releaseDate": "2026-05-22",
+      "links": {
+        "spotify": "https://open.spotify.com/track/1gopbVPw6LoinIpOANOnEG",
+        "apple": "https://music.apple.com/us/album/marimbaba/6772460819?i=6772460820",
+        "youtube": "https://youtu.be/jXdnJjdV_kY",
+        "distrokid": "https://distrokid.com/dashboard/album/?albumuuid=772E43F5-D367-44A9-A7B4A1FA4E57FBD9"
+      }
+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/chillwave/out/helpabeach.mp3",
+      "title": "helpabeach",
+      "lane": "chillwave",
+      "backend": "JS DSP",
+      "status": "RELEASED",
+      "updated": "2026-05-22T01:43:40.898Z",
+      "revisions": 13,
+      "bytes": 3338229,
+      "durationSec": 151.1,
+      "bpm": 84,
+      "key": "A minor",
+      "releaseDate": null,
+      "links": {
+        "spotify": "https://open.spotify.com/track/3jzlAylJQLSsNIXjnEY1e8",
+        "apple": "https://music.apple.com/us/album/helpabeach/6772056808?i=6772057057",
+        "youtube": "https://youtu.be/KVynj0RAwg8",
+        "distrokid": "https://distrokid.com/dashboard/album/?albumuuid=B1F5253A-11FA-40EF-83A89866A157829A"
+      }
+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/dance/out/trancenwaltz.mp3",
+      "title": "trancenwaltz",
+      "lane": "dance",
+      "backend": "C engine",
+      "status": "RELEASED",
+      "updated": "2026-05-17T23:59:44.894Z",
+      "revisions": 37,
+      "bytes": 1527477,
+      "durationSec": 86.6,
+      "bpm": null,
+      "key": null,
+      "releaseDate": null,
+      "links": {
+        "spotify": "https://open.spotify.com/track/3PIPwPqptVlWy71rCEhQum",
+        "apple": "https://music.apple.com/us/album/trancenwaltz/6773318345?i=6773318348",
+        "youtube": "https://youtu.be/RBG3k_XsfLA",
+        "distrokid": "https://distrokid.com/dashboard/album/?albumuuid=8FF25085-8F58-4A3A-986A52A21D638805"
+      }
+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/jungle/out/solafiya.mp3",
+      "title": "solafiya",
+      "lane": "jungle",
+      "backend": "JS DSP",
+      "status": "MASTERING",
+      "updated": "2026-05-24T19:31:08.679Z",
+      "revisions": 4,
+      "bytes": 5901345,
+      "durationSec": 100.2,
+      "bpm": 176,
+      "key": null,
+      "releaseDate": null,
+      "links": {
+        "spotify": null,
+        "apple": null,
+        "youtube": null,
+        "distrokid": null
+      }
+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/teknull/out/teknull.mp3",
+      "title": "teknull",
+      "lane": "teknull",
+      "backend": "JS DSP",
+      "status": "WIP",
+      "updated": "2026-06-11T23:43:42.582Z",
+      "revisions": 0,
+      "bytes": 4447749,
+      "durationSec": 120,
+      "bpm": 140,
+      "key": "A minor",
+      "releaseDate": null,
+      "links": {
+        "spotify": null,
+        "apple": null,
+        "youtube": null,
+        "distrokid": null
+      }
+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/nullabye/out/nuellaby.mp3",
+      "title": "nuellaby",
+      "lane": "nullabye",
+      "backend": "C engine",
+      "status": "WIP",
+      "updated": "2026-06-11T23:03:46.120Z",
+      "revisions": 0,
+      "bytes": 2666805,
+      "durationSec": 120,
+      "bpm": 76,
+      "key": "C major",
+      "releaseDate": null,
+      "links": {
+        "spotify": null,
+        "apple": null,
+        "youtube": "https://youtu.be/_Rk-hmIMv6I)):",
+        "distrokid": null
+      }
+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/nullabye/out/nullabye.mp3",
+      "title": "nullabye",
+      "lane": "nullabye",
+      "backend": "C engine",
+      "status": "WIP",
+      "updated": "2026-06-11T21:23:24.127Z",
+      "revisions": 0,
+      "bytes": 1561845,
+      "durationSec": 78.8,
+      "bpm": 76,
+      "key": "C major",
+      "releaseDate": null,
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+      "lane": "maytrax",
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+    },
+    {
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+      "lane": "marimba",
+      "backend": "marimba synth (JS)",
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+    },
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+      "path": "/Users/jas/aesthetic-computer/pop/marimba/out/mommyboo.mp3",
+      "title": "mommyboo",
+      "lane": "marimba",
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+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/marimba/out/wibblybop.mp3",
+      "title": "wibblybop",
+      "lane": "marimba",
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+    {
+      "path": "/Users/jas/aesthetic-computer/pop/marimba/out/buzaboo.mp3",
+      "title": "buzaboo",
+      "lane": "marimba",
+      "backend": "marimba synth (JS)",
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+    {
+      "path": "/Users/jas/aesthetic-computer/pop/marimba/out/lollybap.mp3",
+      "title": "lollybap",
+      "lane": "marimba",
+      "backend": "marimba synth (JS)",
+      "status": "UNRELEASED",
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+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/marimba/out/dewabap.mp3",
+      "title": "dewabap",
+      "lane": "marimba",
+      "backend": "marimba synth (JS)",
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+      "durationSec": 62.1,
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+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/marimba/out/dingaba.mp3",
+      "title": "dingaba",
+      "lane": "marimba",
+      "backend": "marimba synth (JS)",
+      "status": "UNRELEASED",
+      "updated": "2026-05-23T01:37:55.193Z",
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+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/marimba/out/kookabap.mp3",
+      "title": "kookabap",
+      "lane": "marimba",
+      "backend": "marimba synth (JS)",
+      "status": "UNRELEASED",
+      "updated": "2026-05-23T01:37:40.850Z",
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+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/marimba/out/flutterbap.mp3",
+      "title": "flutterbap",
+      "lane": "marimba",
+      "backend": "marimba synth (JS)",
+      "status": "UNRELEASED",
+      "updated": "2026-05-23T01:24:08.226Z",
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+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/marimba/out/marimbabapp.mp3",
+      "title": "marimbabapp",
+      "lane": "marimba",
+      "backend": "marimba synth (JS)",
+      "status": "UNRELEASED",
+      "updated": "2026-05-22T22:09:18.722Z",
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+      "links": null
+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/hum/out/hum.mp3",
+      "title": "hum",
+      "lane": "hum",
+      "backend": "JS DSP",
+      "status": "UNRELEASED",
+      "updated": "2026-05-22T19:35:46.854Z",
+      "revisions": 1,
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+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/marimba/out/tinkaboo.mp3",
+      "title": "tinkaboo",
+      "lane": "marimba",
+      "backend": "marimba synth (JS)",
+      "status": "UNRELEASED",
+      "updated": "2026-05-21T16:00:37.912Z",
+      "revisions": 9,
+      "bytes": 3205215,
+      "durationSec": 60,
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+      "releaseDate": null,
+      "links": null
+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/marimba/out/bronzaba.mp3",
+      "title": "bronzaba",
+      "lane": "marimba",
+      "backend": "marimba synth (JS)",
+      "status": "UNRELEASED",
+      "updated": "2026-05-21T15:59:47.418Z",
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+      "durationSec": 78,
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+      "releaseDate": null,
+      "links": null
+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/marimba/out/doziba.mp3",
+      "title": "doziba",
+      "lane": "marimba",
+      "backend": "marimba synth (JS)",
+      "status": "UNRELEASED",
+      "updated": "2026-05-21T15:59:35.032Z",
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+      "durationSec": 106.4,
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+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/gecs/out/gecs.mp3",
+      "title": "gecs",
+      "lane": "gecs",
+      "backend": "JS DSP",
+      "status": "UNRELEASED",
+      "updated": "2026-05-20T14:15:08.174Z",
+      "revisions": 1,
+      "bytes": 2201469,
+      "durationSec": 84.4,
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+      "links": null
+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/hippyhayzard/out/hippyhayzard.mp3",
+      "title": "hippyhayzard",
+      "lane": "hippyhayzard",
+      "backend": "JS DSP",
+      "status": "UNRELEASED",
+      "updated": "2026-05-19T05:47:33.917Z",
+      "revisions": 1,
+      "bytes": 1122261,
+      "durationSec": 93.4,
+      "bpm": null,
+      "key": null,
+      "releaseDate": null,
+      "links": null
+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/jungle/out/solfia.mp3",
+      "title": "solfia",
+      "lane": "jungle",
+      "backend": "JS DSP",
+      "status": "UNRELEASED",
+      "updated": "2026-05-17T13:53:58.171Z",
+      "revisions": 4,
+      "bytes": 5794513,
+      "durationSec": 83.5,
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+      "releaseDate": null,
+      "links": null
+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/jungle/out/rodando.mp3",
+      "title": "rodando",
+      "lane": "jungle",
+      "backend": "JS DSP",
+      "status": "UNRELEASED",
+      "updated": "2026-05-17T04:05:18.246Z",
+      "revisions": 4,
+      "bytes": 5215803,
+      "durationSec": 81.1,
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+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/jungle/out/raggasol.mp3",
+      "title": "raggasol",
+      "lane": "jungle",
+      "backend": "JS DSP",
+      "status": "UNRELEASED",
+      "updated": "2026-05-17T04:05:12.366Z",
+      "revisions": 4,
+      "bytes": 5182581,
+      "durationSec": 83.5,
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+      "releaseDate": null,
+      "links": null
+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/jungle/out/jungleton.mp3",
+      "title": "jungleton",
+      "lane": "jungle",
+      "backend": "JS DSP",
+      "status": "UNRELEASED",
+      "updated": "2026-05-17T04:05:06.167Z",
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+      "releaseDate": null,
+      "links": null
+    },
+    {
+      "path": "/Users/jas/aesthetic-computer/pop/dance/out/.booty.mp3",
+      "title": ".booty",
+      "lane": "dance",
+      "backend": "C engine",
+      "status": "UNRELEASED",
+      "updated": "2026-05-15T18:31:19.939Z",
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+      "releaseDate": null,
+      "links": null
+    }
+  ]
+}
\ No newline at end of file
diff --git a/pop/teknull/bin/gen-illy.mjs b/pop/teknull/bin/gen-illy.mjs
new file mode 100644
index 000000000..1f592e1d4
--- /dev/null
+++ b/pop/teknull/bin/gen-illy.mjs
@@ -0,0 +1,133 @@
+#!/usr/bin/env node
+// teknull/bin/gen-illy.mjs — generate the teknull album cover via
+// gpt-image-2, then embed it into the rendered mp3 as ID3 art.
+//
+// Teknull's cover is the technique made visible: jeffrey alone at a
+// rack of vintage 32-band graphic equalizers in a dark warehouse,
+// pushing one slider up — carving the track out of noise. Red diegetic
+// work-lamp light, amber LED freckles, closed Citrus Neo with the
+// butterfly scrap on a road case. Same identity-ref path as
+// pop/momboba/bin/gen-illy.mjs.
+//
+// Prompt: pop/teknull/teknull.illy.txt (lowercase fragments — papers voice)
+// Output: pop/teknull/out/teknull-cover.png
+// Embed:  pop/teknull/out/teknull.mp3  (ID3v2 attached picture)
+//
+// Usage:
+//   node pop/teknull/bin/gen-illy.mjs            # cached if cover exists
+//   node pop/teknull/bin/gen-illy.mjs --force    # regenerate
+//   node pop/teknull/bin/gen-illy.mjs --embed-only   # skip gen, just embed
+
+import { readFileSync, writeFileSync, existsSync, mkdirSync, renameSync } from "node:fs";
+import { resolve, dirname } from "node:path";
+import { fileURLToPath } from "node:url";
+import { spawnSync } from "node:child_process";
+
+const HERE = dirname(fileURLToPath(import.meta.url));
+const LANE = resolve(HERE, "..");
+const REPO = resolve(LANE, "..", "..");
+
+const flags = {};
+for (let i = 2; i < process.argv.length; i++) {
+  if (process.argv[i].startsWith("--")) flags[process.argv[i].slice(2)] = true;
+}
+const FORCE = flags.force === true;
+const SIZE = "1024x1024";
+
+const _af = (k, d) => { const i = process.argv.indexOf(k); return i >= 0 && process.argv[i + 1] ? process.argv[i + 1] : d; };
+const PROMPT_PATH = resolve(process.cwd(), _af("--prompt", `${LANE}/teknull.illy.txt`));
+const OUT_PATH    = resolve(process.cwd(), _af("--cover",  `${LANE}/out/teknull-cover.png`));
+const MP3_PATH    = resolve(process.cwd(), _af("--mp3",    `${LANE}/out/teknull.mp3`));
+mkdirSync(`${LANE}/out`, { recursive: true });
+
+// ── identity refs (mirrors momboba/bin/gen-illy.mjs) ─────────────────────
+const SHOOT_DIR   = `${REPO}/portraits/jeffrey/corpus/shoot-2k`;
+const ARCHIVE_DIR = `${REPO}/portraits/jeffrey/ig-archive/whistlegraph`;
+const REFS = [
+  `${SHOOT_DIR}/jeffery-av--07.jpg`,
+  `${SHOOT_DIR}/jeffery-av--01.jpg`,
+  `${SHOOT_DIR}/jeffery-av--04.jpg`,
+  `${ARCHIVE_DIR}/2018-12-02_Bq4ckGFFNtW.jpg`,
+  `${ARCHIVE_DIR}/2020-09-02_CEpxlO2FOvD.jpg`,
+  `${ARCHIVE_DIR}/2021-07-10_CRI095Vl7AO_1.jpg`,
+  `${ARCHIVE_DIR}/2025-01-25_DFQ2lHPzN_W.jpg`,
+].filter((p) => {
+  if (existsSync(p)) return true;
+  console.warn(`  ⚠ ref missing, dropping: ${p}`);
+  return false;
+});
+
+function loadOpenAIKey() {
+  if (process.env.OPENAI_API_KEY) return process.env.OPENAI_API_KEY;
+  const vault = `${REPO}/aesthetic-computer-vault/.devcontainer/envs/devcontainer.env`;
+  if (existsSync(vault)) {
+    for (const line of readFileSync(vault, "utf8").split("\n")) {
+      if (line.startsWith("OPENAI_API_KEY=")) {
+        return line.slice("OPENAI_API_KEY=".length).trim().replace(/^['"]|['"]$/g, "");
+      }
+    }
+  }
+  throw new Error("OPENAI_API_KEY not set and not found in vault");
+}
+
+// ── embed the cover into the mp3 as ID3v2 attached picture ───────────────
+function embedCover() {
+  if (!existsSync(OUT_PATH) || !existsSync(MP3_PATH)) {
+    console.warn(`  ⚠ skip embed — need both ${OUT_PATH} and ${MP3_PATH}`);
+    return;
+  }
+  const tmp = `${MP3_PATH}.embed.mp3`;
+  const r = spawnSync("ffmpeg", ["-hide_banner", "-y", "-loglevel", "error",
+    "-i", MP3_PATH, "-i", OUT_PATH,
+    "-map", "0:a", "-map", "1:v", "-c", "copy", "-id3v2_version", "3",
+    "-metadata:s:v", "title=cover", "-metadata:s:v", "comment=Cover (front)",
+    "-disposition:v", "attached_pic", tmp], { stdio: "inherit" });
+  if (r.status !== 0 || !existsSync(tmp)) { console.error("✗ embed failed"); return; }
+  renameSync(tmp, MP3_PATH);
+  console.log(`✓ cover embedded → ${MP3_PATH.replace(REPO + "/", "")}`);
+}
+
+if (flags["embed-only"]) { embedCover(); process.exit(0); }
+
+if (existsSync(OUT_PATH) && !FORCE) {
+  console.log(`✓ cached cover → ${OUT_PATH.replace(REPO + "/", "")} (use --force to regen)`);
+  embedCover();
+  process.exit(0);
+}
+
+const apiKey = loadOpenAIKey();
+const prompt = readFileSync(PROMPT_PATH, "utf8").trim();
+console.log(`▸ teknull cover · ${SIZE} · ${REFS.length} refs`);
+const t0 = Date.now();
+
+const fd = new FormData();
+fd.append("model", "gpt-image-2");
+fd.append("prompt", prompt);
+fd.append("size", SIZE);
+fd.append("quality", "high");
+fd.append("n", "1");
+for (const ref of REFS) {
+  const buf = readFileSync(ref);
+  const ext = ref.toLowerCase().endsWith(".png") ? "png"
+            : ref.toLowerCase().endsWith(".webp") ? "webp" : "jpeg";
+  fd.append("image[]", new Blob([buf], { type: `image/${ext}` }), ref.split("/").pop());
+}
+const res = await fetch("https://api.openai.com/v1/images/edits", {
+  method: "POST",
+  headers: { Authorization: `Bearer ${apiKey}` },
+  body: fd,
+});
+if (!res.ok) {
+  console.error(`✗ OpenAI ${res.status}: ${(await res.text()).slice(0, 600)}`);
+  process.exit(1);
+}
+const json = await res.json();
+const b64 = json.data?.[0]?.b64_json;
+if (!b64) {
+  console.error(`✗ no image: ${JSON.stringify(json).slice(0, 280)}`);
+  process.exit(1);
+}
+writeFileSync(OUT_PATH, Buffer.from(b64, "base64"));
+console.log(`✓ ${((Date.now() - t0) / 1000).toFixed(1)}s → ${OUT_PATH.replace(REPO + "/", "")}`);
+
+embedCover();
diff --git a/pop/teknull/bin/render-teknull.mjs b/pop/teknull/bin/render-teknull.mjs
new file mode 100644
index 000000000..a2fda6a1c
--- /dev/null
+++ b/pop/teknull/bin/render-teknull.mjs
@@ -0,0 +1,312 @@
+#!/usr/bin/env node
+// render-teknull.mjs — fast techno carved from cancelled noise, on a
+// strict 32-EQ-point budget. Composition lives here; ALL DSP runs in the
+// shared C engine (pop/nullabye/c/nullnoise.c) — this script just bakes
+// the score and calls run-c.mjs with the techno master preset.
+//
+// The trick (after Andy Brewer, https://youtu.be/_Rk-hmIMv6I): two copies
+// of pink noise, one phase-inverted — silence — and every sound is a
+// peaking EQ bell breaking the cancellation. Techno turns out to be the
+// technique's home turf:
+//   · the CLAP is literally a burst of the noise itself (wide 2.3k bell)
+//   · the ACID LINE is one monophonic EQ point — 303 slides are freqEnd
+//     glides, accents are gain, note-off is the mono-cut
+//   · the KICK is the classic 115→44 Hz pitch-drop, carved not synthesized
+//
+// 140 BPM 4/4 → bar = 240/140 s, so 70 bars = 120.0 s exactly: 2:00.
+//
+//   bars   section     what runs
+//   0–7    intro       kick, hats join, clap at 6, veil throughout
+//   8–15   build       + offbeat sub, drone, perc, riser
+//   16–23  acid        + the 303 line, working the room
+//   24–39  drop A      + stabs, rim ghosts, air; lead hook from 32
+//   40–47  breakdown   kick out — chord swells, noise-wash, subdrop boom
+//   48–63  drop B      everything + ride 16ths + acid echo an octave up
+//   64–69  outro       strip to kick + hats, final boom, veil closes
+//
+// Run:
+//   node pop/teknull/bin/render-teknull.mjs            # → out/teknull.mp3
+//   node pop/teknull/bin/render-teknull.mjs --bake-only
+
+import { writeFileSync, mkdirSync } from "node:fs";
+import { spawnSync } from "node:child_process";
+import { dirname, resolve } from "node:path";
+import { fileURLToPath } from "node:url";
+
+const HERE = dirname(fileURLToPath(import.meta.url));
+const SR = 48_000;
+const BPM = 140;
+const BEAT = 60 / BPM;
+const BAR = 4 * BEAT;
+const TOTAL_BARS = 70; // 70 × 240/140 = 120.0 s — exactly 2:00
+const totalSec = TOTAL_BARS * BAR;
+
+const t = (bar, beat = 0) => bar * BAR + beat * BEAT;
+const st = (semis) => 110 * Math.pow(2, semis / 12); // A2 = 110 Hz base
+
+// sections
+const DROP_A = (b) => b >= 24 && b <= 39;
+const BREAK = (b) => b >= 40 && b <= 47;
+const DROP_B = (b) => b >= 48 && b <= 63;
+const DROP = (b) => DROP_A(b) || DROP_B(b);
+const OUTRO = (b) => b >= 64;
+
+// ── 32-point budget: every lane declared up front, audited below ──────
+const MAX_POINTS = 32;
+const lanes = new Map(); // name → { events: [] }
+
+function note(lane, t0, { freq, freqEnd = 0, peakDb, q, atk, hold, rel, group = 0 }) {
+  let L = lanes.get(lane);
+  if (!L) { L = { events: [], group }; lanes.set(lane, L); }
+  const prev = L.events[L.events.length - 1];
+  if (prev && prev.end > t0) { prev.cut = t0; prev.end = t0; } // mono-clip
+  L.events.push({ t0, freq, freqEnd, peakDb, q, atk, hold, rel, end: t0 + atk + hold + rel, cut: -1 });
+}
+
+// ── groove machinery ──────────────────────────────────────────────────
+// SWING: odd 16ths land late. EAGER hats push early, claps drag late
+// (the hellsine "eager percussion" trick). JITTER: deterministic ±4 ms
+// human wobble on everything that isn't the kick — the kick is the law.
+const SW = 0.08; // beats of swing on odd 16ths (~34 ms at 140)
+const sw = (beat) => (Math.round(beat * 4) % 2 ? beat + SW : beat);
+const jit = (seedA, seedB, amt = 0.004) => {
+  let s = (seedA * 374761393 + seedB * 668265263 + 1442695041) >>> 0;
+  s = (s ^ (s >> 13)) * 1274126177 >>> 0;
+  return ((s / 4294967296) * 2 - 1) * amt;
+};
+const EAGER = -0.008, DRAG = 0.007; // seconds: hats lean in, claps lean back
+
+// ── the score ─────────────────────────────────────────────────────────
+// A natural minor. Stabs on Am (A3 C4 E4 A4); acid on A2.
+const STAB = [220, 261.63, 329.63];
+const STAB_RHYTHM = [[0.75, 1.75, 3.25], [0.5, 2.25, 3.75]]; // alternates by bar
+
+// acid pattern: 16 steps × [semitones from A2 | null=rest, accent, slideToNext]
+// the RESTS are the groove — a 303 line has to breathe
+const ACID = [
+  [0, 1, 0], [null, 0, 0], [0, 0, 0], [12, 0, 1],
+  [null, 0, 0], [0, 1, 0], [null, 0, 0], [7, 0, 0],
+  [null, 0, 0], [0, 0, 0], [3, 0, 1], [null, 0, 0],
+  [0, 1, 0], [null, 0, 0], [10, 0, 1], [12, 0, 0],
+];
+const ACID_FILL = [ // every 4th bar climbs out the top
+  [0, 1, 0], [0, 0, 0], [12, 0, 0], [0, 0, 0],
+  [3, 1, 0], [7, 0, 1], [10, 0, 0], [12, 0, 1],
+  [15, 1, 0], [12, 0, 0], [10, 0, 0], [7, 0, 0],
+  [3, 0, 1], [0, 1, 0], [-2, 0, 1], [0, 0, 0],
+];
+
+for (let bar = 0; bar < TOTAL_BARS; bar++) {
+  const inBreak = BREAK(bar);
+  const drop = DROP(bar);
+
+  // kick — four on the floor, out for the breakdown. two stacked bells
+  // per hit: the click-thump and a SUB BODY underneath (52→40) with a
+  // long tail — at 40 Hz a cycle is 25 ms, the boom needs time to bloom.
+  // SOFT from the very start: the intro opens at +22 dB with a slow
+  // attack and a duller sweep, growing to the full machine thump by bar 8.
+  if (!inBreak && bar <= 67)
+    for (const beat of [0, 1, 2, 3]) {
+      const soft = bar < 8 ? bar / 8 : 1;
+      note("kick", t(bar, beat), {
+        freq: 80 + soft * 35, freqEnd: 38, peakDb: 22 + soft * 9, q: 2.2,
+        atk: 0.002 + (1 - soft) * 0.012, hold: 0.02, rel: 0.32,
+      });
+      if (bar >= 4)
+        note("kickSub", t(bar, beat + 0.025), { freq: 52, freqEnd: 40, peakDb: 26 * Math.min(1, soft + 0.3), q: 4.5, atk: 0.008, hold: 0.08, rel: 0.26 });
+    }
+
+  // hats — eager (lean in early), accent cycle, open hat wanders
+  if (bar <= 67) // ticking from bar 0 — soft at first, full by bar 8
+    [0.5, 1.5, 2.5, 3.5].forEach((beat, i) =>
+      note("hatC", t(bar, beat) + EAGER + jit(bar, i), {
+        freq: 9200, peakDb: (bar < 8 ? -3 : 0) + [22, 19, 23, 20][i], q: 2.5,
+        atk: 0.002, hold: 0.006, rel: 0.04,
+      }));
+  if (bar >= 4 && bar <= 67 && !inBreak)
+    note("hatO", t(bar, bar % 4 === 2 ? 1.5 : 3.5) + EAGER, { freq: 7400, peakDb: 20, q: 1.8, atk: 0.002, hold: 0.015, rel: 0.2 });
+
+  // clap — 2 and 4, dragged late against the eager hats; ghost "clap-a"
+  // closing every 4th bar. the most honest instrument here, it IS the noise
+  if (bar >= 6 && bar <= 67 && !inBreak) {
+    for (const beat of [1, 3])
+      note("clap", t(bar, beat) + DRAG, { freq: 2300, peakDb: 21, q: 1.3, atk: 0.002, hold: 0.03, rel: 0.15 });
+    if (bar % 4 === 3)
+      note("clap", t(bar, 3.375) + DRAG, { freq: 2300, peakDb: 15, q: 1.3, atk: 0.002, hold: 0.02, rel: 0.1 });
+  }
+
+  // sub — offbeat "oontz" with a small downward settle per note; odd bars
+  // anticipate beat 3 by a 16th — that little push IS the groove
+  if (bar >= 8 && bar <= 67 && !inBreak)
+    for (const beat of bar % 2 ? [0.5, 1.5, 2.75, 3.5] : [0.5, 1.5, 2.5, 3.5])
+      note("sub", t(bar, beat), { freq: 56, freqEnd: 49, peakDb: 26, q: 6, atk: 0.01, hold: 0.16, rel: 0.16 });
+
+  // acid — ONE monophonic EQ point doing 303 work, now swung + jittered
+  if ((bar >= 16 && bar <= 39) || DROP_B(bar)) {
+    const pat = bar % 4 === 3 ? ACID_FILL : ACID;
+    for (let k = 0; k < 16; k++) {
+      const [semi, accent, slide] = pat[k];
+      if (semi === null) continue;
+      const nxt = pat[(k + 1) % 16];
+      note("acid", t(bar, sw(k * 0.25)) + jit(bar * 16 + k, 7, 0.003), {
+        freq: st(semi),
+        freqEnd: slide && nxt[0] !== null ? st(nxt[0]) : 0,
+        peakDb: accent ? 23 : 17, q: 22, atk: 0.008, hold: 0.05, rel: 0.06,
+      });
+    }
+  }
+
+  // acid2 — drop B echo, an octave up, 3 sixteenths behind, quieter
+  if (DROP_B(bar)) {
+    const pat = bar % 4 === 3 ? ACID_FILL : ACID;
+    for (let k = 0; k < 16; k++) {
+      const [semi, , ] = pat[k];
+      if (semi === null) continue;
+      note("acid2", t(bar, sw(k * 0.25 + 0.75)) + jit(bar * 16 + k, 13, 0.003), { freq: st(semi + 12), peakDb: 13, q: 30, atk: 0.008, hold: 0.04, rel: 0.05 });
+    }
+  }
+
+  // stabs — Am hits, rhythm alternates by bar, riding the swing
+  if (drop) {
+    for (const beat of STAB_RHYTHM[bar % 2]) {
+      STAB.forEach((f, i) =>
+        note(`stab${i}`, t(bar, sw(beat)), { freq: f, peakDb: 17, q: 40, atk: 0.006, hold: 0.07, rel: 0.12 }));
+      note("stabOct", t(bar, sw(beat)), { freq: 440, peakDb: 14, q: 40, atk: 0.006, hold: 0.07, rel: 0.12 });
+    }
+  }
+
+  // percussion spice — swung
+  if (bar >= 8 && bar <= 63)
+    note("perc1", t(bar, sw(bar % 2 ? 3.75 : 1.25)) + jit(bar, 23), { freq: 380, freqEnd: 200, peakDb: 16, q: 5, atk: 0.003, hold: 0.02, rel: 0.09 });
+  if (drop)
+    for (const beat of [2.75, 3.25])
+      note("perc2", t(bar, sw(beat)) + jit(bar * 4 + beat, 31), { freq: 4600, peakDb: 14, q: 9, atk: 0.002, hold: 0.008, rel: 0.05 });
+
+  // ride 16ths — drop B sizzle, swung, with a hole at the bar's last 16th
+  if (DROP_B(bar))
+    for (let k = 0; k < 16; k++) {
+      if (k % 8 === 7) continue;
+      note("ride16", t(bar, sw(k * 0.25)) + jit(bar * 16 + k, 41, 0.002), { freq: 12500, peakDb: k % 4 === 2 ? 12 : 9, q: 5, atk: 0.002, hold: 0.005, rel: 0.04 });
+    }
+
+  // LEADS — the hook rides the WHOLE drop now: a swung 2-bar pentatonic
+  // riff, lifting a fifth in each drop's back half, octave echo trailing
+  if (drop) {
+    const riff = bar % 2 === 0
+      ? [[440, 0.75, 0.5], [523.25, 1.5, 0.25], [659.26, 2.25, 0.75], [587.33, 3.25, 0.5]]
+      : [[659.26, 0.5, 0.5], [587.33, 1.25, 0.25], [523.25, 1.75, 0.5], [440, 2.5, 1.25]];
+    const lift = (DROP_A(bar) && bar >= 32) || (DROP_B(bar) && bar >= 56) ? 1.5 : 1;
+    for (const [f, beat, beats] of riff) {
+      const t0 = t(bar, sw(beat)) + jit(bar * 7 + beat * 4, 99, 0.003);
+      note("lead", t0, { freq: f * lift, peakDb: 22, q: 35, atk: 0.015, hold: beats * BEAT - 0.02, rel: 0.18 });
+      note("lead2", t0 + 0.75 * BEAT, { freq: f * lift * 2, peakDb: 13, q: 45, atk: 0.02, hold: beats * BEAT * 0.5, rel: 0.12 });
+    }
+  }
+
+  // breakdown — chord swells + rising noise-wash while the kick rests
+  if (inBreak) {
+    note("noisewash", t(bar), { freq: 1200 + (bar - 40) * 350, peakDb: 9 + (bar - 40) * 0.7, q: 0.5, atk: 0.5, hold: BAR - 0.5, rel: 0.8 });
+  }
+}
+
+// one-shots: crashes, risers, drop zaps, sub booms
+for (const bar of [8, 16, 24, 32, 40, 48, 56, 64])
+  note("crash", t(bar), { freq: 5500, peakDb: 16, q: 0.7, atk: 0.003, hold: 0.05, rel: 1.0 });
+for (const bar of [14, 22, 46, 62])
+  note("riser", t(bar), { freq: 600, freqEnd: 6500, peakDb: 8.5, q: 1.2, atk: 2 * BAR - 0.6, hold: 0.3, rel: 0.3 });
+for (const bar of [24, 48, 64])
+  note("fall", t(bar), { freq: 3500, freqEnd: 90, peakDb: 18, q: 2, atk: 0.004, hold: 0.05, rel: 0.45 });
+for (const bar of [40, 64, 68])
+  note("subdrop", t(bar), { freq: 55, freqEnd: 30, peakDb: 24, q: 3, atk: 0.01, hold: 0.4, rel: 2.0 });
+
+// breakdown chord swells — ONE long event per lane, not per-bar
+STAB.forEach((f, i) =>
+  note(`swell${i}`, t(40), { freq: f, peakDb: 20, q: 28, atk: 2.0, hold: 8 * BAR - 3.5, rel: 1.5, group: 1 }));
+
+// ── HARMONY CHANNEL (group 1) — a SECOND cancellation pair ────────────
+// independent pink noise + its own serial chain, residues summed in
+// parallel with the main channel. that means these chords can sit on the
+// SAME frequencies the stabs/leads already boost — no serial dB blowup.
+// voice-led Am / F / C / G, two bars per chord: real harmonic motion.
+{
+  const VOICED = {
+    Am: [220, 261.63, 329.63],   // A3 C4 E4
+    F:  [220, 261.63, 349.23],   // A3 C4 F4
+    C:  [196, 261.63, 329.63],   // G3 C4 E4
+    G:  [196, 246.94, 293.66],   // G3 B3 D4
+  };
+  const PROG_BUILD = ["Am", "F"];           // bars 16–23: gentle sway
+  const PROG_DROP = ["Am", "F", "C", "G"];  // drops: the full turn
+  for (let bar = 16; bar < 64; bar += 2) {
+    if (BREAK(bar)) continue; // the swells own the breakdown
+    const drop = DROP(bar);
+    if (!drop && bar >= 24) continue;
+    const prog = drop ? PROG_DROP : PROG_BUILD;
+    const chord = VOICED[prog[Math.floor((bar - (drop ? 24 : 16)) / 2) % prog.length]];
+    chord.forEach((f, i) =>
+      note(`harmPad${i}`, t(bar), { freq: f, peakDb: drop ? 16 : 13, q: 26, atk: 0.5, hold: 2 * BAR - 1.3, rel: 0.8, group: 1 }));
+    note("harmHi", t(bar), { freq: chord[2] * 2, peakDb: drop ? 12 : 9, q: 30, atk: 0.6, hold: 2 * BAR - 1.4, rel: 0.8, group: 1 });
+  }
+}
+
+// the NEVER-SILENT floor — veil (mids) + drone (low) + air (high), as
+// 8-BAR events: per-bar bed events left a mono-cut hole at every bar
+// line (the loudness curve notched −35 dB at each seam, 70 times). With
+// 8-bar spans the only seams sit on crash-marked section starts.
+for (const [a, z] of [[0, 8], [8, 16], [16, 24], [24, 32], [32, 40], [40, 48], [48, 56], [56, 64], [64, 70]]) {
+  const dropSect = DROP(a);
+  const span = (z - a) * BAR;
+  note("veil", t(a), { freq: 900, peakDb: dropSect ? 7 : 6.5, q: 0.5, atk: 0.3, hold: span - 0.3, rel: 0.6 });
+  note("drone", t(a), { freq: 110, peakDb: a >= 8 ? 13 : 11, q: 12, atk: 0.4, hold: span - 0.4, rel: 0.6 });
+  note("air", t(a), { freq: 13000, peakDb: dropSect ? 6 : 4.5, q: 1.0, atk: 0.5, hold: span - 0.5, rel: 0.5 });
+}
+
+// ── audit the budget ──────────────────────────────────────────────────
+if (lanes.size > MAX_POINTS)
+  throw new Error(`${lanes.size} EQ points exceeds the ${MAX_POINTS}-point budget`);
+console.log(`→ teknull · ${TOTAL_BARS} bars · A minor @ ${BPM} BPM · ${lanes.size}/${MAX_POINTS} EQ points`);
+
+// ── bake the score for the C engine ───────────────────────────────────
+const bands = [...lanes.values()];
+for (const b of bands) b.events.sort((x, y) => x.t0 - y.t0);
+
+// loudness ride: techno wants a firm floor — flat-ish targets, dip for
+// the breakdown, lift for the drops
+const rideTarget = (bar) => {
+  if (BREAK(bar)) return -17.5;
+  if (DROP(bar)) return -16.6;
+  if (OUTRO(bar)) return -19;
+  if (bar >= 16) return -18;
+  if (bar >= 8) return -18.5;
+  return -19.5;
+};
+const RIDE_BARS = 68; // leave the final boom + veil tail alone
+
+const L = [];
+L.push(`sr ${SR}`, `dur ${totalSec}`, `detune 1.0009 0.9991`, `seed ${0xAC1D} ${0x303}`);
+L.push(`normpeak 0.9`, `fadein 0.004`, `fadeout 1.2`);
+L.push(`ridewin ${BAR} ${RIDE_BARS}`);
+for (let b = 0; b < RIDE_BARS; b++) L.push(String(rideTarget(b)));
+for (const g of [0, 1]) {
+  const groupBands = bands.filter((b) => (b.group ?? 0) === g);
+  if (!groupBands.length) continue;
+  if (g > 0) L.push(`group ${0x7E77 + g} ${0x9A11 + g}`); // fresh noise pair per group
+  for (const band of groupBands) {
+    L.push(`band ${band.events.length}`);
+    for (const e of band.events)
+      L.push([e.t0, e.freq, e.freqEnd, e.peakDb, e.q, e.atk, e.hold, e.rel, e.cut].join(" "));
+  }
+}
+const OUT_DIR = resolve(HERE, "..", "out");
+mkdirSync(OUT_DIR, { recursive: true });
+const scorePath = resolve(OUT_DIR, "teknull.score.txt");
+writeFileSync(scorePath, L.join("\n") + "\n");
+console.log(`✓ baked ${bands.length} bands → ${scorePath}`);
+if (process.argv.includes("--bake-only")) process.exit(0);
+
+// ── render through the C engine + techno master ───────────────────────
+const _argi = (k) => { const i = process.argv.indexOf(k); return i >= 0 ? process.argv[i + 1] : null; };
+const outPath = _argi("--out") || resolve(OUT_DIR, "teknull.mp3");
+const r = spawnSync("node", [resolve(HERE, "../../nullabye/c/run-c.mjs"),
+  scorePath, "--out", outPath, "--master", "techno"], { stdio: "inherit" });
+process.exit(r.status ?? 1);
diff --git a/pop/teknull/teknull.illy.txt b/pop/teknull/teknull.illy.txt
new file mode 100644
index 000000000..ad267e881
--- /dev/null
+++ b/pop/teknull/teknull.illy.txt
@@ -0,0 +1,58 @@
+teknull — album cover. the sound is carved out of noise: lowpoly
+jeffrey alone at a wall of equalizers in a dark warehouse, pulling
+music out of static.
+
+an aggressively LOWPOLY 3D render, square — a videogame character
+screenshot, PS1/N64-era polygon budget rendered with modern moody
+lighting. EVERYTHING is triangles: the man is maybe 800 polygons
+total. his FACE is large flat triangles — an angular wedge nose,
+faceted cheekbones and jaw, flat-shaded skin with NO texture, NO
+pores, NO smooth gradients across the face. his hair is a chunky
+angular polygon shell, not strands. hands are blocky mitts of a few
+facets. clothes are stiff faceted shells with hard creases. the gear,
+floor, walls, fog — all visibly triangulated, flat-shaded per facet,
+hard polygon edges catching the light. NO photorealism anywhere, NO
+smooth organic surfaces, NO subsurface skin, NO fabric weave — if any
+part looks like a photograph, it is WRONG. crisp throughout, no
+motion blur.
+
+the lowpoly man is built FROM the man in the reference photos — the
+polygon head still reads as him: about 30, medium-length brown
+tousled hair as angular clumps, his soft red plastic glasses on
+(chunky lowpoly frames). his clothing is the faceted lowpoly version
+of the ACTUAL clothing in the reference photos — same colors, same
+garments, do not invent new ones. never a tank top, never a costume.
+he stands side-on at a tall rack of audio hardware, one arm reaching
+out, a blocky fingertip pushing up a single slider. his eyes are
+nearly-closed polygon slits, head dipped in a slow nod — locked into
+the groove, feeling it, not performing.
+
+the rack: stacked lowpoly rack units of old analog outboard gear —
+graphic equalizers with rows of tiny rectangular sliders, a patch bay
+with a few dangling faceted cables, vented panels. the slider caps and
+tiny LED meters glow warm red and amber — small emissive polygons, not
+screens. a handful of sliders on the main EQ are pushed up into a
+jagged little skyline; the rest sit flat. every brand plate is a blank
+worn rectangle — NO readable wordmarks, NO logos, NO text anywhere.
+there are NO screens in the scene — no monitors, no phones, no
+laptops anywhere at all.
+
+light: DAYGLO — the whole scene blazes in fluorescent blacklight-party
+color, MUCH more light than a club photo, bright like a poster. the
+palette is highlighter colors: hot fluorescent PINK, ACID GREEN,
+electric ORANGE, ultraviolet PURPLE, highlighter YELLOW — fully
+saturated, glowing like they're under UV. a hot pink work lamp
+clamped to the rack frame blasts across his faceted face, acid-green
+and highlighter-orange LED polygons blaze in rows along every rack
+unit, UV tubes wash the brick wall violet, and strings of bulbs burn
+across the ceiling. a sharp acid-green rim light carves his back and
+hair. the lowpoly fog — flat angular fog planes — floods the floor
+GLOWING hot pink and orange like a lightbox. the faceted floor
+bounces fluorescent color back up onto everything. NO darkness
+anywhere — shadows are saturated purple and magenta, never black,
+never grey; the entire frame is lit, every facet edge burning with
+color. high exposure, poster-bright.
+
+mood: peak-hour dayglo rave, hypnotic, joyful — one lowpoly person
+and a wall of fluorescent burning machines, carving a track out of
+noise while the whole room glows like a highlighter.
diff --git a/portraits/jeffrey/bin/IG-ARCHIVE-MIRROR.md b/portraits/jeffrey/bin/IG-ARCHIVE-MIRROR.md
new file mode 100644
index 000000000..1be60c0f7
--- /dev/null
+++ b/portraits/jeffrey/bin/IG-ARCHIVE-MIRROR.md
@@ -0,0 +1,85 @@
+# Archiving the @whistlegraph grid via iPhone Mirroring
+
+The only path that **actually changes grid visibility** AND can't be flagged as a
+bot: drive the **real Instagram app on the real iPhone** through macOS iPhone
+Mirroring. (IG web has no Archive in its menu; the Graph API has no archive
+endpoint; the private-API route got `login_required` and twitched the account.
+See memory `whistlegraph-grid-pruning`.)
+
+Per-post **Archive** (the "⋯" menu on an opened post) is the action that removes a
+post from the grid into your private Archive — reversible, engagement preserved.
+
+## Pieces
+
+- **`toolchain/macos/iphone-tap`** — eyes+hands CLI (`shot`/`ocr`/`tap`). Build it
+  first; see its README for permissions and the black-capture fallback.
+- **`bin/ig-archive-mirror.mjs`** — the orchestrator. Walks the profile feed,
+  classifies each post, archives photos/carousels, **skips reels**, logs + resumes.
+
+## What it protects
+
+- **All reels/videos** — `345` video posts excluded from the plan, plus an
+  on-screen reel guard (OCR hints: "views"/"plays"/"original audio"; vision
+  fallback). Keep all reels = honored.
+- **The oldest "Hi!" post** (`sDmBX0ir5u`, 2014) and any `--keep=<shortcode>`.
+- **Resume**: shortcodes already in `curated/whistlegraph-archived.jsonl` are skipped.
+
+Plan today: **2,415** photos+carousels eligible, out of 2,761 grid posts.
+
+## Vision key (recommended)
+
+The reel guard and control-finding fall back to OpenAI vision when OCR is unsure.
+Export a key first (from the vault `.env`):
+
+```bash
+export OPENAI_API_KEY=...   # without it: OCR-only, weaker reel detection
+```
+
+## 5pm calibration checklist (do this live, once)
+
+1. **Connect + mirror the phone.** Open **iPhone Mirroring**, unlock, leave it
+   foreground. Build the CLI: `toolchain/macos/iphone-tap/build.sh`.
+2. **Prove capture isn't black:**
+   ```bash
+   node portraits/jeffrey/bin/ig-archive-mirror.mjs --calibrate
+   open /tmp/ig-mirror-shot.png
+   ```
+   - Real screenshot + OCR lines listed → good.
+   - Blank/black → start a QuickTime Movie Recording of the phone and switch the
+     read window (see iphone-tap README). Re-run `--calibrate`.
+3. **Tune `COORDS`** at the top of `ig-archive-mirror.mjs` if needed: open a post
+   in the app, run `--calibrate`, eyeball `/tmp/ig-mirror-shot.png`, and adjust
+   `moreOptions` (the ⋯), `nextPost` (advance), `back`. (With a vision key, ⋯ and
+   Archive are found automatically — coords are just the fallback.)
+4. **One live post, watched:**
+   ```bash
+   # open the post you want to start from in the IG app, then:
+   node portraits/jeffrey/bin/ig-archive-mirror.mjs --live --limit=1
+   ```
+   Confirm it opened ⋯ → tapped Archive → the post left the grid.
+5. **Then small batches**, paced, watching the first few:
+   ```bash
+   node portraits/jeffrey/bin/ig-archive-mirror.mjs --live --limit=50
+   ```
+   Default pace 4–9s/post; raise `--min-delay`/`--max-delay` if anything feels hot.
+   It hard-stops on a login/challenge wall, a blank capture, or 3 consecutive
+   misses. Re-run to resume.
+
+## Flags
+
+```
+--live              actually archive (default = dry-run plan)
+--calibrate         dump a labelled shot+ocr to tune coords
+--limit=N           stop after N archives
+--keep=<shortcode>  extra post to never archive
+--min-delay / --max-delay   seconds between posts (default 4 / 9)
+--model=<id>        vision model (default gpt-4o-mini)
+--no-vision         OCR-only, skip OpenAI fallback
+```
+
+## Safety notes
+
+- Watch the first batch. This taps a live account; pace conservatively.
+- Dry-run prints exactly what it *would* tap (control + source: ocr/vision/coord).
+- Local backup is intact (`whistlegraph-grid.json` + downloaded originals), so
+  archived posts remain recoverable independent of Instagram.
diff --git a/portraits/jeffrey/bin/ig-archive-loop.sh b/portraits/jeffrey/bin/ig-archive-loop.sh
new file mode 100755
index 000000000..943782b1d
--- /dev/null
+++ b/portraits/jeffrey/bin/ig-archive-loop.sh
@@ -0,0 +1,44 @@
+#!/bin/bash
+# Auto-resuming wrapper for the sight-gated archiver.
+# On a TRANSIENT halt (auto-advance flashed a reel/loading frame) it re-launches
+# if we're still on a valid @whistlegraph post/grid. It STOPS for a paused/locked
+# connection (needs the Mac password) or if we've drifted off-account.
+cd /Users/jas/aesthetic-computer || exit 1
+TAP=toolchain/macos/iphone-tap/iphone-tap
+LOG=portraits/jeffrey/curated/whistlegraph-archived.jsonl
+
+classify() {
+  "$TAP" shot /tmp/wrap.png >/dev/null 2>&1 || { echo nowindow; return; }
+  "$TAP" ocr /tmp/wrap.png 2>&1 | python3 -c '
+import json, sys, re
+d = json.load(sys.stdin); ls = d.get("lines", [])
+t = " ".join(l["text"] for l in ls).lower()
+if "resume" in t or "connection paused" in t or "connection interrupted" in t: print("paused"); sys.exit()
+if "enter the mac login" in t or "is locked" in t: print("locked"); sys.exit()
+post = any(l["text"].strip() == "Posts" and abs(l["x"] + l["w"]/2 - 0.5) < 0.12 and l["y"] + l["h"]/2 < 0.17 for l in ls)
+grid = ("followers" in t and "following" in t) or (re.search(r"\breels\b", t) and re.search(r"\btagged\b", t))
+acct = "whistlegraph" in t
+print("ok" if (post or grid) and acct else ("transient" if acct else "offaccount"))
+'
+}
+
+stuck=0
+for run in $(seq 1 40); do
+  before=$(grep -c '' "$LOG")
+  echo "=== wrapper run $run ==="
+  node portraits/jeffrey/bin/ig-archive-mirror.mjs --live --limit=400 --min-delay=0.6 --max-delay=1.3
+  sleep 2
+  after=$(grep -c '' "$LOG")
+  st=$(classify)
+  echo "[wrapper] post-run state: $st  (cumulative: $after)"
+  # No-progress guard: if two runs in a row archive nothing, we're stuck on one
+  # post — stop rather than spin.
+  if [ "$after" -le "$before" ]; then stuck=$((stuck+1)); else stuck=0; fi
+  if [ "$stuck" -ge 2 ]; then echo "[wrapper] no progress for 2 runs — stuck on a post, stopping."; break; fi
+  case "$st" in
+    ok|transient) sleep 2 ;;
+    paused|locked) echo "[wrapper] NEEDS HUMAN ($st) — stopping."; break ;;
+    *) echo "[wrapper] off-account/unknown ($st) — stopping for safety."; break ;;
+  esac
+done
+echo "[wrapper] done. cumulative log: $(grep -c '' "$LOG")"
diff --git a/portraits/jeffrey/bin/ig-archive-mirror.mjs b/portraits/jeffrey/bin/ig-archive-mirror.mjs
new file mode 100755
index 000000000..00eb1ce2e
--- /dev/null
+++ b/portraits/jeffrey/bin/ig-archive-mirror.mjs
@@ -0,0 +1,598 @@
+#!/usr/bin/env node
+// ig-archive-mirror.mjs
+//
+// Archive @whistlegraph grid posts by driving the REAL Instagram app on the
+// REAL iPhone through macOS "iPhone Mirroring" — the only path that changes
+// grid visibility AND can't be flagged as a bot, because it literally is the
+// app on the device. (IG's web/API and private-API archiving were both dead
+// ends — see memory: whistlegraph-grid-pruning.)
+//
+// Eyes + hands come from the iphone-tap CLI (toolchain/macos/iphone-tap):
+//   shot → PNG of the mirror window,  ocr → text+boxes,  tap FX FY → a tap.
+// Targeting is HYBRID: on-device OCR first (fast/free), Claude vision as a
+// fallback when OCR can't confidently find the control.
+//
+// Per post the loop walks the profile feed:
+//   shot+read → classify (reel/keep? → skip) → tap "⋯" → find "Archive" →
+//   tap → verify → log → pace → next.
+//
+// ── Usage ────────────────────────────────────────────────────────────
+//   node bin/ig-archive-mirror.mjs                 # DRY-RUN (reads + plans, no taps that mutate)
+//   node bin/ig-archive-mirror.mjs --live          # actually archive
+//   node bin/ig-archive-mirror.mjs --live --limit=1   # one post (the 5pm smoke test)
+//   node bin/ig-archive-mirror.mjs --calibrate     # interactive: dump shot+ocr so you can tune COORDS
+//
+// Resume is automatic (skips shortcodes already in *-archived.jsonl). Always
+// preserves reels, the protected oldest post, and any --keep shortcode.
+
+import { readFileSync, existsSync, appendFileSync, mkdirSync, writeFileSync } from "fs";
+import { join, dirname } from "path";
+import { execFileSync } from "child_process";
+
+// ── args ─────────────────────────────────────────────────────────────
+const args = process.argv.slice(2);
+const has = (n) => args.includes(n);
+const val = (n) => {
+  const a = args.find((x) => x.startsWith(n + "="));
+  return a ? a.slice(n.length + 1) : null;
+};
+
+const ACCOUNT = val("--account") || "whistlegraph";
+const LIVE = has("--live");
+const CALIBRATE = has("--calibrate");
+const LIMIT = val("--limit") ? parseInt(val("--limit"), 10) : Infinity;
+const MIN_DELAY = val("--min-delay") ? parseFloat(val("--min-delay")) : 4; // seconds
+const MAX_DELAY = val("--max-delay") ? parseFloat(val("--max-delay")) : 9;
+const KEEP = val("--keep"); // extra shortcode to never archive
+const VISION_MODEL = val("--model") || "gpt-4o-mini"; // OpenAI vision
+const NO_VISION = has("--no-vision"); // OCR-only
+
+// ── paths ────────────────────────────────────────────────────────────
+const HERE = new URL(".", import.meta.url).pathname;
+const REPO = join(HERE, "..", "..", "..");
+const TAP = join(REPO, "toolchain/macos/iphone-tap/iphone-tap");
+const CURATED = join(REPO, "portraits/jeffrey/curated");
+const indexPath = join(CURATED, `${ACCOUNT}-grid.json`);
+const archivedPath = join(CURATED, `${ACCOUNT}-archived.jsonl`);
+const failedPath = join(CURATED, `${ACCOUNT}-archive-mirror-failed.jsonl`);
+const SHOT = "/tmp/ig-mirror-shot.png";
+
+// ── coords, calibrated live 2026-06-15 against the real app ────────────
+// Controls are LOCATED BY OCR every time — the ⋯ menu's contents and their
+// positions shift per post type (a reel's sheet ≠ a photo's; an already-removed
+// post shows "Pin to main grid" where "Remove from grid" was). These are only
+// fallbacks / anchors. Run --calibrate to re-tune if Instagram's layout moves.
+const COORDS = {
+  firstPost: [0.17, 0.63], // top-left grid thumbnail when scrolled to the very top
+  back: [0.07, 0.124], // back arrow (top-left, on the "Posts" title row) → grid. x=0.07 not 0.05 (edge misses)
+  profileTab: [0.90, 0.965], // profile avatar in the bottom nav — return-to-grid fallback
+};
+
+// The ⋯ glyph isn't OCR-readable, but it sits on the SAME ROW as the author
+// name, hard right. So we find the author row by OCR (account name, left-
+// aligned) and tap [0.93, thatRowY]. Robust across the audio-row / no-audio
+// layouts that shift the ⋯ up and down.
+const MORE_X = 0.93;
+const MORE_Y_FALLBACK = 0.185;
+
+// Per-post action (confirmed with @jeffrey 2026-06-15):
+//   reel/video → "Remove from grid"  (stays in the Reels tab, just off the grid)
+//   photo/carousel → "Archive"       (hidden from everyone, reversible)
+// Overridable: --archive-all or --remove-all force one action for every post.
+const FORCE = has("--archive-all") ? "archive" : has("--remove-all") ? "remove" : null;
+
+// ── preflight ─────────────────────────────────────────────────────────
+if (!existsSync(TAP)) {
+  console.error(`✗ iphone-tap not built. Run: toolchain/macos/iphone-tap/build.sh`);
+  process.exit(1);
+}
+if (!existsSync(indexPath)) {
+  console.error(`✗ missing ${indexPath} — run bin/ig-grid-index.mjs first`);
+  process.exit(1);
+}
+const index = JSON.parse(readFileSync(indexPath, "utf8"));
+const keepShortcode = KEEP || index.first_post.shortcode;
+
+const done = new Set();
+if (existsSync(archivedPath)) {
+  for (const l of readFileSync(archivedPath, "utf8").split("\n").filter(Boolean)) {
+    try { done.add(JSON.parse(l).shortcode); } catch {}
+  }
+}
+
+// Every grid post is in scope now (reels get "Remove from grid", photos get
+// "Archive"). The queue is a planning count; the live walk reads each post's
+// type on screen. Keep the protected oldest post and any --keep.
+const queue = index.posts.filter(
+  (p) => p.shortcode !== keepShortcode && !done.has(p.shortcode),
+);
+const videoCount = index.posts.filter((p) => p.is_video).length;
+const photoCount = index.posts.length - videoCount;
+
+// OpenAI key: env first, else the vault devcontainer env (same source the
+// recap scripts use) so the run works without an explicit export.
+function resolveOpenAIKey() {
+  if (process.env.OPENAI_API_KEY) return process.env.OPENAI_API_KEY;
+  const vault = join(REPO, "aesthetic-computer-vault/.devcontainer/envs/devcontainer.env");
+  try {
+    for (const line of readFileSync(vault, "utf8").split("\n")) {
+      if (line.startsWith("OPENAI_API_KEY=")) {
+        return line.slice("OPENAI_API_KEY=".length).trim().replace(/^['"]|['"]$/g, "");
+      }
+    }
+  } catch {}
+  return "";
+}
+const VISION_KEY = resolveOpenAIKey();
+
+const actionLabel = FORCE === "archive" ? "ALL → Archive"
+  : FORCE === "remove" ? "ALL → Remove from grid"
+  : "reels → Remove from grid · photos → Archive";
+
+console.log("══ ig-grid-prune (mirror) ══");
+console.log(`  account:        @${ACCOUNT}`);
+console.log(`  total grid:     ${index.posts.length} (${photoCount} photo/carousel, ${videoCount} reel/video)`);
+console.log(`  action:         ${actionLabel}`);
+console.log(`  keep visible:   ${keepShortcode} (${index.first_post.date})`);
+console.log(`  already done:   ${done.size}`);
+console.log(`  to process:     ${queue.length}`);
+console.log(`  pace:           ${MIN_DELAY}–${MAX_DELAY}s/post (jittered)`);
+console.log(`  targeting:      OCR${NO_VISION ? " only" : ` + ${VISION_MODEL} fallback`}`);
+console.log(`  vision key:     ${VISION_KEY ? "present" : "MISSING (OCR-only)"}`);
+console.log(`  mode:           ${CALIBRATE ? "CALIBRATE" : LIVE ? "LIVE (will modify the grid)" : "DRY-RUN"}`);
+console.log(`  limit:          ${LIMIT === Infinity ? "none" : LIMIT}`);
+console.log("");
+
+// ── primitives over iphone-tap ─────────────────────────────────────────
+const sleep = (ms) => new Promise((r) => setTimeout(r, ms));
+const jitter = () => (MIN_DELAY + Math.random() * (MAX_DELAY - MIN_DELAY)) * 1000;
+
+function tapcli(...a) {
+  try {
+    return JSON.parse(execFileSync(TAP, a, { encoding: "utf8" }));
+  } catch (e) {
+    const out = e.stdout?.toString() || "";
+    try { return JSON.parse(out); } catch { return { error: e.message }; }
+  }
+}
+
+function frame() { return tapcli("frame"); }
+function shot() { return tapcli("shot", SHOT); }
+function ocr() { return tapcli("ocr", SHOT); }
+async function tap(fx, fy) {
+  const r = tapcli("tap", String(fx), String(fy));
+  await sleep(280);
+  return r;
+}
+
+// Read the current screen once: returns { lines:[{text,x,y,w,h,conf}] } or null.
+function read() {
+  const s = shot();
+  if (s.error) return { error: s.error };
+  const o = ocr();
+  if (o.error) return { error: o.error };
+  // Detect the dreaded all-black Continuity capture (OCR finds nothing AND the
+  // file is tiny/uniform) so the caller can switch to the QuickTime read path.
+  return { lines: o.lines, blank: o.lines.length === 0 };
+}
+
+// Find a control by visible text. Returns center fraction [fx,fy] or null.
+function findByText(lines, matcher) {
+  const hit = lines.find((l) => matcher(l.text));
+  if (!hit) return null;
+  return [hit.x + hit.w / 2, hit.y + hit.h / 2];
+}
+
+// LLM vision fallback: ask OpenAI where a control is, normalized [0,1].
+async function askVision(question) {
+  if (NO_VISION || !VISION_KEY) return null;
+  const b64 = readFileSync(SHOT).toString("base64");
+  const body = {
+    model: VISION_MODEL,
+    max_tokens: 200,
+    messages: [{
+      role: "user",
+      content: [
+        { type: "text", text:
+          `This is a screenshot of an iPhone running Instagram. ${question}\n` +
+          `Reply ONLY with compact JSON: {"found":true,"x":0.0,"y":0.0} where x,y are ` +
+          `the target's center as fractions (0..1) from the TOP-LEFT, or {"found":false} ` +
+          `if it isn't visible.` },
+        { type: "image_url", image_url: { url: `data:image/png;base64,${b64}` } },
+      ],
+    }],
+  };
+  try {
+    const res = await fetch("https://api.openai.com/v1/chat/completions", {
+      method: "POST",
+      headers: {
+        "content-type": "application/json",
+        authorization: `Bearer ${VISION_KEY}`,
+      },
+      body: JSON.stringify(body),
+    });
+    const j = await res.json();
+    const text = j.choices?.[0]?.message?.content || "";
+    const m = text.match(/\{[^}]*\}/);
+    if (!m) return null;
+    const parsed = JSON.parse(m[0]);
+    return parsed.found ? [parsed.x, parsed.y] : null;
+  } catch (e) {
+    console.log(`   ↳ vision error: ${e.message}`);
+    return null;
+  }
+}
+
+// Hybrid locate: OCR first, vision second.
+async function locate(lines, { ocrMatch, visionAsk }) {
+  if (ocrMatch) {
+    const p = findByText(lines, ocrMatch);
+    if (p) return { at: p, via: "ocr" };
+  }
+  if (visionAsk) {
+    const p = await askVision(visionAsk);
+    if (p) return { at: p, via: "vision" };
+  }
+  return null;
+}
+
+// Locate the ⋯ button. Its glyph isn't OCR-readable, but it sits on a post's
+// AUTHOR ROW, hard right. The trap: on the scrollable feed page, CAPTIONS also
+// start with the handle ("whistlegraph <caption…>") — so we must pick the SHORT
+// line (just the handle, optionally + a verified badge), NOT a long caption.
+// Search the whole left column (y up to 0.85) since the author row can sit
+// mid-screen between two stacked posts.
+function locateMore(lines) {
+  const acct = ACCOUNT.toLowerCase();
+  const leftCol = (l) => l.x + l.w / 2 < 0.45 && l.y + l.h / 2 > 0.05 && l.y + l.h / 2 < 0.85;
+  // Author row: a SHORT line starting with the handle (excludes long captions).
+  let row = lines
+    .filter((l) => leftCol(l) && l.text.trim().toLowerCase().startsWith(acct) &&
+      l.text.trim().length <= acct.length + 4)
+    .sort((a, b) => a.y - b.y)[0];
+  // Collab posts read "X and whistlegraph" — a short-ish contains line.
+  if (!row) row = lines
+    .filter((l) => leftCol(l) && l.text.toLowerCase().includes(acct) && l.text.trim().length <= 32)
+    .sort((a, b) => a.y - b.y)[0];
+  const y = row ? row.y + row.h / 2 : MORE_Y_FALLBACK;
+  return { at: [MORE_X, y], via: row ? "author-row" : "anchor" };
+}
+
+// The ⋯ sheet has NO "Cancel" — dismiss it by swiping it down off-screen.
+async function dismissSheet() {
+  tapcli("swipe", "0.5", "0.15", "0.5", "0.95", "--duration", "250");
+  await sleep(600);
+}
+
+// Is the ⋯ action sheet open? Match DISTINCTIVE menu-only PHRASES — multi-word
+// strings that never appear in a caption. (We deliberately do NOT use bare
+// "archive" here: post captions can contain the word "archive", which would
+// look like an open menu — that caused false "sheet still open" halts. OCR also
+// prepends row icons as glyphs, so substring-match, not exact-line.)
+const SHEET_ITEMS = /(remove from grid|pin to main grid|add to grid|hide (like count|likes|share count)|turn off (commenting|downloading|reuse)|adjust preview)/i;
+const sheetIsOpen = (lines) => lines.some((l) => SHEET_ITEMS.test(l.text.trim()));
+// The Archive ROW is a SHORT line ("Archive", maybe an icon glyph) — distinct
+// from a caption that merely contains the word "archive".
+const isArchiveItem = (text) => /\barchive\b/i.test(text) && text.trim().length <= 14;
+
+// ── logging ────────────────────────────────────────────────────────────
+function record(path, row) {
+  mkdirSync(dirname(path), { recursive: true });
+  appendFileSync(path, JSON.stringify({ ...row, at: new Date().toISOString() }) + "\n");
+}
+const recordDone = (extra) => record(archivedPath, { via: "mirror", ...extra });
+const recordFail = (reason, extra = {}) => record(failedPath, { reason, ...extra });
+
+// ── calibrate mode: dump a labelled read so coords can be tuned ─────────
+if (CALIBRATE) {
+  const f = frame();
+  if (f.error) { console.log(`frame: ${f.error}`); process.exit(1); }
+  console.log(`window frame: ${JSON.stringify(f)}`);
+  const r = read();
+  if (r.error) { console.log(`read: ${r.error}`); process.exit(1); }
+  if (r.blank) {
+    console.log("⚠ capture is BLANK (Continuity privacy). Use the QuickTime read path:");
+    console.log("  open a QuickTime 'Movie Recording' of the phone and re-run with");
+    console.log("  --read-window calibration (see README).");
+  }
+  console.log(`saved shot → ${SHOT}`);
+  console.log(`OCR found ${r.lines?.length || 0} text lines:`);
+  for (const l of r.lines || []) {
+    console.log(`  "${l.text}"  center≈ [${(l.x + l.w / 2).toFixed(3)}, ${(l.y + l.h / 2).toFixed(3)}]`);
+  }
+  writeFileSync("/tmp/ig-mirror-ocr.json", JSON.stringify(r, null, 2));
+  console.log("full OCR → /tmp/ig-mirror-ocr.json");
+  console.log("\nopen the shot to eyeball coords:  open " + SHOT);
+  process.exit(0);
+}
+
+// ── act on the post currently open on screen ───────────────────────────
+// SAFETY: are we on @ACCOUNT's OWN content? Profile/post headers show the
+// account name CENTERED at the very top. If it's a different account, refuse to
+// act (Archive/Remove are owner-only anyway, but this stops wasted churn + the
+// wrong-account scare). Used to HALT the run if we ever drift off-account.
+// "whistlegraph" appearing anywhere in the TOP HEADER BAND (cy<0.18) means it's
+// whistlegraph's own post/grid (the header shows the profile owner there). Robust
+// to OCR merging the handle into an adjacent caption ("…it'd bwhistlegraph") and
+// to collab name-order ("X and whistlegraph"). A DIFFERENT account's page shows
+// THAT name in the band, not whistlegraph — so this still halts on drift.
+// Match a distinctive PREFIX of the handle in the header band — tolerant of OCR
+// errors in the tail ("whistlegraph" → "whistlegranh", ph→nh) and of glued
+// neighbours ("bwhistlegraph"). The prefix is long enough not to false-match
+// other accounts. (Full match also accepted.)
+const ACCT_LC = ACCOUNT.toLowerCase();
+const ACCT_PREFIX = ACCT_LC.slice(0, Math.min(ACCT_LC.length, 10)); // "whistlegra"
+const onAccount = (lines) =>
+  lines.some((l) => l.y + l.h / 2 < 0.18 &&
+    (l.text.toLowerCase().includes(ACCT_LC) || l.text.toLowerCase().includes(ACCT_PREFIX)));
+
+// Are we on the profile GRID? "followers"/"following" when scrolled up, OR the
+// Reels+Tagged tab pair (visible even scrolled down). The grid also has a
+// left-aligned "Posts" TAB — which must NOT be confused with a post's header.
+const onGridLines = (lines) =>
+  // The stats row has BOTH "followers" and "following"; requiring both avoids
+  // false-positives from a caption/comment that merely contains "following".
+  (lines.some((l) => /\bfollowers\b/i.test(l.text)) &&
+   lines.some((l) => /\bfollowing\b/i.test(l.text))) ||
+  // OCR often prefixes the tab icons ("D Reels", "9 Tagged") — match loosely.
+  (lines.some((l) => /\breels\b/i.test(l.text)) &&
+   lines.some((l) => /\btagged\b/i.test(l.text)));
+
+// Are we on a post-detail CARD? Its header reads "Posts" CENTERED at the very
+// top (cx≈0.5, cy<0.17) — distinct from the grid's left-aligned "Posts" tab.
+// A full-screen reel PLAYER has no such header → treated as fell-out → re-enter
+// via the grid, where reels open as cards we can act on.
+// A CENTERED "Posts" title at the very top is the definitive post-detail marker
+// (the grid's "Posts" is a LEFT-aligned tab at cx≈0.17). This is independent of
+// grid-word noise — a post caption can contain "followers"/"following"/"reels",
+// which must NOT flip it back to "grid".
+const onPost = (lines) =>
+  lines.some((l) => /^posts$/i.test(l.text.trim()) &&
+    Math.abs(l.x + l.w / 2 - 0.5) < 0.12 && l.y + l.h / 2 < 0.17);
+
+// A cheap fingerprint of the post on screen — the longest text line in the lower
+// half (caption / "Liked by …"). Used to tell whether an action advanced us to a
+// new post (archive auto-advances; remove/skip may leave the same post showing).
+function postSig(lines) {
+  const c = (lines || [])
+    .filter((l) => l.y + l.h / 2 > 0.62 && l.text.trim().length > 6)
+    .sort((a, b) => b.text.length - a.text.length);
+  return c[0]?.text.trim() || "";
+}
+
+// Advance to the next post within the Posts detail feed (swipe up = next).
+async function advanceToNextPost() {
+  tapcli("swipe", "0.5", "0.72", "0.5", "0.30", "--duration", "240");
+  await sleep(750);
+}
+
+// Two-tier (confirmed 2026-06-15): reel → "Remove from grid", photo → "Archive".
+// Controls are OCR-located fresh (the sheet's contents + positions vary per
+// post). Returns { status: "done"|"dry"|"skip"|"fail", action, type, via }.
+async function actOnCurrent() {
+  let r = read();
+  if (r.error) return { status: "fail", reason: r.error };
+  if (r.blank) return { status: "fail", reason: "blank_capture_use_quicktime" };
+  // Real login/challenge wall? Use word boundaries + specific phrases so post
+  // CAPTIONS don't false-trigger (e.g. "b[log in]to" matched bare /log in/).
+  // A real wall also has NO post header, so only flag it when NOT on a post.
+  if (!onPost(r.lines) && r.lines.some((l) =>
+    /(\blog in\b|\bsign up\b|couldn'?t refresh feed|confirm it'?s you|try again later|we restrict)/i.test(l.text)))
+    return { status: "fail", reason: "auth_or_challenge_wall" };
+
+  // Open the ⋯ sheet. The glyph isn't OCR-readable and its Y varies by layout
+  // (author row, location line) and scroll position, so TRY candidate Ys at the
+  // right edge until the sheet opens — primary is the located author row (the
+  // SHORT handle line). Header taps that miss are harmless.
+  const tryOpenMenu = async () => {
+    const cands = [];
+    const lm = locateMore(r.lines).at[1];
+    for (const y of [lm, 0.19, 0.143, 0.232]) if (!cands.includes(y)) cands.push(y);
+    for (const y of cands) {
+      await tap(MORE_X, y);
+      await sleep(450);
+      r = read();
+      if (!r.error && sheetIsOpen(r.lines)) return true;
+    }
+    return false;
+  };
+  let opened = await tryOpenMenu();
+  if (!opened) {
+    // The post is probably sitting scrolled so the ⋯/author row is above the
+    // viewport. Gently scroll UP a touch to reveal the header, then retry once.
+    // (Small + deliberate — not blind hunting.)
+    tapcli("scroll", "6"); await sleep(120); tapcli("scroll", "6"); await sleep(350);
+    r = read();
+    if (!r.error) opened = await tryOpenMenu();
+  }
+  if (!opened) {
+    // Genuinely no ⋯ menu (e.g. a collab post @whistlegraph doesn't own).
+    return { status: "skip", reason: "no_menu" };
+  }
+
+  // Decide from what the sheet offers. "Pin to main grid" is the pin option,
+  // present on normal on-grid posts — NOT an off-grid signal.
+  let hasRemove = r.lines.some((l) => /remove from grid/i.test(l.text));
+  let hasArchive = r.lines.some((l) => isArchiveItem(l.text));
+  // The sheet animates open top-down; a fast read can catch "Pin to main grid"
+  // (sheet-open passes) before "Archive"/"Remove" render → a false "off-grid"
+  // skip. If neither is seen yet, re-read once after it settles.
+  if (!hasRemove && !hasArchive) {
+    await sleep(450);
+    r = read();
+    if (!r.error) {
+      hasRemove = r.lines.some((l) => /remove from grid/i.test(l.text));
+      hasArchive = r.lines.some((l) => isArchiveItem(l.text));
+    }
+  }
+  const type = hasRemove ? "reel" : "photo"; // remove-from-grid ⟺ video/reel
+
+  let effAction = null;
+  if (FORCE === "remove") effAction = hasRemove ? "remove" : null;
+  else if (FORCE === "archive") effAction = hasArchive ? "archive" : null;
+  else if (hasRemove) effAction = "remove";  // reel/video → remove (keep in Reels tab)
+  else if (hasArchive) effAction = "archive"; // photo → archive
+
+  if (!effAction) {
+    // no Remove and no Archive = already off the grid / already archived.
+    await dismissSheet();
+    return { status: "skip", reason: "already_off_grid", type };
+  }
+
+  if (!LIVE) {
+    await dismissSheet();
+    console.log(`${type} → would ${effAction}`);
+    return { status: "dry", type };
+  }
+
+  const itemMatch = effAction === "remove"
+    ? (t) => /remove from grid/i.test(t)
+    : (t) => isArchiveItem(t); // SHORT "Archive" row, not a caption containing "archive"
+  const itemAsk = effAction === "remove"
+    ? "Where is the 'Remove from grid' item in this sheet?"
+    : "Where is the 'Archive' item in this sheet?";
+  const item = await locate(r.lines, { ocrMatch: (t) => itemMatch(t.trim()), visionAsk: itemAsk });
+  if (!item) {
+    await dismissSheet();
+    return { status: "fail", reason: `${effAction}_item_not_found`, type };
+  }
+  await tap(...item.at);
+  await sleep(500);
+
+  // verify — poll for the sheet to close (close animation + reload can take a
+  // moment; reads first so a fast close returns immediately). Up to ~3s.
+  let sheetGone = false;
+  for (let p = 0; p < 6 && !sheetGone; p++) {
+    r = read();
+    if (!r.error && !sheetIsOpen(r.lines)) { sheetGone = true; break; }
+    await sleep(500);
+  }
+  if (effAction === "remove") {
+    const toast = r.lines.some((l) => /removed from (the )?main grid/i.test(l.text));
+    if (toast) return { status: "done", action: effAction, type, via: item.via };
+    // toast can fade fast; sheet-gone is a soft confirm
+    return sheetGone
+      ? { status: "done", action: effAction, type, via: item.via, soft: true }
+      : { status: "fail", reason: "remove_not_confirmed", type };
+  }
+  // archive: success = the sheet (and usually the post) is gone
+  return sheetGone
+    ? { status: "done", action: effAction, type, via: item.via }
+    : { status: "fail", reason: "sheet_still_open_after_archive", type };
+}
+
+// ── feed walk (the fast path) ───────────────────────────────────────────
+// @jeffrey's tip 2026-06-15: after Archive the Posts detail view AUTO-ADVANCES
+// to the prior post — so we never go back to the grid. Open ONE post, then
+// ⋯ → act → (auto-advance) → repeat. Remove/skip/dry leave the same post, so a
+// signature check swipes to the next one. Eliminates the back+scroll+reopen that
+// dominated the old per-post time.
+const scrollToTop = async () => { for (let k = 0; k < 4; k++) { tapcli("scroll", "12"); await sleep(90); } await sleep(300); };
+const onGrid = onGridLines;
+
+// Surprise interstitial? IG pops an "Edits" App-Store promo card (recurs on app
+// open). It has no X — dismiss by tapping ABOVE the card. Detect by its text.
+const dismissPromoIfAny = async (lines) => {
+  if (lines?.some((l) => /level up|edits|app store/i.test(l.text))) {
+    await tap(0.5, 0.15); // tap outside (above the card)
+    await sleep(700);
+    return true;
+  }
+  return false;
+};
+
+console.log(`Sight-gated walk: acts ONLY when the top reads "Posts / ${ACCOUNT}".`);
+console.log("Rides the Archive auto-advance. NO blind swiping — halts the moment it can't confirm.\n");
+
+let archivedN = 0, removed = 0, skipped = 0, halted = "";
+const effLimit = (LIMIT === Infinity && !LIVE) ? 5 : LIMIT; // bounded dry-run preview
+
+for (let i = 0; archivedN + removed + skipped < effLimit; i++) {
+  const label = `#${i + 1}`;
+  let r = read();
+  if (!r.error && r.lines && (await dismissPromoIfAny(r.lines))) r = read();
+
+  // GATE 1: must be on a @ACCOUNT post detail ("Posts / <account>" at top).
+  // Auto-advance can briefly flash a loading/reel frame, so WAIT a few re-reads
+  // for it to settle on a valid post before deciding (wait-and-see, not swiping).
+  if (r.error || !r.lines || !onPost(r.lines) || !onAccount(r.lines)) {
+    for (let p = 0; p < 4 && (r.error || !r.lines || !(onPost(r.lines) && onAccount(r.lines))); p++) {
+      await sleep(700);
+      r = read();
+      if (!r.error && r.lines) await dismissPromoIfAny(r.lines) && (r = read());
+    }
+  }
+  if (r.error || !r.lines || !onPost(r.lines) || !onAccount(r.lines)) {
+    // The only allowed recovery is DELIBERATE: if on @ACCOUNT's own grid, open
+    // the top post. Anything else (wrong account, reel player, modal, lost
+    // feed) → HALT. Never blind-swipe to hunt for a post.
+    if (!r.error && r.lines && onGrid(r.lines) && onAccount(r.lines)) {
+      console.log(`[${label}] on @${ACCOUNT} grid → opening top post`);
+      await scrollToTop();
+      await tap(...COORDS.firstPost);
+      await sleep(1000);
+      continue;
+    }
+    halted = `top is not "Posts / ${ACCOUNT}" (wrong account / off-page) — not swiping`;
+    break;
+  }
+
+  const sigBefore = postSig(r.lines);
+  process.stdout.write(`[${label}] `);
+
+  // actOnCurrent opens ⋯ (confirms the menu opened) and acts (confirms the sheet
+  // is gone) — every tap is gated on seeing the expected control/state.
+  const res = await actOnCurrent();
+  if (res.status === "done") {
+    res.action === "remove" ? removed++ : archivedN++;
+    console.log(`✓ ${res.type} → ${res.action}${res.soft ? " (soft)" : ""}`);
+    recordDone({ action: res.action, type: res.type, index: i });
+
+    // GATE 2: confirm we're ready for the next post. An ARCHIVE hides the post,
+    // so the field ALWAYS auto-advances — just confirm we land back on a valid
+    // @ACCOUNT post (no signature check; two posts can share a caption line and
+    // collide, which was causing false halts). A REMOVE leaves the post on
+    // screen, so it needs a deliberate advance + a real signature change.
+    const validPost = (lines) => onPost(lines) && onAccount(lines);
+    const movedPost = (lines) => validPost(lines) && (!sigBefore || postSig(lines) !== sigBefore);
+    let onNew = false;
+    if (res.action === "archive") {
+      for (let p = 0; p < 7 && !onNew; p++) {        // read-first: instant advance returns at once
+        const r1 = read();
+        if (!r1.error && r1.lines && validPost(r1.lines)) { onNew = true; break; }
+        await sleep(450);
+      }
+    } else { // remove: post stays → wait for natural move, else one deliberate advance
+      for (let p = 0; p < 4 && !onNew; p++) {
+        await sleep(450);
+        const r1 = read();
+        if (!r1.error && r1.lines && movedPost(r1.lines)) onNew = true;
+      }
+      if (!onNew) {
+        await advanceToNextPost();
+        for (let p = 0; p < 3 && !onNew; p++) {
+          await sleep(450);
+          const r2 = read();
+          if (!r2.error && r2.lines && movedPost(r2.lines)) onNew = true;
+        }
+      }
+    }
+    if (!onNew) { halted = `couldn't confirm advance to the next @${ACCOUNT} post`; break; }
+  } else if (res.status === "skip") {
+    skipped++;
+    console.log(`• skip (${res.reason})`);
+    halted = `non-actionable post (${res.reason}) — stopping rather than swiping`;
+    break;
+  } else if (res.status === "dry") {
+    console.log("(dry)"); break;
+  } else {
+    console.log(`✗ ${res.reason}`);
+    recordFail(res.reason, { index: i });
+    halted = res.reason;
+    break;
+  }
+  await sleep(jitter());
+}
+
+console.log(`\n── done. archived ${archivedN}, removed ${removed}, skipped ${skipped}.${halted ? "  HALTED: " + halted : ""} ──`);
+console.log(`log: ${archivedPath}`);
diff --git a/portraits/jeffrey/bin/ig-archive-reels.mjs b/portraits/jeffrey/bin/ig-archive-reels.mjs
new file mode 100644
index 000000000..52cb27da9
--- /dev/null
+++ b/portraits/jeffrey/bin/ig-archive-reels.mjs
@@ -0,0 +1,184 @@
+#!/usr/bin/env node
+// ig-archive-reels.mjs
+//
+// Archive @whistlegraph REELS by driving the real IG app via iPhone Mirroring.
+// Companion to ig-archive-mirror.mjs (which does grid posts). Reels live in the
+// full-screen reel PLAYER, where the flow is different and more dangerous:
+//
+//   ⋯ [0.91,0.84]  →  "Manage"  →  "Archive"  →  confirm dialog "Archive"
+//      → "Archived" toast, auto-advances to the next reel.
+//
+// SAFETY: the reel right-rail has a REPOST button (~cy 0.62–0.72) that BROADCASTS
+// to followers. This script ONLY ever taps the ⋯ at the exact coord [0.91,0.84]
+// and menu items located by OCR — it NEVER taps elsewhere on the rail and NEVER
+// swipes near it. Account-guarded: acts only when "whistlegra" is on screen.
+//
+//   node bin/ig-archive-reels.mjs --live [--limit=N] [--min-delay --max-delay]
+// Start ON a @whistlegraph reel in the reel player. Default dry-run.
+
+import { existsSync, appendFileSync, mkdirSync } from "fs";
+import { join, dirname } from "path";
+import { execFileSync } from "child_process";
+
+const args = process.argv.slice(2);
+const has = (n) => args.includes(n);
+const val = (n) => { const a = args.find((x) => x.startsWith(n + "=")); return a ? a.slice(n.length + 1) : null; };
+
+const ACCOUNT = val("--account") || "whistlegraph";
+const ACCT_PREFIX = ACCOUNT.toLowerCase().slice(0, 10);
+const LIVE = has("--live");
+const LIMIT = val("--limit") ? parseInt(val("--limit"), 10) : Infinity;
+const MIN_DELAY = val("--min-delay") ? parseFloat(val("--min-delay")) : 1;
+const MAX_DELAY = val("--max-delay") ? parseFloat(val("--max-delay")) : 2;
+
+const HERE = new URL(".", import.meta.url).pathname;
+const REPO = join(HERE, "..", "..", "..");
+const TAP = join(REPO, "toolchain/macos/iphone-tap/iphone-tap");
+const archivedPath = join(REPO, "portraits/jeffrey/curated", `${ACCOUNT}-reels-archived.jsonl`);
+const SHOT = "/tmp/ig-reel-shot.png";
+
+// The ⋯ on the reel player. Its Y SHIFTS between reels (caption length, product
+// tags move the rail), so we try a few candidate Ys at the rail x and detect
+// which menu opened. We ONLY tap at x≈0.91 on these specific Ys — never the
+// repost zone (~0.62–0.72) — so we can't broadcast.
+const MORE_X = 0.91;
+const MORE_YS = [0.84, 0.88, 0.80, 0.86];
+
+if (!existsSync(TAP)) { console.error("✗ iphone-tap not built"); process.exit(1); }
+
+const sleep = (ms) => new Promise((r) => setTimeout(r, ms));
+const jitter = () => (MIN_DELAY + Math.random() * (MAX_DELAY - MIN_DELAY)) * 1000;
+
+function tapcli(...a) {
+  try { return JSON.parse(execFileSync(TAP, a, { encoding: "utf8" })); }
+  catch (e) { const o = e.stdout?.toString() || ""; try { return JSON.parse(o); } catch { return { error: e.message }; } }
+}
+const shot = () => tapcli("shot", SHOT);
+const ocr = () => tapcli("ocr", SHOT);
+async function tap(fx, fy) { const r = tapcli("tap", String(fx), String(fy)); await sleep(300); return r; }
+function read() { const s = shot(); if (s.error) return { error: s.error }; const o = ocr(); if (o.error) return { error: o.error }; return { lines: o.lines || [] }; }
+
+// Locate a menu item by text → center fraction, or null. `short` requires a
+// short line (so a caption containing the word doesn't match a menu row).
+function findItem(lines, re, { short = false } = {}) {
+  const hit = lines.find((l) => re.test(l.text) && (!short || l.text.trim().length <= 16));
+  return hit ? [hit.x + hit.w / 2, hit.y + hit.h / 2] : null;
+}
+const hasText = (lines, re) => lines.some((l) => re.test(l.text));
+// Account guard: handle appears (OCR-tolerant prefix) somewhere on screen.
+const onAccount = (lines) => lines.some((l) => l.text.toLowerCase().includes(ACCT_PREFIX));
+// Reel/media-detail markers (so we don't act on random screens). Broad on
+// purpose — some reels show "Add comment"/no view-count instead of the usual
+// markers. The real safety is downstream: openOptions + Manage→Archive only
+// succeed on an owned reel; anything else skips. Account guard also holds.
+const onReel = (lines) =>
+  hasText(lines, /views|plays|inspired on edits|original audio|· audio|add comment|view insights/i);
+
+function record(row) {
+  mkdirSync(dirname(archivedPath), { recursive: true });
+  appendFileSync(archivedPath, JSON.stringify({ ...row, at: new Date().toISOString() }) + "\n");
+}
+
+// Dismiss any open bottom-sheet/dialog SAFELY — tap the dimmed area ABOVE it
+// (never swipe near the rail). cy=0.25 is reliably in the dimmed zone.
+async function safeDismiss() { await tap(0.5, 0.25); await sleep(600); }
+
+// The ⋯ options menu (Save / Remix / Manage). NOT the share sheet.
+const isOptionsMenu = (lines) => hasText(lines, /\bmanage\b/i) ||
+  (hasText(lines, /\bremix\b/i) && hasText(lines, /\bsave\b/i));
+const isShareSheet = (lines) => hasText(lines, /add to story|copy link/i);
+
+// Open the ⋯ options menu, trying candidate Ys until the options menu (not the
+// share sheet) appears. Returns true if open. Dismisses any wrong sheet first.
+async function openOptions() {
+  for (const y of MORE_YS) {
+    await tap(MORE_X, y);
+    await sleep(700);
+    let r = read();
+    if (r.error) continue;
+    if (isOptionsMenu(r.lines)) return true;
+    if (isShareSheet(r.lines)) { await safeDismiss(); continue; } // wrong icon → retry lower/other
+    // some other state (e.g. nothing opened) — try next Y
+  }
+  return false;
+}
+
+// Archive the reel currently on screen. Returns status.
+async function archiveCurrentReel() {
+  let r = read();
+  if (r.error) return { status: "fail", reason: r.error };
+  // Patient checks — a freshly auto-advanced reel may still be loading, so the
+  // handle/markers haven't rendered yet. Re-read a few times before halting.
+  for (let p = 0; p < 4 && (r.error || !onReel(r.lines) || !onAccount(r.lines)); p++) {
+    await sleep(700);
+    r = read();
+  }
+  if (r.error || !onReel(r.lines)) return { status: "halt", reason: "not_on_reel_player" };
+  if (!onAccount(r.lines)) return { status: "halt", reason: "account_not_visible" };
+
+  if (!LIVE) return { status: "dry" };
+
+  // 1) open the ⋯ options menu (tries candidate Ys; handles the shifting rail)
+  if (!(await openOptions())) { await safeDismiss(); return { status: "skip", reason: "couldnt_open_options" }; }
+  r = read();
+  // 2) "Manage" (in the options sheet). A collab reel @whistlegraph doesn't own
+  // shows Report/etc. with NO Manage → can't archive → SKIP (advance), not halt.
+  const manage = findItem(r.lines, /^manage$|manage$/i, { short: true });
+  if (!manage) { await safeDismiss(); return { status: "skip", reason: "collab_or_unowned" }; }
+  await tap(...manage);
+  await sleep(700);
+  // 3) "Archive" in the Manage submenu (short line, not a caption with "archive")
+  r = read();
+  let arch = findItem(r.lines, /\barchive\b/i, { short: true });
+  if (!arch) { await sleep(500); r = read(); arch = findItem(r.lines, /\barchive\b/i, { short: true }); }
+  if (!arch) { await safeDismiss(); return { status: "halt", reason: "no_archive_item" }; }
+  await tap(...arch);
+  await sleep(900);
+  // 4) confirmation dialog → tap the "Archive" button (NOT "Cancel")
+  r = read();
+  const confirm = findItem(r.lines, /^archive$/i, { short: true });
+  if (!confirm) { await safeDismiss(); return { status: "fail", reason: "no_confirm_dialog" }; }
+  await tap(...confirm);
+  await sleep(1500);
+  // 5) verify: dialog gone (poll a little for the toast/advance)
+  for (let p = 0; p < 5; p++) {
+    r = read();
+    if (!r.error && !hasText(r.lines, /archive reel\?/i)) {
+      if (hasText(r.lines, /archived/i)) return { status: "done", via: "toast" };
+      return { status: "done", via: "dialog-gone" };
+    }
+    await sleep(600);
+  }
+  return { status: "fail", reason: "confirm_not_verified" };
+}
+
+console.log("══ ig-archive-reels ══");
+console.log(`  account: @${ACCOUNT}   mode: ${LIVE ? "LIVE" : "DRY-RUN"}   limit: ${LIMIT === Infinity ? "none" : LIMIT}`);
+console.log(`  pace: ${MIN_DELAY}–${MAX_DELAY}s/reel`);
+console.log("  Start ON a @whistlegraph reel. ⋯→Manage→Archive→confirm. Repost-safe (only taps ⋯ + OCR'd items).\n");
+
+let archived = 0, skipped = 0, halted = "";
+for (let i = 0; archived < (LIMIT === Infinity ? Infinity : LIMIT); i++) {
+  process.stdout.write(`[#${i + 1}] `);
+  const res = await archiveCurrentReel();
+  if (res.status === "done") {
+    archived++;
+    console.log(`✓ archived (${res.via})`);
+    record({ index: i });
+    await sleep(jitter()); // archive auto-advances to the next reel
+  } else if (res.status === "dry") {
+    console.log("(dry — would archive)"); break;
+  } else if (res.status === "skip") {
+    // A collab/unowned reel blocks the walk and the player won't advance
+    // programmatically → halt and ask @jeffrey to swipe past it by hand.
+    skipped++;
+    halted = `collab/unowned reel (${res.reason}) — SWIPE to the next reel, then re-run`;
+    console.log(`✋ ${halted}`); break;
+  } else if (res.status === "halt") {
+    halted = res.reason; console.log(`⛔ ${res.reason}`); break;
+  } else {
+    halted = res.reason; console.log(`✗ ${res.reason}`); break;
+  }
+}
+console.log(`\n── done. archived ${archived}.${halted ? "  HALTED: " + halted : ""} ──`);
+console.log(`log: ${archivedPath}`);
diff --git a/reports/js-tooling-audit.md b/reports/js-tooling-audit.md
new file mode 100644
index 000000000..4209d5b58
--- /dev/null
+++ b/reports/js-tooling-audit.md
@@ -0,0 +1,193 @@
+# JS/TS Code-Intelligence Tooling Audit — 2026-06-10
+
+Machine: MacBook (Apple Silicon), **8 GB RAM** — every recommendation below was
+filtered through "one process at a time, low resident memory."
+
+Target repos:
+- `/Users/jas/aesthetic-computer` — large JS/.mjs runtime, no TS (~8,600 .mjs files, 75 MB in `system/public/aesthetic.computer`)
+- `/Users/jas/Developer/fuser` — TypeScript 5.8.3 pnpm/turbo monorepo, 22 packages, ~5,900 .ts/.tsx files
+
+## 1. Inventory (before → after)
+
+| Tool | Before | After | Notes |
+|---|---|---|---|
+| ripgrep (rg) | 15.1.0 | — | already best-in-class baseline |
+| ugrep | "missing" on PATH | — | **Claude Code embeds it**: the agent-shell `grep` function execs the `claude` binary as `ARGV0=ugrep` (ugrep 7.5.0). So plain `grep` in agent shells is already smart. |
+| fd | missing | **10.4.2** | installed (brew) |
+| fzf | missing | **0.73.1** | installed (brew) — interactive, marginal for agents |
+| ast-grep (`ast-grep` / `sg`) | missing | **0.43.0** | installed (brew); binary is `ast-grep` (no `sg` symlink — `sg` is a Unix builtin name) |
+| comby | missing | not installed | superseded by ast-grep (not AST-aware, weak query logic) |
+| semgrep | missing | not installed | Python, slow startup, heavier RSS; overkill vs ast-grep for grokking |
+| universal-ctags | only BSD `/usr/bin/ctags` | **6.2.1** (brew, with `readtags`) | TS/TSX parser maintained upstream |
+| tree-sitter CLI | missing | not installed | ast-grep covers the use cases |
+| jq | 1.x present | — | fine |
+| gron | missing | not installed | jq suffices |
+| node / tsc | v22.22.2 / TS 6.0.3 global; fuser pins TS 5.8.3 | — | |
+| deno | 2.7.14 | — | |
+| bun | missing | not installed | no current need |
+| typescript-language-server | 5.1.3 (global) | — | used by the Claude Code typescript-lsp plugin |
+| vtsls | missing | **0.3.0** (npm -g `@vtsls/language-server`) | installed as an option; see proposals |
+| **tsgo** (`@typescript/native-preview`) | missing | **7.0.0-dev.20260610.1** (npm -g) | the headline install |
+| oxlint | missing | **1.69.0** (brew) | instant whole-package sanity linting |
+| biome | missing | not installed | oxlint is ~2x faster for lint-only; fuser keeps eslint as canonical |
+| eslint | repo-local only (fuser `node_modules/.bin/eslint`) | — | canonical but slow |
+| difftastic (difft) | missing | **0.69.0** (brew) | semantic diffs |
+| scip-typescript / scip | missing | **not installed — deliberately** | docs recommend `--max-old-space-size=16000`; a non-starter on 8 GB. ctags is the cheap index instead. |
+| Claude Code | 2.1.170 | — | LSP tool is built-in (shipped ~2.0.74, no env flag needed) |
+| Claude plugins | `typescript-lsp@claude-plugins-official` + `swift-lsp` installed & **enabled** | — | `.in_use` markers show live sessions using it |
+| MCP servers (`~/.claude.json`) | asana, chrome-devtools ×3, sketchup | — | no code-intel MCP servers |
+
+## 2. Research findings
+
+### Structural/AST search → **ast-grep wins**
+- Rust, multi-core, "tens of thousands of files in seconds"; semgrep is slow as a CLI; comby is not AST-aware and can't express logic (and/not/inside) — [ast-grep tool comparison](https://ast-grep.github.io/advanced/tool-comparison.html), [TS catalog](https://ast-grep.github.io/catalog/typescript/).
+- Measured here: 49 MB peak RSS scanning the whole AC public tree. Perfect 8 GB citizen.
+- Gotcha found in testing: `--lang ts` does **not** match `.tsx` files. Omit `--lang` and ast-grep infers per-file — that's the right default idiom.
+
+### Fast typechecking → **tsgo is real and a 7–40x win**
+- Native Go port of tsc, nightly `@typescript/native-preview`, becomes TypeScript 7; `--build`/project-references/`--incremental` ported; ~10x typical speedups, lower memory ([npm](https://www.npmjs.com/package/@typescript/native-preview), [typescript-go repo](https://github.com/microsoft/typescript-go), [announcement](https://devblogs.microsoft.com/typescript/announcing-typescript-native-previews/), [Dec 2025 progress](https://devblogs.microsoft.com/typescript/progress-on-typescript-7-december-2025/), [early-2026 release target](https://www.infoworld.com/article/4100582/microsoft-steers-native-port-of-typescript-to-early-2026-release.html)).
+- **Verified locally** (numbers in §3): 5.35 s vs 37.2 s on the same fuser package, similar RSS. The 8 GB swap-fest tsc typecheck becomes a coffee-sip.
+- **Blocker found:** tsgo (TS7) removed `baseUrl` → `error TS5102` and the check aborts. Most fuser packages (incl. `core`, `flow-types`, `flow`) set `baseUrl: "."`. Eight packages don't and check cleanly today. Fix is mechanical: replace `baseUrl` with `"paths": {"*": ["./*"]}` (or `"@/*": ["./*"]` where used) — that's a fuser-repo change to propose, not made here.
+
+### LSP for agents → **already wired; vtsls is the upgrade path**
+- Claude Code has built-in LSP support (changelog ~v2.0.74; no `ENABLE_LSP_TOOL` needed on 2.1.170) and this machine already has `typescript-lsp@claude-plugins-official` installed/enabled, backed by global `typescript-language-server` 5.1.3 ([plugin page](https://claude.com/plugins/typescript-lsp), [Scott Spence](https://scottspence.com/posts/enable-lsp-in-claude-code), [field report](https://alirezarezvani.medium.com/i-set-up-claude-code-lsp-for-a-200-file-typescript-codebase-heres-what-actually-happened-1dd84e85187d)).
+- vtsls (wraps the actual VS Code TS extension) is faster/more correct on big monorepos and is now Zed's default TS server ([vtsls](https://github.com/yioneko/vtsls), [helix issue](https://github.com/helix-editor/helix/issues/13032), [zed issue](https://github.com/zed-industries/zed/issues/18698)). Caveat for 8 GB: tsserver-family servers grow with project size (VS Code defaults the cap to 3 GB) — on fuser, prefer opening one package at a time, and lean on rg/ast-grep/ctags for repo-wide questions instead of repo-wide LSP.
+- Serena MCP ([oraios/serena](https://github.com/oraios/serena)) layers symbol-level navigation/edit tools over LSP; popular with Claude Code in 2026. On this machine it would run *another* Python process + a tsserver — redundant with the built-in LSP plugin. Verdict: skip unless doing heavy cross-file refactors, and never alongside a typecheck.
+
+### Symbol indexing → **universal-ctags yes, scip no**
+- universal-ctags has a maintained TS parser ([ctags repo](https://github.com/universal-ctags/ctags)); measured: full fuser index in 16.7 s / 36 MB RSS, lookups via `readtags` in <1 s / 1.4 MB.
+- scip-typescript runs the real TS compiler to index; upstream guidance includes `node --max-old-space-size=16000` and `--no-global-caches` to avoid OOM ([scip-typescript](https://github.com/sourcegraph/scip-typescript), [SCIP announcement](https://sourcegraph.com/blog/announcing-scip)). Wrong tool for 8 GB; precision delta over ctags+LSP isn't worth it here.
+
+### Fast linting as comprehension → **oxlint**
+- oxlint 50–100x faster than eslint, ~2x faster than biome; ~300 rules ([oxc benchmarks](https://oxc.rs/docs/guide/benchmarks), [bench-linter](https://github.com/oxc-project/bench-linter), [LogRocket](https://blog.logrocket.com/retire-eslint-migrate-oxlint/), [PkgPulse 2026 comparison](https://www.pkgpulse.com/guides/biome-vs-eslint-vs-oxlint-2026)). Use as a zero-config "is this package internally sane / what's dead code here" probe; the repo's eslint stays canonical for CI.
+- biome skipped: its formatter would fight prettier (AC) and fuser's eslint config.
+
+### New-in-2025/26 misc
+- **difftastic** — tree-sitter-based semantic diffs; installed, verified (§3). Memory scales with file size: 212 MB on the 16k-line `bios.mjs`, trivial on normal files. Use per-file, not `git difftool --dir-diff` on huge trees.
+- **Repomix/codebase-map context packers** — built for stuffing cloud-model contexts; for a local agent with rg/ast-grep/LSP they just burn tokens. Skip.
+- **GritQL** — overlaps ast-grep with a smaller community and stalled momentum; ast-grep's YAML rules + relational constraints cover the same ground. Skip.
+
+## 3. Benchmarks (wall clock + `/usr/bin/time -l` max RSS)
+
+| Query | Tool / scope | Time | Peak RSS |
+|---|---|---|---|
+| All `setTimeout($FN, $MS)` (311 hits) | ast-grep, whole AC public tree | 6.5 s | 49 MB |
+| `setTimeout` with delay > 5000 (inline YAML rule, 5 hits) | ast-grep, AC `lib/` | ~1 s | <50 MB |
+| Callers of `requestAppPreviewReload` | ast-grep, fuser `packages/flow/src` | 1.9 s | 16 MB |
+| Build full symbol index | ctags, fuser `packages/` (22 pkgs) | 16.7 s | 36 MB (5.9 MB tags file) |
+| Build full symbol index | ctags, AC public tree | 10.0 s | 36 MB (23 MB tags file) |
+| "Where is `executionData` defined?" | readtags on fuser index | 0.8 s | 1.4 MB → `packages/core/src/sanitizeUtils.ts` `interface SanitizableNodeDataShape` |
+| Typecheck `packages/app-node-protocol` | **tsgo** `--noEmit -p` | **5.4 s** | 119 MB |
+| Typecheck `packages/app-node-protocol` | tsc 5.8.3 `--noEmit -p` | **37.2 s** | 125 MB |
+| Typecheck `packages/flow-types` | tsc 5.8.3 | **256.8 s** (pulls Next.js types; machine contended) | 257 MB RSS / 880 MB footprint |
+| Typecheck `packages/flow-types` | tsgo | 6.4 s — **but aborts on `baseUrl` (TS5102)**, so not a completed check | 306 MB |
+| Lint AC `disks/` (~1,000 pieces) | oxlint | 2.6 s | 47 MB |
+| Lint fuser `packages/core/src` | oxlint | 1.4 s | 12 MB |
+| Semantic diff of dirty `bios.mjs` (16k lines) | difft | 9.1 s | 212 MB |
+| File find `-e mjs` pattern | fd, whole AC repo | 1.0 s | 13 MB |
+| tsgo error-detection sanity | bad `/tmp/bad.ts` | instant | exit 1, both TS2322 caught |
+
+Honest pairing: tsgo vs tsc on the *same clean package* = **6.9x faster, same memory**. The flow-types row shows the worst-case tsc behavior the 8 GB machine suffers (4+ min, ~900 MB footprint for a 41-file package, because the shared `nextjs.json` config drags in the Next type universe).
+
+## 4. Playbook — how agents should grok TS/JS on this machine
+
+**Golden rule: one heavy process at a time.** rg/fd/ast-grep/readtags/oxlint are all "free" (<50 MB). tsgo, difft-on-huge-files, and any tsserver are the heavies — never overlap them with ffmpeg/Chromium/whisper or each other.
+
+### Structural search (ast-grep)
+```bash
+# Callers of a function (omit --lang: it auto-infers per file, and
+# --lang ts does NOT match .tsx — easy silent miss)
+ast-grep run -p 'requestAppPreviewReload($$$ARGS)' packages/flow/src
+
+# Pattern with metavariable capture
+ast-grep run -p 'setTimeout($FN, $MS)' system/public/aesthetic.computer/lib
+
+# One-shot rule with constraints (e.g. numeric delay >= 5000)
+ast-grep scan --inline-rules '
+id: long-settimeout
+language: js
+rule: { pattern: "setTimeout($FN, $MS)" }
+constraints:
+  MS: { regex: "^([5-9][0-9]{3}|[0-9]{5,})$" }
+' system/public/aesthetic.computer/lib
+
+# Relational logic: awaits inside a loop
+ast-grep scan --inline-rules '
+id: await-in-loop
+language: ts
+rule:
+  pattern: "await $X"
+  inside: { kind: for_statement, stopBy: end }
+' packages/core/src
+
+# Rewrite preview (no file changes without --update-all / -U)
+ast-grep run -p 'console.log($$$A)' -r 'console.debug($$$A)' lib/
+```
+
+### Single-package typecheck (the big workflow change)
+```bash
+# fuser: tsgo on a package WITHOUT baseUrl — 5s instead of 37s
+tsgo --noEmit -p /Users/jas/Developer/fuser/packages/app-node-protocol
+
+# baseUrl-free today: app-node, app-node-protocol, canvas-runtime,
+# code-gen, flow-agents, flow-chats, harness, node-enrichment
+# Packages WITH baseUrl (core, flow, flow-types, …) abort with TS5102
+# until baseUrl → paths is landed in fuser; fall back to repo tsc:
+cd /Users/jas/Developer/fuser && node_modules/.bin/tsc --noEmit -p packages/<pkg>
+
+# Single-file sanity (no tsconfig needed):
+tsgo --noEmit path/to/file.ts
+```
+Never run tsgo/tsc `--build` across the whole fuser monorepo casually; per-package only, one at a time.
+
+### Symbol lookup (ctags index — rebuild is cheap, do it per session)
+```bash
+# Index (fuser: ~17s; AC: ~10s)
+ctags -R --languages=TypeScript,JavaScript \
+  --exclude=node_modules --exclude=dist --exclude=.next --exclude=.turbo \
+  -f /tmp/fuser.tags /Users/jas/Developer/fuser/packages
+ctags -R --languages=JavaScript --exclude=node_modules \
+  -f /tmp/ac.tags /Users/jas/aesthetic-computer/system/public/aesthetic.computer
+
+# Exact symbol → definition site + kind + owning interface/class
+readtags -t /tmp/fuser.tags -e executionData
+# Prefix search
+readtags -t /tmp/fuser.tags -e -p execution
+```
+
+### Whole-package sanity sweep
+```bash
+oxlint packages/core/src          # fuser, ~1.4s — unused vars/dead code map
+oxlint system/public/aesthetic.computer/disks   # AC, ~2.6s
+# eslint stays canonical for fuser CI; oxlint is the comprehension probe.
+```
+
+### Semantic diffs
+```bash
+difft --display inline /tmp/old.mjs current.mjs   # ignores formatting noise
+GIT_EXTERNAL_DIFF=difft git -C <repo> diff -- path/file.ts   # ad hoc, per-file
+# Caution: ~212 MB RSS on 16k-line files (bios.mjs/disk.mjs scale) — fine
+# solo, don't run while a typecheck is live.
+```
+
+### Fast file finding
+```bash
+fd -e mjs kidlisp /Users/jas/aesthetic-computer     # respects .gitignore
+fd --type f -e tsx AppNode /Users/jas/Developer/fuser/packages
+```
+
+### LSP (already on)
+The built-in Claude Code LSP tool + `typescript-lsp` plugin already serve
+go-to-definition / find-references / hover for `.ts/.tsx/.js/.mjs` in both
+repos. Use it for "what is this symbol exactly" questions; use rg/ast-grep/
+ctags for repo-wide enumeration (cheaper than forcing tsserver to load the
+whole monorepo into an 8 GB machine).
+
+## 5. Proposed Claude Code / repo config changes (NOT applied)
+
+1. **Switch the TS language server backing to vtsls** (installed: `@vtsls/language-server` 0.3.0). Either via a community vtsls plugin (e.g. the Piebald `claude-code-lsps` marketplace) or when the official plugin grows a server option. Faster/more correct completions on the fuser monorepo; keep typescript-language-server as fallback. Human applies — plugin config untouched.
+2. **fuser repo: replace `baseUrl` with `paths`** in `packages/*/tsconfig.json` (`"paths": {"*": ["./*"]}`; keep existing `@/*` mappings) so tsgo can check every package. This is also the TS7 migration path — needed eventually regardless. Coordinate with the agent working in fuser-genrecovery before touching shared config.
+3. **Optional fuser devDependency**: `@typescript/native-preview` pinned in the repo so `pnpm tsgo --noEmit -p packages/x` matches the repo TS version drift-free (global nightly works fine meanwhile).
+4. **Permissions allowlist** (project `.claude/settings.json`, via `/fewer-permission-prompts`): pre-allow `ast-grep run*`, `ast-grep scan*`, `readtags*`, `fd*`, `oxlint*`, `difft*`, `tsgo --noEmit*` as read-only-safe Bash patterns to cut prompt friction.
+5. **Do not add** Serena MCP or scip-typescript on this machine (memory rationale in §2). Revisit Serena if a 16 GB+ machine appears.
+6. **Tags freshness convention**: indexes live in `/tmp` (wiped on reboot) — agents should rebuild rather than trust a stale index; 10–17 s is cheap.
diff --git a/slab/bin/puppet-view.mjs b/slab/bin/puppet-view.mjs
new file mode 100755
index 000000000..c5c2718f9
--- /dev/null
+++ b/slab/bin/puppet-view.mjs
@@ -0,0 +1,116 @@
+#!/usr/bin/env node
+// puppet-view.mjs — live fleet viewer for puppet screencast frames.
+//
+// puppet `watch` keeps the latest JPEG per window at
+// ~/.local/share/puppet/frames/<name>.jpg (atomic rename). This serves:
+//   GET /            a dark grid page, one <img> per frame, all live
+//   GET /stream/<n>  multipart/x-mixed-replace MJPEG of that frame file
+//   GET /sheet.jpg   one-shot contact sheet of ALL frames (ffmpeg xstack,
+//                    ~30ms) — what a driving agent curls to see every window
+//
+// Push-based: fs.watch on the FRAMES DIR (file watchers chase the old inode
+// across renames; directory watchers see every landing). Chrome renders
+// MJPEG in <img> natively — sub-50ms from frame landing to glass.
+//
+//   node slab/bin/puppet-view.mjs [port]     # default 7777
+//   open http://localhost:7777
+//
+// PUBLIC repo: no machine names here — frame names come from whatever the
+// operator passes to `puppet watch`.
+
+import { execFile } from "node:child_process";
+import { readdirSync, readFileSync, watch, existsSync, mkdirSync } from "node:fs";
+import http from "node:http";
+import { homedir } from "node:os";
+import { join } from "node:path";
+
+const FRAMES_DIR = join(homedir(), ".local", "share", "puppet", "frames");
+mkdirSync(FRAMES_DIR, { recursive: true });
+const PORT = Number(process.argv[2] || 7777);
+
+const names = () =>
+  readdirSync(FRAMES_DIR)
+    .filter(f => f.endsWith(".jpg"))
+    .map(f => f.slice(0, -4));
+
+// Contact sheet: montage every current frame into one JPEG (benchmarked
+// ~30ms for 5×900w frames on an M-series). Grid is ~square; single frame
+// passes through untouched.
+function sheet(res) {
+  const files = names().map(n => join(FRAMES_DIR, n + ".jpg"));
+  if (!files.length) { res.writeHead(404); return res.end("no frames"); }
+  if (files.length === 1) {
+    res.writeHead(200, { "Content-Type": "image/jpeg", "Cache-Control": "no-store" });
+    return res.end(readFileSync(files[0]));
+  }
+  // frames arrive at whatever width each watch chose — normalize every tile
+  // (scale + pad to TW×TH) so xstack can use literal grid coordinates;
+  // heterogeneous inputs otherwise scramble the w0/h0-relative layout.
+  const TW = 640, TH = 400;
+  const cols = Math.ceil(Math.sqrt(files.length));
+  const norm = files
+    .map((_, i) =>
+      `[${i}:v]scale=${TW}:${TH}:force_original_aspect_ratio=decrease,` +
+      `pad=${TW}:${TH}:(ow-iw)/2:(oh-ih)/2:black[t${i}]`)
+    .join(";");
+  const layout = files.map((_, i) => `${(i % cols) * TW}_${Math.floor(i / cols) * TH}`).join("|");
+  const refs = files.map((_, i) => `[t${i}]`).join("");
+  execFile(
+    "ffmpeg",
+    ["-y", "-loglevel", "error", ...files.flatMap(f => ["-i", f]),
+     "-filter_complex", `${norm};${refs}xstack=inputs=${files.length}:layout=${layout}:fill=black`,
+     "-q:v", "6", "-f", "image2", "pipe:1"],
+    { encoding: "buffer", maxBuffer: 32 * 1024 * 1024 },
+    (err, stdout) => {
+      if (err) { res.writeHead(503); return res.end("ffmpeg failed: " + err.message); }
+      res.writeHead(200, { "Content-Type": "image/jpeg", "Cache-Control": "no-store" });
+      res.end(stdout);
+    },
+  );
+}
+
+http
+  .createServer((req, res) => {
+    if (req.url.startsWith("/sheet.jpg")) return sheet(res);
+    const m = req.url.match(/^\/stream\/([\w.-]+)/);
+    if (!m) {
+      const tiles = names()
+        .map(
+          n =>
+            `<figure style="margin:0"><figcaption style="color:#9a9;font:12px ui-monospace;padding:2px 6px">${n}</figcaption><img src="/stream/${n}" style="width:100%;display:block;border:1px solid #233"></figure>`,
+        )
+        .join("");
+      res.writeHead(200, { "Content-Type": "text/html" });
+      res.end(
+        `<!doctype html><title>puppet fleet</title><body style="background:#0b0f10;margin:0;padding:8px"><div style="display:grid;grid-template-columns:repeat(auto-fit,minmax(440px,1fr));gap:8px">${tiles || '<p style="color:#677">no frames yet — start one with: puppet watch &lt;machine&gt; ~/.local/share/puppet/frames/&lt;name&gt;.jpg --target=…</p>'}</div><script>setInterval(()=>{if(document.images.length===0)location.reload()},3000)</script>`,
+      );
+      return;
+    }
+    const file = join(FRAMES_DIR, m[1] + ".jpg");
+    if (!existsSync(file)) {
+      res.writeHead(404);
+      res.end("no such frame");
+      return;
+    }
+    res.writeHead(200, {
+      "Content-Type": "multipart/x-mixed-replace; boundary=F",
+      "Cache-Control": "no-store",
+    });
+    const send = () => {
+      try {
+        const b = readFileSync(file);
+        res.write(`--F\r\nContent-Type: image/jpeg\r\nContent-Length: ${b.length}\r\n\r\n`);
+        res.write(b);
+      } catch {}
+    };
+    send();
+    // debounce: each atomic rename fires two dir events; one part per frame
+    let timer = null;
+    const w = watch(FRAMES_DIR, (_, f) => {
+      if (f !== m[1] + ".jpg") return;
+      clearTimeout(timer);
+      timer = setTimeout(send, 10);
+    });
+    req.on("close", () => { clearTimeout(timer); w.close(); });
+  })
+  .listen(PORT, () => console.log(`puppet-view: http://localhost:${PORT} (frames: ${FRAMES_DIR})`));
diff --git a/slab/bin/puppet.mjs b/slab/bin/puppet.mjs
new file mode 100755
index 000000000..80503c00b
--- /dev/null
+++ b/slab/bin/puppet.mjs
@@ -0,0 +1,984 @@
+#!/usr/bin/env node
+// puppet.mjs — a persistent CDP multiplexer for driving browsers on many machines.
+//
+// One daemon on the controlling machine holds open Chrome DevTools Protocol
+// WebSockets to every registered browser (local or remote-over-tunnel), so a
+// command costs one LAN round-trip instead of a process spawn + fresh WS
+// handshake (~400ms → ~5ms). A thin CLI talks to the daemon over a unix
+// socket. Same spirit as a game server: persistent connections, broadcast,
+// live event streams.
+//
+// This file ships in the PUBLIC aesthetic.computer repo, so it carries NO
+// machine names or addresses: the machine registry lives in an UNTRACKED
+// config at ~/.config/slab/puppet.json (see `puppet config`).
+//
+//   puppet daemon                     run the daemon (foreground)
+//   puppet list                       machines, connection state, page targets
+//   puppet eval <machine> <js>        evaluate an expression in the active page
+//   puppet evalall <machine> <js...>  N expressions, one round-trip
+//   puppet batch                      JSON-lines requests on stdin, one connection
+//   puppet broadcast <js>             evaluate on ALL connected machines at once
+//   puppet nav <machine> <url>        navigate the active page
+//   puppet shot <machine> <out.png|.jpg>  screenshot (jpeg reads live watch frame)
+//   puppet watch <machine> <out.jpg>  screencast → latest frame on disk (--nth=N)
+//   puppet stroke <machine> x1,y1 x2,y2 [...]   trusted mouse drag through points
+//   puppet cursor <machine> <x> <y>   show/move a virtual cursor overlay
+//   puppet tail <machine>             stream console messages (ctrl-c to stop)
+//   puppet status                     daemon status (same JSON slab reads)
+//   puppet config                     print/create the config stub path
+//
+// Target selection: most-recently-active http(s) page, like cdp.mjs. Override
+// per-call with --target=<url or id substring>.
+//
+// Config shape (~/.config/slab/puppet.json):
+//   { "machines": { "<name>": { "cdpUrl": "http://127.0.0.1:9223",
+//                               "tunnelCmd": "ssh -fN -L 9223:127.0.0.1:9222 <host>" } } }
+// `tunnelCmd` is optional — run when the cdpUrl is unreachable, then retried.
+
+import { execSync } from "node:child_process";
+import { existsSync, mkdirSync, readFileSync, unlinkSync, writeFileSync } from "node:fs";
+import net from "node:net";
+import { homedir } from "node:os";
+import { dirname, join } from "node:path";
+
+const HOME = homedir();
+const CONFIG_PATH =
+  process.env.SLAB_PUPPET_CONFIG || join(HOME, ".config", "slab", "puppet.json");
+const RUN_DIR = join(HOME, ".local", "share", "puppet");
+const SOCK_PATH = process.env.SLAB_PUPPET_SOCK || join(RUN_DIR, "puppet.sock");
+const STATUS_PATH = join(RUN_DIR, "status.json");
+
+const CONFIG_STUB = {
+  _README:
+    "slab puppet config — UNTRACKED, never committed. Register machines " +
+    "whose Chrome runs with --remote-debugging-port (reachable from here, " +
+    "e.g. via an ssh -L tunnel since CDP binds loopback).",
+  machines: {},
+};
+
+// ─── config ──────────────────────────────────────────────────────────────
+
+function loadConfig() {
+  if (!existsSync(CONFIG_PATH)) return null;
+  try {
+    return JSON.parse(readFileSync(CONFIG_PATH, "utf8"));
+  } catch {
+    return null;
+  }
+}
+
+function cmdConfig() {
+  if (!existsSync(CONFIG_PATH)) {
+    mkdirSync(dirname(CONFIG_PATH), { recursive: true });
+    writeFileSync(CONFIG_PATH, JSON.stringify(CONFIG_STUB, null, 2) + "\n");
+    console.log(`created stub: ${CONFIG_PATH}`);
+  } else {
+    console.log(CONFIG_PATH);
+  }
+}
+
+// ─── daemon: one Machine per registry entry ──────────────────────────────
+
+class Machine {
+  constructor(name, spec) {
+    this.name = name;
+    this.spec = spec; // { cdpUrl, tunnelCmd? }
+    this.browser = null; // browser-level WebSocket
+    this.nextId = 1;
+    this.pending = new Map(); // id -> {resolve, reject}
+    this.sessions = new Map(); // targetId -> sessionId
+    this.targets = new Map(); // targetId -> {url, title, attached}
+    this.consoleSubs = new Set(); // client sockets tailing console
+    this.watches = new Map(); // sessionId -> live frame path (shot fast-path)
+    this.frameHandlers = new Map(); // sessionId -> screencast frame sink
+    this.connected = false;
+    this.lastError = null;
+    this.triedTunnel = false;
+  }
+
+  log(msg) {
+    console.log(`[${this.name}] ${msg}`);
+  }
+
+  async connectLoop() {
+    for (;;) {
+      try {
+        await this.connect();
+        this.triedTunnel = false;
+        await new Promise(res => (this.onClose = res)); // park until close
+      } catch (err) {
+        this.lastError = String(err?.message || err);
+        if (this.spec.tunnelCmd && !this.triedTunnel) {
+          this.triedTunnel = true;
+          this.log(`unreachable, running tunnelCmd`);
+          try {
+            execSync(this.spec.tunnelCmd, { stdio: "ignore", timeout: 15000 });
+          } catch {}
+        }
+      }
+      this.connected = false;
+      this.browser = null;
+      this.sessions.clear();
+      this.targets.clear();
+      writeStatus();
+      await new Promise(res => setTimeout(res, 3000));
+    }
+  }
+
+  async connect() {
+    const ver = await fetch(`${this.spec.cdpUrl}/json/version`).then(r => r.json());
+    const ws = new WebSocket(ver.webSocketDebuggerUrl);
+    await new Promise((res, rej) => {
+      ws.onopen = res;
+      ws.onerror = () => rej(new Error("ws connect failed"));
+    });
+    this.browser = ws;
+    ws.onmessage = e => this.onMessage(JSON.parse(e.data));
+    ws.onclose = () => {
+      this.log("browser socket closed");
+      for (const p of this.pending.values()) p.reject(new Error("socket closed"));
+      this.pending.clear();
+      this.connected = false;
+      this.onClose?.();
+    };
+    await this.call("Target.setDiscoverTargets", { discover: true });
+    this.connected = true;
+    this.lastError = null;
+    this.log(`connected (${ver.Browser})`);
+    writeStatus();
+  }
+
+  call(method, params = {}, sessionId) {
+    return new Promise((resolve, reject) => {
+      const id = this.nextId++;
+      const timer = setTimeout(() => {
+        if (this.pending.delete(id)) reject(new Error(`${method} timed out`));
+      }, 20000);
+      this.pending.set(id, {
+        resolve: v => {
+          clearTimeout(timer);
+          resolve(v);
+        },
+        reject: e => {
+          clearTimeout(timer);
+          reject(e);
+        },
+      });
+      this.browser.send(JSON.stringify({ id, method, params, sessionId }));
+    });
+  }
+
+  // Fire-and-forget CDP send — no pending entry, replies are ignored. CDP
+  // preserves ordering on the socket, so streams of input events stay in
+  // sequence; await only the calls whose results matter.
+  callNoWait(method, params = {}, sessionId) {
+    this.browser.send(JSON.stringify({ id: this.nextId++, method, params, sessionId }));
+  }
+
+  onMessage(msg) {
+    if (msg.id && this.pending.has(msg.id)) {
+      const p = this.pending.get(msg.id);
+      this.pending.delete(msg.id);
+      if (msg.error) p.reject(new Error(msg.error.message));
+      else p.resolve(msg.result);
+      return;
+    }
+    const { method, params } = msg;
+    if (method === "Target.targetCreated" || method === "Target.targetInfoChanged") {
+      const t = params.targetInfo;
+      if (t.type === "page") this.targets.set(t.targetId, { url: t.url, title: t.title });
+    } else if (method === "Target.targetDestroyed") {
+      this.targets.delete(params.targetId);
+      this.sessions.delete(params.targetId);
+    } else if (method === "Page.screencastFrame" && msg.sessionId) {
+      const h = this.frameHandlers?.get(msg.sessionId);
+      if (h) h(msg);
+    } else if (method === "Runtime.consoleAPICalled" && msg.sessionId) {
+      const line = params.args
+        .map(a => a.value ?? a.description ?? "")
+        .join(" ");
+      const evt = JSON.stringify({
+        machine: this.name,
+        type: params.type,
+        line,
+      });
+      this.pushToSubs(evt);
+    } else if (method === "Runtime.bindingCalled" && params.name === "__puppetEvent") {
+      // push-style events from in-page harnesses — no polling, no console noise
+      const evt = JSON.stringify({ machine: this.name, type: "event", line: params.payload });
+      this.pushToSubs(evt);
+    }
+  }
+
+  // Write to console subscribers, EVICTING the dead and the backed-up. A
+  // SIGKILLed tail leaves a half-open socket whose writes buffer in daemon
+  // memory forever — this fed a machine-wide RAM leak on 2026-06-12 (hours
+  // of console events × several abandoned tails on an 8 GB controller).
+  pushToSubs(evt) {
+    for (const sock of this.consoleSubs) {
+      if (sock.destroyed || sock.writableLength > 1 << 20) {
+        this.consoleSubs.delete(sock);
+        try { sock.destroy(); } catch {}
+        continue;
+      }
+      try {
+        sock.write(evt + "\n");
+      } catch {
+        this.consoleSubs.delete(sock);
+      }
+    }
+  }
+
+  pickTarget(filter) {
+    const pages = [...this.targets.entries()].map(([id, t]) => ({ id, ...t }));
+    if (filter) {
+      const m = pages.find(p => p.id.includes(filter) || (p.url || "").includes(filter));
+      if (m) return m;
+    }
+    return pages.filter(p => /^https?:/.test(p.url || "")).pop() || pages.pop();
+  }
+
+  async session(filter) {
+    const target = this.pickTarget(filter);
+    if (!target) throw new Error("no page target");
+    let sessionId = this.sessions.get(target.id);
+    if (!sessionId) {
+      const r = await this.call("Target.attachToTarget", {
+        targetId: target.id,
+        flatten: true,
+      });
+      sessionId = r.sessionId;
+      this.sessions.set(target.id, sessionId);
+      // enable once per attach — nav/shot/reload used to re-send Page.enable
+      // every call, one wasted tunnel round-trip each (6-17ms here).
+      await this.call("Runtime.enable", {}, sessionId).catch(() => {});
+      await this.call("Page.enable", {}, sessionId).catch(() => {});
+      // push channel: pages call window.__puppetEvent(str) → tail stream
+      await this.call("Runtime.addBinding", { name: "__puppetEvent" }, sessionId).catch(() => {});
+    }
+    return sessionId;
+  }
+
+  async eval(expr, filter) {
+    const sessionId = await this.session(filter);
+    const r = await this.call(
+      "Runtime.evaluate",
+      { expression: expr, returnByValue: true, awaitPromise: true },
+      sessionId,
+    );
+    if (r.exceptionDetails) throw new Error(r.exceptionDetails.exception?.description || "eval threw");
+    return r.result?.value;
+  }
+
+  // Open a new tab or positioned window (Target.createTarget). Returns targetId.
+  async newtab(url, win) {
+    const params = { url };
+    if (win) Object.assign(params, { newWindow: true, ...win });
+    const r = await this.call("Target.createTarget", params);
+    return r.targetId;
+  }
+
+  // Close a tab/window by target filter (Target.closeTarget). STRICT match
+  // only — never falls back to "most recent page" like pickTarget does
+  // (a close that guesses closes the wrong window; learned 2026-06-12).
+  async closeTarget(filter) {
+    if (!filter) throw new Error("close requires a target filter");
+    const target = [...this.targets.entries()]
+      .map(([id, t]) => ({ id, ...t }))
+      .find(t => t.id.includes(filter) || (t.url || "").includes(filter));
+    if (!target) throw new Error("no matching target");
+    await this.call("Target.closeTarget", { targetId: target.id });
+    this.sessions.delete(target.id);
+    this.targets.delete(target.id);
+    return `closed ${target.url?.slice(0, 60) || target.id}`;
+  }
+
+  // Hard refresh: cache-bypassing reload (what ⌘⇧R does).
+  async reload(filter) {
+    const sessionId = await this.session(filter);
+    await this.call("Page.reload", { ignoreCache: true }, sessionId);
+    return "hard-reloaded";
+  }
+
+  async nav(url, filter) {
+    const sessionId = await this.session(filter);
+    await this.call("Page.navigate", { url }, sessionId);
+    return url;
+  }
+
+  // Screenshot. opts: { format: "png"|"jpeg", quality (jpeg), fresh: true to
+  // force a capture even when a live watch frame could answer instantly }.
+  // PNG encode of a big window costs Chrome 50-150ms and 5-10× the tunnel
+  // bytes of JPEG — prefer .jpg outputs for iteration loops.
+  async shot(filter, opts = {}) {
+    const sessionId = await this.session(filter);
+    const live = this.watches?.get(sessionId);
+    if (live && opts.format === "jpeg" && !opts.fresh) {
+      try {
+        const fs = await import("node:fs");
+        return fs.readFileSync(live).toString("base64"); // 0ms: latest screencast frame
+      } catch {}
+    }
+    const params = { format: opts.format ?? "png" };
+    if (params.format === "jpeg") params.quality = opts.quality ?? 80;
+    const r = await this.call("Page.captureScreenshot", params, sessionId);
+    return r.data; // base64
+  }
+
+  // Trusted mouse drag through points, virtual cursor overlay riding along.
+  async stroke(points, filter) {
+    const sessionId = await this.session(filter);
+    await this.cursorEval(sessionId);
+    const [x0, y0] = points[0];
+    await this.cursorMove(sessionId, x0, y0, true);
+    await this.call(
+      "Input.dispatchMouseEvent",
+      { type: "mousePressed", x: x0, y: y0, button: "left", clickCount: 1 },
+      sessionId,
+    );
+    for (const [x, y] of points.slice(1)) {
+      this.callNoWait(
+        "Input.dispatchMouseEvent",
+        { type: "mouseMoved", x, y, button: "left", buttons: 1 },
+        sessionId,
+      );
+      await new Promise(res => setTimeout(res, 12));
+    }
+    const [xn, yn] = points[points.length - 1];
+    await this.call(
+      "Input.dispatchMouseEvent",
+      { type: "mouseReleased", x: xn, y: yn, button: "left", clickCount: 1 },
+      sessionId,
+    );
+    await this.cursorMove(sessionId, xn, yn, false);
+    return points.length;
+  }
+
+  // "Finger gesture": a trusted drag from start to goal that moves like a
+  // turtle — heading steered toward the goal with a limited turn rate,
+  // eased velocity (slow-fast-slow), micro-jitter — instead of a polyline.
+  // opts: { speed: px/s cruise (default 900), bend: initial heading offset
+  // in degrees (default random ±40), press: drag with button held (true),
+  // wobble: 0..1 hand tremor (heading noise + tiny speed flutter, default
+  // 0.3), hesitation: 0..1 likelihood of brief mid-gesture pauses (default
+  // 0.15) — parametric "finger personalities" for latency/sync testing }.
+  async gesture(from, to, opts = {}, filter) {
+    const sessionId = await this.session(filter);
+    await this.cursorEval(sessionId);
+    const speed = opts.speed ?? 900;
+    const press = opts.press !== false;
+    const [gx, gy] = to;
+    let [x, y] = from;
+    const bearing = Math.atan2(gy - y, gx - x);
+    const bend = ((opts.bend ?? (Math.random() * 80 - 40)) * Math.PI) / 180;
+    let heading = bearing + bend;
+    const DT = 0.008; // ~120Hz event clock
+    const MAX_TURN = 4.2 * DT; // rad per tick
+    const total = Math.hypot(gx - x, gy - y);
+    const ease = p => 0.25 + 0.75 * Math.sin(Math.min(1, Math.max(0, p)) * Math.PI); // slow-fast-slow
+    await this.cursorMove(sessionId, x, y, press);
+    if (press)
+      await this.call(
+        "Input.dispatchMouseEvent",
+        { type: "mousePressed", x, y, button: "left", clickCount: 1 },
+        sessionId,
+      );
+    let steps = 0;
+    for (; steps < 2000; steps++) {
+      const dist = Math.hypot(gx - x, gy - y);
+      if (dist < 3) break;
+      const want = Math.atan2(gy - y, gx - x);
+      let dh = want - heading;
+      while (dh > Math.PI) dh -= 2 * Math.PI;
+      while (dh < -Math.PI) dh += 2 * Math.PI;
+      // tighten steering as the goal nears so the turtle can't orbit it
+      const turn = Math.min(Math.abs(dh), MAX_TURN * (1 + (8 * (total - dist)) / total));
+      const wobble = opts.wobble ?? 0.3;
+      heading += Math.sign(dh) * turn + (Math.random() - 0.5) * 0.08 * wobble;
+      const hesitation = opts.hesitation ?? 0.15;
+      if (Math.random() < hesitation * 0.015)
+        await new Promise(r => setTimeout(r, 60 + Math.random() * 180));
+      const flutter = 1 + (Math.random() - 0.5) * 0.3 * wobble;
+      const v = speed * ease(1 - dist / total) * DT * flutter;
+      x += Math.cos(heading) * Math.min(v, dist);
+      y += Math.sin(heading) * Math.min(v, dist);
+      // fire-and-forget: the DT tick is the clock; awaiting each dispatch
+      // dragged the "120Hz" loop down to 35–55Hz over the tunnels. The
+      // page-side follower in cursorEval moves the overlay for free.
+      this.callNoWait(
+        "Input.dispatchMouseEvent",
+        {
+          type: "mouseMoved",
+          x: Math.round(x),
+          y: Math.round(y),
+          button: press ? "left" : "none",
+          buttons: press ? 1 : 0,
+        },
+        sessionId,
+      );
+      await new Promise(r => setTimeout(r, DT * 1000));
+    }
+    if (press)
+      await this.call(
+        "Input.dispatchMouseEvent",
+        { type: "mouseReleased", x: Math.round(x), y: Math.round(y), button: "left", clickCount: 1 },
+        sessionId,
+      );
+    await this.cursorMove(sessionId, Math.round(x), Math.round(y), false);
+    return steps;
+  }
+
+  // Trusted key press (Input.dispatchKeyEvent). `key` is a DOM key name
+  // ("Backspace", "Enter", "a"); modifiers bitmask: 1 alt, 2 ctrl, 4 meta, 8 shift.
+  async key(key, modifiers = 0, filter) {
+    const sessionId = await this.session(filter);
+    const printable = key.length === 1;
+    // keyCode AND code matter: apps read e.key, e.keyCode, or e.code — a 0
+    // keyCode + missing code made arrow keys invisible to games (stayon).
+    const CODES = {
+      Backspace: 8, Tab: 9, Enter: 13, Escape: 27, Space: 32, Delete: 46,
+      ArrowLeft: 37, ArrowUp: 38, ArrowRight: 39, ArrowDown: 40,
+    };
+    const base = {
+      key,
+      modifiers,
+      code: printable
+        ? (/[a-z]/i.test(key) ? "Key" + key.toUpperCase() : /\d/.test(key) ? "Digit" + key : undefined)
+        : key === " " ? "Space" : key,
+      windowsVirtualKeyCode:
+        CODES[key] ?? (printable ? key.toUpperCase().charCodeAt(0) : 0),
+      nativeVirtualKeyCode:
+        CODES[key] ?? (printable ? key.toUpperCase().charCodeAt(0) : 0),
+    };
+    await this.call(
+      "Input.dispatchKeyEvent",
+      { type: printable ? "keyDown" : "rawKeyDown", ...base, text: printable ? key : undefined },
+      sessionId,
+    );
+    await this.call("Input.dispatchKeyEvent", { type: "keyUp", ...base }, sessionId);
+    return key;
+  }
+
+  cursorEval(sessionId) {
+    return this.call(
+      "Runtime.evaluate",
+      {
+        expression: `(()=>{let c=document.getElementById("__puppet_cursor");
+if(!c){c=document.createElement("div");c.id="__puppet_cursor";
+c.style.cssText="position:fixed;z-index:2147483647;width:18px;height:18px;border-radius:50%;border:2px solid #fff;background:rgba(255,64,129,.8);pointer-events:none;transform:translate(-50%,-50%);box-shadow:0 0 8px rgba(0,0,0,.5);transition:opacity .3s";
+document.documentElement.appendChild(c);
+// page-side follower: the overlay rides the (trusted) pointer stream itself,
+// so drivers never spend a round-trip moving it
+document.addEventListener("mousemove",e=>{c.style.left=e.clientX+"px";c.style.top=e.clientY+"px";c.style.opacity=1;},{passive:true,capture:true});
+}return true;})()`,
+        returnByValue: true,
+      },
+      sessionId,
+    );
+  }
+
+  cursorMove(sessionId, x, y, pressed) {
+    return this.call(
+      "Runtime.evaluate",
+      {
+        expression: `(()=>{const c=document.getElementById("__puppet_cursor");
+if(c){c.style.left=${x}+"px";c.style.top=${y}+"px";c.style.opacity=1;
+c.style.background=${pressed} ? "rgba(255,64,129,.9)" : "rgba(255,64,129,.45)";}return true;})()`,
+        returnByValue: true,
+      },
+      sessionId,
+    );
+  }
+
+  // Live screencast: Chrome pushes JPEG frames; we keep the LATEST on disk
+  // (atomic rename) so "give me a screenshot" is a zero-latency file read.
+  async watch(filter, outPath, opts = {}) {
+    const sessionId = await this.session(filter);
+    const fs = await import("node:fs");
+    fs.mkdirSync(dirname(outPath), { recursive: true });
+    await this.call("Page.enable", {}, sessionId).catch(() => {});
+    // Occluded windows stop painting on macOS → zero damage frames. Surface
+    // the page so the screencast actually flows (chicken streamed only
+    // because its window happened to be frontmost).
+    await this.call("Page.bringToFront", {}, sessionId).catch(() => {});
+    this.frameHandlers ??= new Map();
+    this.watches ??= new Map(); // sessionId -> outPath (lets shot read the live frame)
+    this.watches.set(sessionId, outPath);
+    this.frameHandlers.set(sessionId, msg => {
+      fs.writeFileSync(outPath + ".tmp", Buffer.from(msg.params.data, "base64"));
+      fs.renameSync(outPath + ".tmp", outPath);
+      this.call("Page.screencastFrameAck", { sessionId: msg.params.sessionId }, sessionId).catch(() => {});
+    });
+    await this.call(
+      "Page.startScreencast",
+      {
+        format: "jpeg",
+        quality: opts.quality ?? 60, // q60 @ 900w verified legible for terminal text
+        maxWidth: opts.maxWidth ?? 900,
+        everyNthFrame: opts.everyNthFrame ?? 1, // 2-3 halves encode CPU on animated pieces
+      },
+      sessionId,
+    );
+    return `watching → ${outPath}`;
+  }
+
+  async unwatch(filter) {
+    const sessionId = await this.session(filter);
+    await this.call("Page.stopScreencast", {}, sessionId).catch(() => {});
+    this.frameHandlers?.delete(sessionId);
+    this.watches?.delete(sessionId);
+    return "stopped";
+  }
+
+  async tailConsole(sock, filter) {
+    const sessionId = await this.session(filter);
+    await this.call("Runtime.enable", {}, sessionId).catch(() => {});
+    this.consoleSubs.add(sock);
+    sock.on("close", () => this.consoleSubs.delete(sock));
+    sock.on("error", () => this.consoleSubs.delete(sock));
+  }
+
+  info() {
+    return {
+      connected: this.connected,
+      lastError: this.lastError,
+      targets: [...this.targets.values()].map(t => t.url),
+    };
+  }
+}
+
+const machines = new Map();
+
+function writeStatus() {
+  mkdirSync(RUN_DIR, { recursive: true });
+  const status = { updatedAt: new Date().toISOString(), machines: {} };
+  for (const [name, m] of machines) status.machines[name] = m.info();
+  writeFileSync(STATUS_PATH, JSON.stringify(status, null, 2));
+}
+
+async function handleRequest(req, sock) {
+  const { cmd, machine, args = {} } = req;
+  const one = name => {
+    const m = machines.get(name);
+    if (!m) throw new Error(`unknown machine: ${name}`);
+    if (!m.connected) throw new Error(`${name} not connected`);
+    return m;
+  };
+  switch (cmd) {
+    case "list": {
+      const out = {};
+      for (const [name, m] of machines) out[name] = m.info();
+      return out;
+    }
+    case "eval":
+      return one(machine).eval(args.expr, args.target);
+    // N expressions against one target, one client round-trip (CDP calls
+    // pipeline on the open browser socket) — assertion loops in one shot.
+    // Poll an expression until truthy — replaces fixed client-side sleeps at
+    // coordination points (page loaded? composer open? node count right?).
+    // One client round-trip; the daemon polls the open CDP socket at
+    // `interval` ms (default 150) until `timeout` (default 15000).
+    case "waitFor": {
+      const m = one(machine);
+      const t0 = Date.now();
+      const interval = args.interval ?? 150;
+      const timeout = args.timeout ?? 15000;
+      for (;;) {
+        let v;
+        try {
+          v = await m.eval(args.expr, args.target);
+        } catch {}
+        if (v) return { ok: true, value: v, ms: Date.now() - t0 };
+        if (Date.now() - t0 > timeout) return { ok: false, ms: Date.now() - t0 };
+        await new Promise(r => setTimeout(r, interval));
+      }
+    }
+    case "evalAll": {
+      const m = one(machine);
+      return Promise.all(
+        (args.exprs || []).map(e => m.eval(e, args.target).catch(x => `ERR: ${x.message}`)),
+      );
+    }
+    // Simultaneous action against an explicit set of {machine, target}
+    // pairs — the multi-window fan-out broadcast can't express (broadcast
+    // picks each machine's most-recent page; fanout pins every window).
+    case "fanout": {
+      const { pairs, action, expr, points, key } = args;
+      const results = await Promise.all(
+        pairs.map(async p => {
+          try {
+            const m = one(p.machine);
+            if (action === "eval") return await m.eval(expr, p.target);
+            if (action === "stroke") return await m.stroke(points, p.target);
+            if (action === "key") return await m.key(key, args.modifiers ?? 0, p.target);
+            throw new Error(`unknown fanout action: ${action}`);
+          } catch (e) {
+            return `ERR: ${e.message}`;
+          }
+        }),
+      );
+      return Object.fromEntries(pairs.map((p, i) => [`${p.machine}:${(p.target || "").slice(0, 8)}`, results[i]]));
+    }
+    case "broadcast": {
+      const out = {};
+      await Promise.all(
+        [...machines.entries()]
+          .filter(([, m]) => m.connected)
+          .map(async ([name, m]) => {
+            out[name] = await m.eval(args.expr, args.target).catch(e => `ERR: ${e.message}`);
+          }),
+      );
+      return out;
+    }
+    case "nav":
+      return one(machine).nav(args.url, args.target);
+    case "newtab":
+      return one(machine).newtab(args.url, args.window);
+    case "close":
+      return one(machine).closeTarget(args.target);
+    case "reload": {
+      if (machine) return one(machine).reload(args.target);
+      const out = {};
+      await Promise.all(
+        [...machines.entries()]
+          .filter(([, m]) => m.connected)
+          .map(async ([name, m]) => {
+            out[name] = await m.reload(args.target).catch(e => `ERR: ${e.message}`);
+          }),
+      );
+      return out;
+    }
+    case "shot":
+      return one(machine).shot(args.target, args);
+    case "stroke":
+      return one(machine).stroke(args.points, args.target);
+    case "key":
+      return one(machine).key(args.key, args.modifiers ?? 0, args.target);
+    case "gesture":
+      return one(machine).gesture(args.from, args.to, args.opts ?? {}, args.target);
+    case "cursor": {
+      const m = one(machine);
+      const sessionId = await m.session(args.target);
+      await m.cursorEval(sessionId);
+      await m.cursorMove(sessionId, args.x, args.y, false);
+      return true;
+    }
+    case "watch":
+      return one(machine).watch(args.target, args.out, args.opts ?? {});
+    case "unwatch":
+      return one(machine).unwatch(args.target);
+    case "tail":
+      await one(machine).tailConsole(sock, args.target);
+      return "__stream__"; // keep socket open
+    default:
+      throw new Error(`unknown cmd: ${cmd}`);
+  }
+}
+
+async function cmdDaemon() {
+  const cfg = loadConfig();
+  if (!cfg || !Object.keys(cfg.machines || {}).length) {
+    console.error(`no machines registered — edit ${CONFIG_PATH} (puppet config)`);
+    process.exit(1);
+  }
+  mkdirSync(RUN_DIR, { recursive: true });
+  try { unlinkSync(SOCK_PATH); } catch {}
+  for (const [name, spec] of Object.entries(cfg.machines)) {
+    const m = new Machine(name, spec);
+    machines.set(name, m);
+    m.connectLoop();
+  }
+  const server = net.createServer(sock => {
+    let buf = "";
+    sock.on("data", async chunk => {
+      buf += chunk;
+      let nl;
+      while ((nl = buf.indexOf("\n")) >= 0) {
+        const line = buf.slice(0, nl);
+        buf = buf.slice(nl + 1);
+        if (!line.trim()) continue;
+        let req;
+        try {
+          req = JSON.parse(line);
+        } catch {
+          sock.write(JSON.stringify({ error: "bad json" }) + "\n");
+          continue;
+        }
+        try {
+          const result = await handleRequest(req, sock);
+          if (result !== "__stream__")
+            sock.write(JSON.stringify({ id: req.id, result }) + "\n");
+        } catch (err) {
+          sock.write(JSON.stringify({ id: req.id, error: String(err.message || err) }) + "\n");
+        }
+      }
+    });
+    sock.on("error", () => {});
+  });
+  server.listen(SOCK_PATH, () => console.log(`puppet daemon listening on ${SOCK_PATH}`));
+  writeStatus();
+  setInterval(writeStatus, 10000);
+}
+
+// ─── CLI client ──────────────────────────────────────────────────────────
+
+function rpc(req, { stream = false, timeoutMs = 20000 } = {}) {
+  return new Promise((resolve, reject) => {
+    const sock = net.createConnection(SOCK_PATH);
+    // A daemon mid-reconnect (or a stale socket) that never replies must
+    // FAIL FAST — an untimed rpc wedged an 8-window fan-out script forever.
+    const timer = stream
+      ? null
+      : setTimeout(() => {
+          sock.destroy();
+          reject(new Error(`rpc timeout after ${timeoutMs}ms (${req.cmd})`));
+        }, timeoutMs);
+    sock.on("error", () => {
+      if (timer) clearTimeout(timer);
+      reject(new Error("daemon not running — start with: puppet daemon"));
+    });
+    let buf = "";
+    sock.on("data", chunk => {
+      buf += chunk;
+      let nl;
+      while ((nl = buf.indexOf("\n")) >= 0) {
+        const line = buf.slice(0, nl);
+        buf = buf.slice(nl + 1);
+        if (stream) {
+          console.log(line);
+          continue;
+        }
+        sock.end();
+        if (timer) clearTimeout(timer);
+        const msg = JSON.parse(line);
+        if (msg.error) reject(new Error(msg.error));
+        else resolve(msg.result);
+      }
+    });
+    sock.write(JSON.stringify(req) + "\n");
+    if (stream) sock.on("close", () => resolve());
+  });
+}
+
+function parseFlags(argv) {
+  const flags = {};
+  const rest = [];
+  for (const a of argv) {
+    const m = a.match(/^--([^=]+)=(.*)$/);
+    if (m) flags[m[1]] = m[2];
+    else rest.push(a);
+  }
+  return { flags, rest };
+}
+
+async function main() {
+  const { flags, rest } = parseFlags(process.argv.slice(2));
+  const [cmd, ...args] = rest;
+  switch (cmd) {
+    case "daemon":
+      return cmdDaemon();
+    case "config":
+      return cmdConfig();
+    case "status":
+      console.log(readFileSync(STATUS_PATH, "utf8"));
+      return;
+    case "list":
+      console.log(JSON.stringify(await rpc({ cmd: "list" }), null, 2));
+      return;
+    case "eval":
+      console.log(
+        JSON.stringify(
+          await rpc({ cmd: "eval", machine: args[0], args: { expr: args[1], target: flags.target } }),
+        ),
+      );
+      return;
+    // puppet waitfor <machine> <expr> [--timeout=15000] [--interval=150]
+    case "waitfor":
+      console.log(
+        JSON.stringify(
+          await rpc({
+            cmd: "waitFor",
+            machine: args[0],
+            args: { expr: args[1], target: flags.target, timeout: Number(flags.timeout || 15000), interval: Number(flags.interval || 150) },
+          }),
+        ),
+      );
+      return;
+    // puppet evalall <machine> <expr1> <expr2> ... — one round-trip
+    case "evalall":
+      console.log(
+        JSON.stringify(
+          await rpc({ cmd: "evalAll", machine: args[0], args: { exprs: args.slice(1), target: flags.target } }),
+          null,
+          2,
+        ),
+      );
+      return;
+    // puppet batch — JSON-lines requests on stdin, replies on stdout,
+    // all over ONE daemon connection (kills the per-call spawn cost for
+    // scripted loops: pipe a heredoc of {cmd,machine,args} lines in).
+    case "batch": {
+      const { createInterface } = await import("node:readline");
+      const sock2 = net.createConnection(SOCK_PATH);
+      let buf2 = "";
+      let received = 0;
+      sock2.on("data", c => {
+        buf2 += c;
+        let nl;
+        while ((nl = buf2.indexOf("\n")) >= 0) {
+          console.log(buf2.slice(0, nl));
+          buf2 = buf2.slice(nl + 1);
+          received++;
+        }
+      });
+      const rl = createInterface({ input: process.stdin });
+      let sent = 0;
+      for await (const line of rl) {
+        if (line.trim()) {
+          sock2.write(line + "\n");
+          sent++;
+        }
+      }
+      // exit as soon as every request has answered (10s safety net)
+      await new Promise(r => {
+        const deadline = setTimeout(r, 10000);
+        const tick = setInterval(() => {
+          if (received >= sent) { clearTimeout(deadline); clearInterval(tick); r(); }
+        }, 5);
+      });
+      sock2.end();
+      return;
+    }
+    case "broadcast":
+      console.log(
+        JSON.stringify(
+          await rpc({ cmd: "broadcast", args: { expr: args[0], target: flags.target } }),
+          null,
+          2,
+        ),
+      );
+      return;
+    // puppet fanout eval '<js>' machine:target [machine:target ...]
+    // puppet fanout stroke x1,y1[ x2,y2 ...] machine:target [...]
+    // puppet fanout key <Key> machine:target [...]
+    case "fanout": {
+      const action = args[0];
+      let expr, points, key, pairStart;
+      if (action === "eval") { expr = args[1]; pairStart = 2; }
+      else if (action === "key") { key = args[1]; pairStart = 2; }
+      else if (action === "stroke") {
+        points = [];
+        let i = 1;
+        while (args[i] && /^[\d.]+,[\d.]+$/.test(args[i])) points.push(args[i++].split(",").map(Number));
+        pairStart = i;
+      } else { console.error("fanout action must be eval|stroke|key"); return; }
+      const pairs = args.slice(pairStart).map(s => {
+        const i = s.indexOf(":");
+        return { machine: s.slice(0, i), target: s.slice(i + 1) };
+      });
+      console.log(
+        JSON.stringify(
+          await rpc({ cmd: "fanout", args: { pairs, action, expr, points, key, modifiers: Number(flags.mod || 0) } }),
+          null,
+          2,
+        ),
+      );
+      return;
+    }
+    case "nav":
+      console.log(await rpc({ cmd: "nav", machine: args[0], args: { url: args[1], target: flags.target } }));
+      return;
+    case "reload":
+      console.log(
+        JSON.stringify(await rpc({ cmd: "reload", machine: args[0], args: { target: flags.target } })),
+      );
+      return;
+    case "close":
+      console.log(await rpc({ cmd: "close", machine: args[0], args: { target: args[1] || flags.target } }));
+      return;
+    case "newtab": {
+      let win;
+      if (flags.window) {
+        const [left, top, width, height] = flags.window.split(",").map(Number);
+        win = { left, top, width, height };
+      }
+      console.log(await rpc({ cmd: "newtab", machine: args[0], args: { url: args[1], window: win } }));
+      return;
+    }
+    case "shot": {
+      // format inferred from extension (.jpg → jpeg); --fresh=1 forces a
+      // real capture instead of returning a live watch frame.
+      const out = args[1];
+      const format = flags.format || (/\.jpe?g$/i.test(out || "") ? "jpeg" : "png");
+      const b64 = await rpc({
+        cmd: "shot",
+        machine: args[0],
+        args: { target: flags.target, format, quality: Number(flags.quality || 80), fresh: flags.fresh === "1" },
+      });
+      writeFileSync(out, Buffer.from(b64, "base64"));
+      console.log(`wrote ${out}`);
+      return;
+    }
+    case "stroke": {
+      const points = args.slice(1).map(p => p.split(",").map(Number));
+      console.log(
+        await rpc({ cmd: "stroke", machine: args[0], args: { points, target: flags.target } }),
+        "points dispatched",
+      );
+      return;
+    }
+    case "key":
+      console.log(
+        await rpc({
+          cmd: "key",
+          machine: args[0],
+          args: { key: args[1], modifiers: Number(flags.mod || 0), target: flags.target },
+        }),
+      );
+      return;
+    case "gesture": {
+      const from = args[1].split(",").map(Number);
+      const to = args[2].split(",").map(Number);
+      const opts = {};
+      for (const k of ["speed", "bend", "wobble", "hesitation"])
+        if (flags[k] !== undefined) opts[k] = Number(flags[k]);
+      console.log(
+        await rpc({ cmd: "gesture", machine: args[0], args: { from, to, opts, target: flags.target } }),
+        "steps",
+      );
+      return;
+    }
+    case "cursor":
+      await rpc({
+        cmd: "cursor",
+        machine: args[0],
+        args: { x: Number(args[1]), y: Number(args[2]), target: flags.target },
+      });
+      console.log("cursor placed");
+      return;
+    case "watch":
+      console.log(
+        await rpc({
+          cmd: "watch",
+          machine: args[0],
+          args: { target: flags.target, out: args[1], opts: { quality: Number(flags.quality || 60), maxWidth: Number(flags.maxwidth || 900), everyNthFrame: Number(flags.nth || 1) } },
+        }),
+      );
+      return;
+    case "unwatch":
+      console.log(await rpc({ cmd: "unwatch", machine: args[0], args: { target: flags.target } }));
+      return;
+    case "tail":
+      await rpc({ cmd: "tail", machine: args[0], args: { target: flags.target } }, { stream: true });
+      return;
+    default:
+      console.log(
+        "usage: puppet daemon|config|status|list|eval|evalall|batch|broadcast|fanout|nav|newtab|close|reload|shot|watch|unwatch|stroke|gesture|key|cursor|tail (see header)",
+      );
+  }
+}
+
+main().catch(err => {
+  console.error(String(err.message || err));
+  process.exit(1);
+});
diff --git a/slab/bin/screenplan.mjs b/slab/bin/screenplan.mjs
new file mode 100755
index 000000000..d739de282
--- /dev/null
+++ b/slab/bin/screenplan.mjs
@@ -0,0 +1,120 @@
+#!/usr/bin/env node
+// screenplan.mjs — rectangle-packing window placement for remote test rigs.
+//
+// The slab AXTiler idea, generalized over ssh: ask a machine for every
+// visible window's frame (System Events; needs Accessibility), add fixed
+// no-go zones (menu bar, desktop badge corner, dock strip), then first-fit
+// scan free space for each requested rect. Prints JSON placements; callers
+// (puppet windows, Stickies moves) apply them.
+//
+//   screenplan.mjs <ssh-host> --want 1200x1000,1200x1000 [--badge TL|TR]
+//                  [--ignore "Google Chrome"] [--margin 16] [--grid 24]
+//
+// `--ignore` drops an app's windows from the occupied set (e.g. when the
+// caller is about to move/replace its own Chrome windows). Stickies are
+// always considered occupied unless ignored. PUBLIC repo: no machine names.
+
+import { execFileSync } from "node:child_process";
+
+const args = process.argv.slice(2);
+const host = args[0];
+const flag = name => {
+  const i = args.indexOf(`--${name}`);
+  return i >= 0 ? args[i + 1] : undefined;
+};
+if (!host || !flag("want")) {
+  console.error("usage: screenplan.mjs <ssh-host> --want WxH[,WxH...] [--badge TL|TR] [--ignore App] [--margin 16] [--grid 24]");
+  process.exit(1);
+}
+const want = flag("want").split(",").map(s => s.split("x").map(Number));
+const badge = flag("badge") ?? "TL";
+const ignore = (flag("ignore") ?? "").split(",").filter(Boolean);
+const MARGIN = Number(flag("margin") ?? 16);
+const GRID = Number(flag("grid") ?? 24);
+
+// ── occupied rects from the machine ────────────────────────────────────
+const SCRIPT = `
+set out to ""
+tell application "Finder" to set sb to bounds of window of desktop
+set out to out & "SCREEN|" & (item 3 of sb) & "|" & (item 4 of sb) & linefeed
+tell application "System Events"
+  repeat with proc in (every process whose visible is true and background only is false)
+    set pname to name of proc
+    try
+      repeat with w in (every window of proc)
+        try
+          set p to position of w
+          set s to size of w
+          set out to out & pname & "|" & (item 1 of p) & "|" & (item 2 of p) & "|" & (item 1 of s) & "|" & (item 2 of s) & linefeed
+        end try
+      end repeat
+    end try
+  end repeat
+end tell
+return out`;
+
+const raw = execFileSync("ssh", ["-o", "ConnectTimeout=10", host, "osascript", "-"], {
+  encoding: "utf8",
+  timeout: 30000,
+  input: SCRIPT,
+});
+
+let scrW = 1440, scrH = 900;
+const occupied = [];
+for (const line of raw.split("\n")) {
+  const parts = line.trim().split("|");
+  if (parts[0] === "SCREEN") {
+    scrW = Number(parts[1]);
+    scrH = Number(parts[2]);
+  } else if (parts.length === 5) {
+    const [app, x, y, w, h] = [parts[0], ...parts.slice(1).map(Number)];
+    if (ignore.includes(app)) continue;
+    if (w < 40 || h < 40) continue; // ignore slivers
+    occupied.push({ app, x, y, w, h });
+  }
+}
+
+// fixed no-go zones: menu bar, badge corner, dock strip
+occupied.push({ app: "_menubar", x: 0, y: 0, w: scrW, h: 28 });
+occupied.push(
+  badge === "TR"
+    ? { app: "_badge", x: scrW - 300, y: 0, w: 300, h: 220 }
+    : { app: "_badge", x: 0, y: 0, w: 300, h: 220 },
+);
+occupied.push({ app: "_dock", x: 0, y: scrH - 70, w: scrW, h: 70 });
+
+const pad = r => ({ x: r.x - MARGIN, y: r.y - MARGIN, w: r.w + 2 * MARGIN, h: r.h + 2 * MARGIN });
+const blocked = occupied.map(pad);
+const hits = (x, y, w, h, rects) =>
+  rects.some(r => x < r.x + r.w && x + w > r.x && y < r.y + r.h && y + h > r.y);
+
+// ── first-fit raster scan, top-left bias ────────────────────────────────
+const placed = [];
+for (const [w, h] of want) {
+  let spot = null;
+  for (let y = 28; y <= scrH - h && !spot; y += GRID) {
+    for (let x = 0; x <= scrW - w && !spot; x += GRID) {
+      if (!hits(x, y, w, h, blocked) && !hits(x, y, w, h, placed.map(pad))) spot = { x, y };
+    }
+  }
+  // fall back to shrinking 10% steps if nothing fits
+  let sw = w, sh = h;
+  while (!spot && sw > w * 0.5) {
+    sw = Math.round(sw * 0.9);
+    sh = Math.round(sh * 0.9);
+    for (let y = 28; y <= scrH - sh && !spot; y += GRID) {
+      for (let x = 0; x <= scrW - sw && !spot; x += GRID) {
+        if (!hits(x, y, sw, sh, blocked) && !hits(x, y, sw, sh, placed.map(pad))) spot = { x, y };
+      }
+    }
+  }
+  placed.push(spot ? { x: spot.x, y: spot.y, w: sw, h: sh } : null);
+}
+
+console.log(
+  JSON.stringify(
+    { screen: { w: scrW, h: scrH }, occupied: occupied.filter(o => !o.app.startsWith("_")).map(o => `${o.app} ${o.x},${o.y} ${o.w}x${o.h}`), placements: placed },
+    null,
+    2,
+  ),
+);
diff --git a/slab/bin/signal b/slab/bin/signal
new file mode 100755
index 000000000..f53485353
--- /dev/null
+++ b/slab/bin/signal
@@ -0,0 +1,38 @@
+#!/bin/bash
+# signal — node-resolving wrapper around signal.mjs.
+#
+# The menubar runs under launchd with a minimal PATH that does NOT include
+# fnm's per-shell node shim, so the Swift side calls THIS absolute path and
+# we resolve a usable `node` ourselves (mirrors Tools.resolve in Swift).
+set -u
+# Resolve through symlinks (this is symlinked into ~/.local/bin like the
+# other slab bins) so SCRIPT points at the real .mjs next to the wrapper.
+SRC="${BASH_SOURCE[0]}"
+while [ -L "$SRC" ]; do
+  DIR="$(cd -P "$(dirname "$SRC")" && pwd)"
+  SRC="$(readlink "$SRC")"
+  [[ "$SRC" != /* ]] && SRC="$DIR/$SRC"
+done
+HERE="$(cd -P "$(dirname "$SRC")" && pwd)"
+SCRIPT="$HERE/signal.mjs"
+
+find_node() {
+  if command -v node >/dev/null 2>&1; then command -v node; return; fi
+  local c
+  for c in \
+    "$HOME/.local/share/fnm/aliases/default/bin/node" \
+    "$HOME/.fnm/aliases/default/bin/node" \
+    /opt/homebrew/bin/node \
+    /usr/local/bin/node \
+    "$HOME/.volta/bin/node"; do
+    [ -x "$c" ] && { echo "$c"; return; }
+  done
+  # Newest fnm-managed version, if any.
+  c=$(ls -td "$HOME"/.local/share/fnm/node-versions/*/installation/bin/node \
+        2>/dev/null | head -1)
+  [ -n "$c" ] && [ -x "$c" ] && { echo "$c"; return; }
+  return 1
+}
+
+NODE="$(find_node)" || { echo '{"configured":false,"label":"iMessage: no node"}'; exit 0; }
+exec "$NODE" "$SCRIPT" "$@"
diff --git a/slab/bin/signal.mjs b/slab/bin/signal.mjs
new file mode 100644
index 000000000..1db839877
--- /dev/null
+++ b/slab/bin/signal.mjs
@@ -0,0 +1,417 @@
+#!/usr/bin/env node
+// signal.mjs — a tiny, generic Signal Desktop bridge for the slab menubar.
+//
+// Reads Signal Desktop's encrypted SQLCipher DB (read-only) for a configured
+// contact, reports an unread/last-message summary as JSON, rings a bell on a
+// NEW inbound message, prints recent messages / a live tail, and decrypts
+// attachments to a temp dir (handing PDFs to the slab viewer).
+//
+// This file ships in the PUBLIC aesthetic.computer repo, so it carries NO
+// personal data: the contact match / display name / bell target all live in
+// an UNTRACKED config at ~/.config/slab/signal.json (see `signal config`).
+//
+// How the DB is opened (all in-process — the key never touches disk or logs):
+//   1. config.json holds an `encryptedKey` (Electron safeStorage, "v10"…).
+//   2. The wrapping password is the macOS Keychain item "Signal Safe Storage"
+//      (prompts once for approval); PBKDF2-SHA1(salt "saltysalt", 1003, 16B)
+//      → AES-128-CBC (IV = 16 spaces) decrypts it to the 64-hex SQLCipher key.
+//   3. sqlcipher opens db.sqlite with `PRAGMA key="x'<hex>'"` + compat 4.
+// Attachments (version 2) are AES-256-CBC: file = IV‖ciphertext‖HMAC, key =
+// first 32B of localKey, mac = last 32B, plaintext truncated to `size`.
+//
+// Subcommands:
+//   signal status            JSON summary; rings bell on new inbound
+//   signal read [N]          print the last N messages (default 15)
+//   signal tail              live terminal client (prints + BEL on new inbound)
+//   signal attachments [N]   list the last N attachments (default 10), indexed
+//   signal save [N|all]      decrypt recent attachments → temp dir; open PDFs
+//   signal open              open Signal.app
+//   signal config            print the resolved config path (creates a stub)
+
+import { spawnSync, execFileSync } from "node:child_process";
+import crypto from "node:crypto";
+import {
+  existsSync,
+  mkdirSync,
+  readFileSync,
+  writeFileSync,
+  unlinkSync,
+} from "node:fs";
+import { homedir, tmpdir } from "node:os";
+import { join, dirname } from "node:path";
+
+const HOME = homedir();
+const SIGNAL_DIR = join(HOME, "Library", "Application Support", "Signal");
+const DB_PATH = join(SIGNAL_DIR, "sql", "db.sqlite");
+const CONFIG_JSON = join(SIGNAL_DIR, "config.json");
+const ATTACH_DIR = join(SIGNAL_DIR, "attachments.noindex");
+const CONFIG_PATH =
+  process.env.SLAB_SIGNAL_CONFIG || join(HOME, ".config", "slab", "signal.json");
+const STATE_DIR = join(
+  process.env.SLAB_HOME || join(HOME, ".local", "share", "slab"),
+  "signal",
+);
+const STATE_PATH = join(STATE_DIR, "state.json");
+const SAVE_DIR = join(STATE_DIR, "attachments");
+const SQLCIPHER = "/opt/homebrew/bin/sqlcipher";
+const SECURITY = "/usr/bin/security";
+
+// ─── config ────────────────────────────────────────────────────────────────
+
+const CONFIG_STUB = {
+  _README:
+    "slab signal contact config — UNTRACKED, never committed. Fill in `match`.",
+  displayName: "REPLACE_ME",
+  match: {
+    _comment:
+      "identify the conversation by ONE of: conversationId (exact), or any " +
+      "substring matched (case-insensitive) against the contact's full name / " +
+      "profile name / phone (e164).",
+    conversationId: "",
+    contains: "REPLACE_ME",
+    e164: "",
+  },
+  bellTty: "",
+  bellTtyComment:
+    "optional: a tty like /dev/ttys004 — writing BEL there flashes that terminal.",
+  sound: true,
+  soundFile: "",
+};
+
+function loadConfig() {
+  if (!existsSync(CONFIG_PATH)) return null;
+  try {
+    const cfg = JSON.parse(readFileSync(CONFIG_PATH, "utf8"));
+    const m = cfg?.match || {};
+    const configured =
+      cfg &&
+      cfg.displayName !== "REPLACE_ME" &&
+      (m.conversationId ||
+        (m.contains && m.contains !== "REPLACE_ME") ||
+        m.e164);
+    return configured ? cfg : null;
+  } catch {
+    return null;
+  }
+}
+
+function ensureConfigStub() {
+  if (existsSync(CONFIG_PATH)) return;
+  mkdirSync(dirname(CONFIG_PATH), { recursive: true });
+  writeFileSync(CONFIG_PATH, JSON.stringify(CONFIG_STUB, null, 2) + "\n", {
+    mode: 0o600,
+  });
+}
+
+// ─── DB key (in-process; never logged or written) ────────────────────────────
+
+let DB_KEY = null;
+function dbKey() {
+  if (DB_KEY) return DB_KEY;
+  const pw = execFileSync(SECURITY, [
+    "find-generic-password",
+    "-ws",
+    "Signal Safe Storage",
+  ])
+    .toString()
+    .trim();
+  const aesKey = crypto.pbkdf2Sync(pw, "saltysalt", 1003, 16, "sha1");
+  const cfg = JSON.parse(readFileSync(CONFIG_JSON, "utf8"));
+  if (!cfg.encryptedKey) {
+    // Legacy plaintext-key installs (pre-safeStorage) keep `key` directly.
+    if (cfg.key) return (DB_KEY = cfg.key);
+    throw new Error("config.json has neither encryptedKey nor key");
+  }
+  const blob = Buffer.from(cfg.encryptedKey, "hex").subarray(3); // strip "v10"
+  const dec = crypto.createDecipheriv("aes-128-cbc", aesKey, Buffer.alloc(16, 0x20));
+  DB_KEY = Buffer.concat([dec.update(blob), dec.final()]).toString();
+  return DB_KEY;
+}
+
+// ─── SQLCipher query (read-only) ─────────────────────────────────────────────
+
+// Route ONLY the SELECT's rows to a temp file via `.output` so the keying
+// PRAGMAs (which also print in -json mode) don't pollute the parsed JSON.
+function sql(query) {
+  const out = join(tmpdir(), `slab-signal-${process.pid}-${Math.random().toString(36).slice(2)}.json`);
+  const script =
+    `PRAGMA key="x'${dbKey()}'";\n` +
+    `PRAGMA cipher_compatibility=4;\n` +
+    `.mode json\n.output ${out}\n${query}\n.output stdout\n`;
+  const r = spawnSync(SQLCIPHER, ["-batch", "-readonly", DB_PATH], {
+    input: script,
+    encoding: "utf8",
+    maxBuffer: 128 * 1024 * 1024,
+  });
+  if (r.status !== 0) {
+    try { unlinkSync(out); } catch {}
+    const e = new Error((r.stderr || "sqlcipher failed").trim());
+    e.code = "SQLCIPHER";
+    throw e;
+  }
+  let text = "";
+  try { text = readFileSync(out, "utf8").trim(); } catch {}
+  try { unlinkSync(out); } catch {}
+  return text ? JSON.parse(text) : [];
+}
+
+const sqlStr = (s) => "'" + String(s).replace(/'/g, "''") + "'";
+
+// ─── conversation resolution ─────────────────────────────────────────────────
+
+function resolveConversationId(cfg) {
+  const m = cfg.match || {};
+  if (m.conversationId) return m.conversationId;
+  if (m.e164) {
+    const r = sql(`SELECT id FROM conversations WHERE e164=${sqlStr(m.e164)} LIMIT 1;`);
+    if (r.length) return r[0].id;
+  }
+  if (m.contains) {
+    const like = `%${m.contains.toLowerCase()}%`;
+    const r = sql(
+      `SELECT id FROM conversations WHERE type='private' AND (` +
+        `LOWER(IFNULL(profileFullName,'')) LIKE ${sqlStr(like)} OR ` +
+        `LOWER(IFNULL(profileName,'')||' '||IFNULL(profileFamilyName,'')) LIKE ${sqlStr(like)} OR ` +
+        `LOWER(IFNULL(name,'')) LIKE ${sqlStr(like)} OR ` +
+        `IFNULL(e164,'') LIKE ${sqlStr(like)}) ` +
+        `ORDER BY active_at DESC LIMIT 1;`,
+    );
+    if (r.length) return r[0].id;
+  }
+  return null;
+}
+
+// ─── messages ────────────────────────────────────────────────────────────────
+
+function recentMessages(convoId, limit) {
+  // sent_at is unix ms. type is 'incoming'/'outgoing'. body holds the text.
+  return sql(
+    `SELECT rowid AS id, type, body, sent_at AS sentAt, hasAttachments ` +
+      `FROM messages WHERE conversationId=${sqlStr(convoId)} ` +
+      `AND ((body IS NOT NULL AND body!='') OR hasAttachments=1) ` +
+      `ORDER BY sent_at DESC LIMIT ${Number(limit) || 15};`,
+  ).reverse();
+}
+
+function unreadInbound(convoId) {
+  // readStatus: 0 = unread (Signal's ReadStatus.Unread) for incoming messages.
+  const r = sql(
+    `SELECT COUNT(*) AS n FROM messages WHERE conversationId=${sqlStr(convoId)} ` +
+      `AND type='incoming' AND readStatus=0;`,
+  );
+  return r.length ? r[0].n : 0;
+}
+
+function maxInboundRowid(convoId) {
+  const r = sql(
+    `SELECT IFNULL(MAX(rowid),0) AS r FROM messages ` +
+      `WHERE conversationId=${sqlStr(convoId)} AND type='incoming';`,
+  );
+  return r.length ? r[0].r : 0;
+}
+
+// ─── attachments ─────────────────────────────────────────────────────────────
+
+function recentAttachments(convoId, limit) {
+  return sql(
+    `SELECT messageId, path, localKey, size, contentType, fileName, version, sentAt ` +
+      `FROM message_attachments WHERE conversationId=${sqlStr(convoId)} ` +
+      `AND path IS NOT NULL ORDER BY sentAt DESC LIMIT ${Number(limit) || 10};`,
+  );
+}
+
+// Decrypt a version-2 local attachment to `destPath`. Returns true on success.
+function decryptAttachment(att, destPath) {
+  const onDisk = join(ATTACH_DIR, att.path);
+  if (!existsSync(onDisk)) return false;
+  const buf = readFileSync(onDisk);
+  if (!att.localKey) {
+    // Unencrypted-at-rest (older/version 1) — copy through, trimmed to size.
+    writeFileSync(destPath, att.size ? buf.subarray(0, att.size) : buf);
+    return true;
+  }
+  const lk = Buffer.from(att.localKey, "base64"); // 32B AES + 32B HMAC
+  const encKey = lk.subarray(0, 32);
+  const macKey = lk.subarray(32, 64);
+  const iv = buf.subarray(0, 16);
+  const mac = buf.subarray(buf.length - 32);
+  const body = buf.subarray(16, buf.length - 32);
+  const want = crypto.createHmac("sha256", macKey).update(buf.subarray(0, buf.length - 32)).digest();
+  if (!crypto.timingSafeEqual(want, mac)) return false; // tamper / wrong key
+  const dec = crypto.createDecipheriv("aes-256-cbc", encKey, iv);
+  dec.setAutoPadding(false);
+  let pt = Buffer.concat([dec.update(body), dec.final()]);
+  if (att.size) pt = pt.subarray(0, att.size); // strip bucket padding
+  writeFileSync(destPath, pt);
+  return true;
+}
+
+// ─── bell / state ────────────────────────────────────────────────────────────
+
+function loadState() {
+  try { return JSON.parse(readFileSync(STATE_PATH, "utf8")); } catch { return {}; }
+}
+function saveState(s) {
+  mkdirSync(STATE_DIR, { recursive: true });
+  writeFileSync(STATE_PATH, JSON.stringify(s, null, 2));
+}
+function ringBell(cfg) {
+  if (cfg.bellTty && existsSync(cfg.bellTty)) {
+    try { writeFileSync(cfg.bellTty, "\x07"); } catch {}
+  }
+  if (cfg.sound !== false) {
+    const snd = cfg.soundFile || "/System/Library/Sounds/Glass.aiff";
+    if (existsSync(snd)) spawnSync("/usr/bin/afplay", [snd], { stdio: "ignore" });
+  }
+}
+
+// ─── formatting ──────────────────────────────────────────────────────────────
+
+const clip = (s, n) => { s = String(s ?? ""); return s.length > n ? s.slice(0, n - 1) + "…" : s; };
+function humanAgo(ms) {
+  const s = Math.max(0, Math.floor((Date.now() - ms) / 1000));
+  if (s < 60) return `${s}s`;
+  if (s < 3600) return `${Math.floor(s / 60)}m`;
+  if (s < 86400) return `${Math.floor(s / 3600)}h`;
+  return `${Math.floor(s / 86400)}d`;
+}
+const arrow = (type) => (type === "outgoing" ? "→" : "←");
+function print(obj) { process.stdout.write(JSON.stringify(obj) + "\n"); }
+
+// ─── commands ────────────────────────────────────────────────────────────────
+
+function needConfig() {
+  ensureConfigStub();
+  console.error(`signal: not configured — edit ${CONFIG_PATH}`);
+  process.exit(2);
+}
+
+function cmdStatus() {
+  const cfg = loadConfig();
+  if (!cfg) { print({ configured: false, label: "Signal: setup" }); return; }
+  const convoId = resolveConversationId(cfg);
+  if (!convoId) { print({ configured: true, found: false, label: "Signal: ?" }); return; }
+
+  const unread = unreadInbound(convoId);
+  const last = recentMessages(convoId, 1)[0];
+  const maxRowid = maxInboundRowid(convoId);
+
+  const state = loadState();
+  const prev = state[convoId]?.lastInboundRowid || 0;
+  if (maxRowid > prev) {
+    if (prev !== 0) ringBell(cfg); // don't blast history on first run
+    state[convoId] = { lastInboundRowid: maxRowid };
+    saveState(state);
+  }
+
+  print({
+    configured: true,
+    found: true,
+    name: cfg.displayName,
+    unread,
+    label: unread > 0 ? `Signal: ${unread}` : "Signal",
+    last: last
+      ? { dir: last.type, text: clip(last.body || (last.hasAttachments ? "📎 attachment" : ""), 80), ago: humanAgo(last.sentAt) }
+      : null,
+  });
+}
+
+function cmdRead(n) {
+  const cfg = loadConfig() || needConfig();
+  const convoId = resolveConversationId(cfg);
+  if (!convoId) { console.error("signal: conversation not found"); process.exit(1); }
+  for (const m of recentMessages(convoId, n || 15)) {
+    const body = m.body || (m.hasAttachments ? "📎 attachment" : "");
+    console.log(`${arrow(m.type)} ${humanAgo(m.sentAt).padStart(3)}  ${body}`);
+  }
+}
+
+function cmdAttachments(n) {
+  const cfg = loadConfig() || needConfig();
+  const convoId = resolveConversationId(cfg);
+  if (!convoId) { console.error("signal: conversation not found"); process.exit(1); }
+  const atts = recentAttachments(convoId, n || 10);
+  atts.forEach((a, i) => {
+    console.log(
+      `[${i}] ${humanAgo(a.sentAt).padStart(3)}  ${(a.contentType || "?").padEnd(40)}  ` +
+        `${((a.size || 0) / 1024).toFixed(0)}K  ${a.fileName || "(unnamed)"}`,
+    );
+  });
+  if (!atts.length) console.log("(no downloaded attachments)");
+}
+
+function cmdSave(which) {
+  const cfg = loadConfig() || needConfig();
+  const convoId = resolveConversationId(cfg);
+  if (!convoId) { console.error("signal: conversation not found"); process.exit(1); }
+  const atts = recentAttachments(convoId, 30);
+  let picks;
+  if (which === "all") picks = atts;
+  else if (which === undefined || which === "latest") picks = atts.slice(0, 1);
+  else picks = [atts[Number(which)]].filter(Boolean);
+  if (!picks.length) { console.error("signal: nothing to save"); process.exit(1); }
+
+  mkdirSync(SAVE_DIR, { recursive: true });
+  const saved = [];
+  for (const a of picks) {
+    const name = (a.fileName || `${a.messageId}.bin`).replace(/[/:]/g, "_");
+    const dest = join(SAVE_DIR, name);
+    if (decryptAttachment(a, dest)) {
+      saved.push(dest);
+      console.log(dest);
+      // PDFs go straight to the slab viewer.
+      if ((a.contentType || "").includes("pdf") || /\.pdf$/i.test(name)) {
+        spawnSync(join(dirname(new URL(import.meta.url).pathname), "slab-pdf"), [dest], { stdio: "ignore" });
+      }
+    } else {
+      console.error(`signal: failed to decrypt ${name}`);
+    }
+  }
+  return saved;
+}
+
+async function cmdTail() {
+  const cfg = loadConfig() || needConfig();
+  const convoId = resolveConversationId(cfg);
+  if (!convoId) { console.error("signal: conversation not found"); process.exit(1); }
+  console.log(`— signal tail: ${cfg.displayName} (Ctrl-C to quit) —`);
+  for (const m of recentMessages(convoId, 10)) {
+    console.log(`${arrow(m.type)} ${m.body || (m.hasAttachments ? "📎 attachment" : "")}`);
+  }
+  let last = maxInboundRowid(convoId);
+  for (;;) {
+    await new Promise((r) => setTimeout(r, 3000));
+    const cur = maxInboundRowid(convoId);
+    if (cur > last) {
+      const fresh = sql(
+        `SELECT type, body, hasAttachments FROM messages WHERE conversationId=${sqlStr(convoId)} ` +
+          `AND type='incoming' AND rowid>${last} ORDER BY rowid ASC;`,
+      );
+      for (const m of fresh) {
+        process.stdout.write("\x07");
+        console.log(`← ${m.body || (m.hasAttachments ? "📎 attachment" : "")}`);
+      }
+      last = cur;
+    }
+  }
+}
+
+// ─── main ────────────────────────────────────────────────────────────────────
+
+const [cmd, arg] = process.argv.slice(2);
+try {
+  switch (cmd) {
+    case "status": cmdStatus(); break;
+    case "read": cmdRead(arg ? Number(arg) : 15); break;
+    case "attachments": case "atts": cmdAttachments(arg ? Number(arg) : 10); break;
+    case "save": cmdSave(arg); break;
+    case "tail": await cmdTail(); break;
+    case "open": spawnSync("/usr/bin/open", ["-a", "Signal"], { stdio: "ignore" }); break;
+    case "config": ensureConfigStub(); console.log(CONFIG_PATH); break;
+    default:
+      console.log("usage: signal status|read [N]|attachments [N]|save [N|all]|tail|open|config");
+  }
+} catch (e) {
+  if (cmd === "status") { print({ configured: !!loadConfig(), error: e.message }); }
+  else { console.error("signal:", e.message); process.exit(1); }
+}
diff --git a/slab/bin/slab-pdf b/slab/bin/slab-pdf
new file mode 100755
index 000000000..ebe71e05e
--- /dev/null
+++ b/slab/bin/slab-pdf
@@ -0,0 +1,51 @@
+#!/usr/bin/env bash
+# slab-pdf <file.pdf> [more.pdf …] — open PDFs in slab's minimal viewer.
+# Appends absolute paths to $SLAB_HOME/state/open-pdf; the menubar's 2 s
+# tick consumes the file and raises a chromeless PDFKit panel per document
+# (Esc closes, one "Preview" button escapes to Preview.app). Re-asking for
+# an open file just brings its window forward. See
+# slab/menubar-swift/Sources/SlabMenubar/PdfViewer.swift.
+set -euo pipefail
+
+SLAB_HOME="${SLAB_HOME:-$HOME/.local/share/slab}"
+REQUEST="$SLAB_HOME/state/open-pdf"
+
+if [ $# -eq 0 ]; then
+    echo "usage: slab-pdf <file.pdf> [more.pdf …]" >&2
+    exit 1
+fi
+
+mkdir -p "$SLAB_HOME/state"
+
+# Which Claude session asked? Walk up the process tree to the claude pid
+# (same loop as claude-prompt-log.sh) and match it against the live
+# active-prompts markers — the viewer chip then wears that session's
+# sticky emoji. Empty when not launched from a Claude session.
+session_id=""
+claude_pid=$$
+for _ in 1 2 3 4 5 6 7 8; do
+    parent=$(ps -o ppid= -p "$claude_pid" 2>/dev/null | tr -d ' ')
+    [ -z "$parent" ] || [ "$parent" = "1" ] && break
+    comm=$(ps -o comm= -p "$parent" 2>/dev/null | tr -d ' ')
+    claude_pid=$parent
+    case "$comm" in *claude*) break ;; esac
+done
+if command -v jq >/dev/null 2>&1; then
+    for marker in "$SLAB_HOME"/state/active-prompts/*; do
+        [ -f "$marker" ] || continue
+        if [ "$(jq -r '.claude_pid // 0' "$marker" 2>/dev/null)" = "$claude_pid" ]; then
+            session_id=$(jq -r '.session_id // ""' "$marker" 2>/dev/null)
+            break
+        fi
+    done
+fi
+
+for f in "$@"; do
+    if [ ! -f "$f" ]; then
+        echo "slab-pdf: no such file: $f" >&2
+        exit 1
+    fi
+    # realpath isn't guaranteed on stock macOS bash paths — resolve by hand.
+    abs="$(cd "$(dirname "$f")" && pwd)/$(basename "$f")"
+    printf '%s\t%s\n' "$abs" "$session_id" >> "$REQUEST"
+done
diff --git a/slab/bin/slab-video b/slab/bin/slab-video
new file mode 100755
index 000000000..4b9a3de41
--- /dev/null
+++ b/slab/bin/slab-video
@@ -0,0 +1,53 @@
+#!/usr/bin/env bash
+# slab-video <file.mp4> [more.mov …] — open videos in slab's minimal player.
+# Appends absolute paths to $SLAB_HOME/state/open-video; the menubar's 2 s
+# tick consumes the file and raises a chromeless AVKit panel per movie
+# (plays immediately; Esc closes, space toggles, one "QuickTime" button
+# escapes to QuickTime Player). Re-asking for an open file brings its
+# window forward and restarts playback. The panel watches the file and
+# reloads on rewrite, so render loops feel live. See
+# slab/menubar-swift/Sources/SlabMenubar/VideoViewer.swift.
+set -euo pipefail
+
+SLAB_HOME="${SLAB_HOME:-$HOME/.local/share/slab}"
+REQUEST="$SLAB_HOME/state/open-video"
+
+if [ $# -eq 0 ]; then
+    echo "usage: slab-video <file.mp4> [more.mov …]" >&2
+    exit 1
+fi
+
+mkdir -p "$SLAB_HOME/state"
+
+# Which Claude session asked? Walk up the process tree to the claude pid
+# (same loop as claude-prompt-log.sh) and match it against the live
+# active-prompts markers — the viewer chip then wears that session's
+# sticky emoji. Empty when not launched from a Claude session.
+session_id=""
+claude_pid=$$
+for _ in 1 2 3 4 5 6 7 8; do
+    parent=$(ps -o ppid= -p "$claude_pid" 2>/dev/null | tr -d ' ')
+    [ -z "$parent" ] || [ "$parent" = "1" ] && break
+    comm=$(ps -o comm= -p "$parent" 2>/dev/null | tr -d ' ')
+    claude_pid=$parent
+    case "$comm" in *claude*) break ;; esac
+done
+if command -v jq >/dev/null 2>&1; then
+    for marker in "$SLAB_HOME"/state/active-prompts/*; do
+        [ -f "$marker" ] || continue
+        if [ "$(jq -r '.claude_pid // 0' "$marker" 2>/dev/null)" = "$claude_pid" ]; then
+            session_id=$(jq -r '.session_id // ""' "$marker" 2>/dev/null)
+            break
+        fi
+    done
+fi
+
+for f in "$@"; do
+    if [ ! -f "$f" ]; then
+        echo "slab-video: no such file: $f" >&2
+        exit 1
+    fi
+    # realpath isn't guaranteed on stock macOS bash paths — resolve by hand.
+    abs="$(cd "$(dirname "$f")" && pwd)/$(basename "$f")"
+    printf '%s\t%s\n' "$abs" "$session_id" >> "$REQUEST"
+done
diff --git a/slab/menuband/tools/gm-audition.c b/slab/menuband/tools/gm-audition.c
new file mode 100644
index 000000000..5840ccb7f
--- /dev/null
+++ b/slab/menuband/tools/gm-audition.c
@@ -0,0 +1,176 @@
+// gm-audition.c — offline audition / static test of the AC-native GM synth.
+//
+// Renders every implemented General-MIDI program from the shared synthesis
+// core (fedac/native/src/gm_synth.c, the same engine Menu Band's "Use AC OS
+// MIDI" mode and AC OS itself play) as a short held C-major chord, back to
+// back, into ONE continuous 48 kHz stereo WAV. Prints a tracklist (timestamp →
+// instrument) and flags any program that comes out silent — the quick way to
+// hear the whole set and catch a broken/unstable voice without booting the app.
+//
+// Build + run:  cc -O2 gm-audition.c ../Sources/CGMSynth/gm_synth.c -lm -o /tmp/gm-audition
+//               /tmp/gm-audition  <output.wav>
+//
+// It is a TEST as much as a demo: exit code is non-zero if any program renders
+// silent or non-finite, so it can gate a synth-core change in CI.
+
+#include "gm_synth.h"
+#include <stdio.h>
+#include <stdlib.h>
+#include <string.h>
+#include <math.h>
+#include <stdint.h>
+
+static const char *GM_NAMES[128] = {
+    "Acoustic Grand Piano","Bright Acoustic Piano","Electric Grand Piano","Honky-tonk Piano",
+    "Electric Piano 1","Electric Piano 2","Harpsichord","Clavinet",
+    "Celesta","Glockenspiel","Music Box","Vibraphone",
+    "Marimba","Xylophone","Tubular Bells","Dulcimer",
+    "Drawbar Organ","Percussive Organ","Rock Organ","Church Organ",
+    "Reed Organ","Accordion","Harmonica","Tango Accordion",
+    "Acoustic Guitar (nylon)","Acoustic Guitar (steel)","Electric Guitar (jazz)","Electric Guitar (clean)",
+    "Electric Guitar (muted)","Overdriven Guitar","Distortion Guitar","Guitar Harmonics",
+    "Acoustic Bass","Electric Bass (finger)","Electric Bass (pick)","Fretless Bass",
+    "Slap Bass 1","Slap Bass 2","Synth Bass 1","Synth Bass 2",
+    "Violin","Viola","Cello","Contrabass",
+    "Tremolo Strings","Pizzicato Strings","Orchestral Harp","Timpani",
+    "String Ensemble 1","String Ensemble 2","Synth Strings 1","Synth Strings 2",
+    "Choir Aahs","Voice Oohs","Synth Choir","Orchestra Hit",
+    "Trumpet","Trombone","Tuba","Muted Trumpet",
+    "French Horn","Brass Section","Synth Brass 1","Synth Brass 2",
+    "Soprano Sax","Alto Sax","Tenor Sax","Baritone Sax",
+    "Oboe","English Horn","Bassoon","Clarinet",
+    "Piccolo","Flute","Recorder","Pan Flute",
+    "Blown Bottle","Shakuhachi","Whistle","Ocarina",
+    "Lead 1 (square)","Lead 2 (sawtooth)","Lead 3 (calliope)","Lead 4 (chiff)",
+    "Lead 5 (charang)","Lead 6 (voice)","Lead 7 (fifths)","Lead 8 (bass + lead)",
+    "Pad 1 (new age)","Pad 2 (warm)","Pad 3 (polysynth)","Pad 4 (choir)",
+    "Pad 5 (bowed)","Pad 6 (metallic)","Pad 7 (halo)","Pad 8 (sweep)",
+    "FX 1 (rain)","FX 2 (soundtrack)","FX 3 (crystal)","FX 4 (atmosphere)",
+    "FX 5 (brightness)","FX 6 (goblins)","FX 7 (echoes)","FX 8 (sci-fi)",
+    "Sitar","Banjo","Shamisen","Koto",
+    "Kalimba","Bagpipe","Fiddle","Shanai",
+    "Tinkle Bell","Agogo","Steel Drums","Woodblock",
+    "Taiko Drum","Melodic Tom","Synth Drum","Reverse Cymbal",
+    "Guitar Fret Noise","Breath Noise","Seashore","Bird Tweet",
+    "Telephone Ring","Helicopter","Applause","Gunshot",
+};
+
+#define SR        48000.0
+#define CHORD_N   4
+static const int CHORD[CHORD_N] = { 60, 64, 67, 72 };   // C4 E4 G4 C5
+
+// Per-program timing (seconds): attack, sustain-hold, release, trailing gap.
+#define T_ATTACK  0.006
+#define T_HOLD    1.30
+#define T_REL     0.45
+#define T_GAP     0.30
+
+static double midi_freq(int m) { return 440.0 * pow(2.0, (m - 69) / 12.0); }
+
+int main(int argc, char **argv) {
+    const char *out_path = (argc > 1) ? argv[1] : "gm-audition.wav";
+    gm_synth_init();
+
+    const int sr = (int)SR;
+    const long note_samps = (long)((T_HOLD + T_REL) * SR);
+    const long gap_samps  = (long)(T_GAP * SR);
+    const long prog_samps = note_samps + gap_samps;
+    const long rel_start  = (long)(T_HOLD * SR);
+    const double atk_inc  = 1.0 / (T_ATTACK * SR);
+    const double rel_dec  = 1.0 / (T_REL * SR);
+
+    // Count implemented programs up front to size the buffer.
+    int impl[128]; int n_impl = 0;
+    for (int p = 0; p < 128; p++) { impl[p] = gm_program_implemented(p) == 1; if (impl[p]) n_impl++; }
+
+    long total = prog_samps * n_impl;
+    double *mix = calloc((size_t)total, sizeof(double));   // mono master, normalized later
+    if (!mix) { fprintf(stderr, "out of memory (%ld samples)\n", total); return 2; }
+
+    int silent = 0, nonfinite = 0;
+    long cursor = 0;
+    printf("  time   GM   instrument                          peak\n");
+    printf("  -----  ---  ----------------------------------  ------\n");
+
+    for (int p = 0; p < 128; p++) {
+        if (!impl[p]) continue;
+        double sec = cursor / SR;
+
+        // One GMVoice per chord note; a shared AR envelope gates them together.
+        GMVoice v[CHORD_N];
+        for (int c = 0; c < CHORD_N; c++) {
+            uint32_t seed = (uint32_t)(p * 2654435761u + CHORD[c] * 40503u + 0x1234u);
+            gm_voice_init(&v[c], p, midi_freq(CHORD[c]), SR, seed);
+        }
+
+        double env = 0.0; int releasing = 0;
+        double peak = 0.0; long bad = 0;
+        for (long i = 0; i < note_samps; i++) {
+            if (i >= rel_start) releasing = 1;
+            if (releasing) { env -= rel_dec; if (env < 0) env = 0; }
+            else if (env < 1.0) { env += atk_inc; if (env > 1.0) env = 1.0; }
+
+            double s = 0.0;
+            for (int c = 0; c < CHORD_N; c++) {
+                double f = midi_freq(CHORD[c]);
+                double x = gm_voice_render(&v[c], SR, env, f);
+                if (!isfinite(x)) { bad++; x = 0.0; }
+                s += x;
+            }
+            s *= 0.28;                 // headroom for 4 summed voices
+            s = tanh(s);               // gentle safety saturation
+            if (cursor + i < total) mix[cursor + i] = s;
+            double a = fabs(s); if (a > peak) peak = a;
+        }
+
+        if (bad) nonfinite++;
+        double peak_db = peak > 1e-9 ? 20.0 * log10(peak) : -120.0;
+        int is_silent = peak < 0.001;
+        if (is_silent) silent++;
+        printf("  %2d:%05.2f  %3d  %-34s  %5.1f dB%s%s\n",
+               (int)(sec / 60), fmod(sec, 60.0), p, GM_NAMES[p], peak_db,
+               is_silent ? "  <SILENT>" : "", bad ? "  <NONFINITE>" : "");
+
+        cursor += prog_samps;          // note + trailing gap (gap stays zero)
+    }
+
+    // Normalize the whole file to -1 dBFS so quiet and loud voices are audible
+    // together without any clipping.
+    double gpeak = 0.0;
+    for (long i = 0; i < total; i++) { double a = fabs(mix[i]); if (a > gpeak) gpeak = a; }
+    double norm = gpeak > 1e-9 ? (0.891 / gpeak) : 1.0;   // 0.891 ≈ -1 dBFS
+
+    // ---- Write 16-bit stereo WAV (mono content duplicated L/R). ----
+    FILE *f = fopen(out_path, "wb");
+    if (!f) { fprintf(stderr, "cannot open %s\n", out_path); free(mix); return 2; }
+    long frames = total;
+    int channels = 2, bits = 16;
+    long data_bytes = frames * channels * (bits / 8);
+    long byte_rate = (long)sr * channels * (bits / 8);
+    uint16_t block_align = channels * (bits / 8);
+    uint32_t u32; uint16_t u16;
+    fwrite("RIFF", 1, 4, f); u32 = (uint32_t)(36 + data_bytes); fwrite(&u32, 4, 1, f);
+    fwrite("WAVE", 1, 4, f);
+    fwrite("fmt ", 1, 4, f); u32 = 16; fwrite(&u32, 4, 1, f);
+    u16 = 1; fwrite(&u16, 2, 1, f);                  // PCM
+    u16 = channels; fwrite(&u16, 2, 1, f);
+    u32 = sr; fwrite(&u32, 4, 1, f);
+    u32 = (uint32_t)byte_rate; fwrite(&u32, 4, 1, f);
+    fwrite(&block_align, 2, 1, f);
+    u16 = bits; fwrite(&u16, 2, 1, f);
+    fwrite("data", 1, 4, f); u32 = (uint32_t)data_bytes; fwrite(&u32, 4, 1, f);
+    for (long i = 0; i < frames; i++) {
+        double s = mix[i] * norm;
+        if (s > 1.0) s = 1.0; if (s < -1.0) s = -1.0;
+        int16_t v = (int16_t)lround(s * 32767.0);
+        fwrite(&v, 2, 1, f); fwrite(&v, 2, 1, f);    // L, R
+    }
+    fclose(f);
+    free(mix);
+
+    double dur = total / SR;
+    printf("\n  %d programs · %.1f s · %s\n", n_impl, dur, out_path);
+    if (silent)    printf("  WARNING: %d program(s) rendered SILENT\n", silent);
+    if (nonfinite) printf("  WARNING: %d program(s) hit NON-FINITE samples (trapped)\n", nonfinite);
+    return (silent || nonfinite) ? 1 : 0;
+}
diff --git a/slides/notepat-keymap/build-figure.fish b/slides/notepat-keymap/build-figure.fish
new file mode 100755
index 000000000..4424e94d7
--- /dev/null
+++ b/slides/notepat-keymap/build-figure.fish
@@ -0,0 +1,40 @@
+#!/usr/bin/env fish
+# Render the canonical notepat keymap FIGURE (paper variant) — piano +
+# QWERTY + connectors only, 2400×860 on white. No QR codes, no portrait,
+# no brand block. See figure.html.
+#
+# Output: slides/notepat-keymap/notepat-keymap-figure.png
+# Optional first arg: alternative output path.
+#
+# Deps: python3, Google Chrome.
+
+set -l here (dirname (status filename))
+set -l repo (realpath "$here/../..")
+set -l out (test -n "$argv[1]"; and echo $argv[1]; or echo "$here/notepat-keymap-figure.png")
+set -l tmp (mktemp -d)
+
+set -l template "$here/figure.html"
+set -l fonts "$repo/system/public/type/webfonts"
+
+echo "data:font/woff2;base64,"(base64 -i "$fonts/ywft-processing-bold.woff2") > "$tmp/ywft-bold.b64"
+echo "data:font/woff2;base64,"(base64 -i "$fonts/BerkeleyMonoVariable-Regular.woff2") > "$tmp/berkeley.b64"
+
+python3 -c "
+html = open('$template').read()
+for placeholder, path in [
+    ('__YWFT_BOLD__', '$tmp/ywft-bold.b64'),
+    ('__BERKELEY__', '$tmp/berkeley.b64'),
+]:
+    html = html.replace(placeholder, open(path).read().strip())
+open('$tmp/keymap-figure.html', 'w').write(html)
+"
+
+"/Applications/Google Chrome.app/Contents/MacOS/Google Chrome" \
+    --headless=new --no-sandbox --disable-gpu --hide-scrollbars \
+    --window-size=2400,860 \
+    --virtual-time-budget=500 \
+    --screenshot="$out" \
+    "file://$tmp/keymap-figure.html" 2>/dev/null
+
+rm -rf "$tmp"
+echo "wrote $out"
diff --git a/slides/notepat-keymap/figure.html b/slides/notepat-keymap/figure.html
new file mode 100644
index 000000000..889cc623c
--- /dev/null
+++ b/slides/notepat-keymap/figure.html
@@ -0,0 +1,433 @@
+<!doctype html>
+<html>
+<head>
+<meta charset="utf-8">
+<style>
+  /* Canonical paper-figure variant of the notepat keymap diagram.
+     Piano octaves + QWERTY + color-matched connectors ONLY — no title,
+     no rationale, no implementation list, no QR codes, no brand block.
+     Derived from template.html; key geometry must stay in sync with it. */
+  @font-face {
+    font-family: "Berkeley Mono";
+    src: url("__BERKELEY__") format("woff2");
+    font-weight: normal;
+    font-style: normal;
+  }
+  @font-face {
+    font-family: "YWFT Processing";
+    src: url("__YWFT_BOLD__") format("woff2");
+    font-weight: 800;
+    font-style: normal;
+  }
+
+  html, body { margin: 0; padding: 0; }
+  body {
+    width: 2400px;
+    height: 860px;
+    background: #ffffff;
+    color: #121012;
+    font-family: "YWFT Processing", -apple-system, "Helvetica Neue", sans-serif;
+    box-sizing: border-box;
+    padding: 36px 40px;
+    overflow: hidden;
+    display: flex;
+    flex-direction: column;
+    position: relative;
+  }
+  .connectors {
+    position: absolute;
+    inset: 0;
+    width: 2400px;
+    height: 860px;
+    pointer-events: none;
+    z-index: 50;
+  }
+
+  /* ---------------- Piano ---------------- */
+  .piano-wrap { display: flex; justify-content: center; margin-bottom: 26px; }
+  .piano {
+    position: relative;
+    height: 340px;
+    width: 2076px;
+    padding-left: 36px;
+    box-sizing: border-box;
+  }
+  .wkey, .bkey {
+    position: absolute;
+    box-sizing: border-box;
+    border-radius: 0 0 10px 10px;
+    border: 2px solid #121012;
+    display: flex;
+    flex-direction: column;
+    align-items: center;
+    justify-content: flex-end;
+    padding-bottom: 16px;
+  }
+  .wkey {
+    width: 120px;
+    height: 320px;
+    background: #fff;
+    color: #121012;
+    overflow: hidden;
+  }
+  .wkey .keyswatch {
+    position: absolute; left: 0; right: 0; bottom: 0;
+    height: 44px;
+    border-top: 2px solid rgba(0,0,0,0.22);
+  }
+  .wkey .qkey {
+    font-family: "Berkeley Mono", "SF Mono", monospace;
+    font-size: 64px;
+    font-weight: 800;
+    line-height: 1;
+    color: #121012;
+    position: absolute;
+    top: 96px; left: 0; right: 0;
+    text-align: center;
+  }
+  .wkey .nname {
+    position: absolute;
+    bottom: 60px; left: 0; right: 0;
+    text-align: center;
+    font-family: "Berkeley Mono", "SF Mono", monospace;
+    font-size: 22px;
+    color: #2a2a2a;
+    letter-spacing: 0.05em;
+    margin: 0;
+    font-weight: 700;
+    z-index: 2;
+  }
+  .wkey[data-pn="c"]  .keyswatch { background: #ff3232; }
+  .wkey[data-pn="d"]  .keyswatch { background: #ffa000; }
+  .wkey[data-pn="e"]  .keyswatch { background: #ffe600; }
+  .wkey[data-pn="f"]  .keyswatch { background: #32c832; }
+  .wkey[data-pn="g"]  .keyswatch { background: #3278ff; }
+  .wkey[data-pn="a"]  .keyswatch { background: #8232c8; }
+  .wkey[data-pn="b"]  .keyswatch { background: #b450ff; }
+  .wkey[data-pn="C5"] .keyswatch { background: #ff2850; }
+  .wkey[data-pn="D5"] .keyswatch { background: #ffb400; }
+  .wkey[data-pn="E5"] .keyswatch { background: #ffff32; }
+  .wkey[data-pn="F5"] .keyswatch { background: #32ff64; }
+  .wkey[data-pn="G5"] .keyswatch { background: #32c8ff; }
+  .wkey[data-pn="A5"] .keyswatch { background: #b432ff; }
+  .wkey[data-pn="B5"] .keyswatch { background: #ff50ff; }
+
+  .bkey {
+    width: 72px;
+    height: 210px;
+    background: #0a0a0a;
+    color: #fff;
+    border-color: #000;
+    z-index: 2;
+  }
+  .bkey .qkey {
+    font-family: "Berkeley Mono", "SF Mono", monospace;
+    font-size: 38px;
+    font-weight: 800;
+    line-height: 1;
+  }
+  .bkey .nname {
+    font-family: "Berkeley Mono", "SF Mono", monospace;
+    font-size: 16px;
+    color: #bbb;
+    letter-spacing: 0.05em;
+    margin-top: 6px;
+    font-weight: 700;
+  }
+
+  .wkey.ext { background: #fff4d6; color: #8a7330; border-color: #d4c075; opacity: 0.78; }
+  .wkey.ext .qkey { color: #8a7330; text-shadow: none; position: static; padding-top: 22px; }
+  .wkey.ext .keyswatch { display: none; }
+  .wkey.ext .nname { position: static; color: #a89855; text-shadow: none; font-size: 22px; font-weight: 700; }
+  .bkey.ext { background: #5a4818; color: #f8e7a0; border-color: #4a3814; opacity: 0.78; }
+  .bkey.ext .nname { color: #d8c878; }
+  .wkey.ext .ext-tag, .bkey.ext .ext-tag {
+    font-family: "Berkeley Mono", monospace;
+    font-size: 12px;
+    letter-spacing: 0.18em;
+    text-transform: uppercase;
+    margin-top: 4px;
+    opacity: 0.85;
+    font-weight: 700;
+  }
+
+  /* ---------------- QWERTY ---------------- */
+  .below { display: flex; justify-content: center; }
+  .below-left { flex: 0 0 1380px; display: flex; flex-direction: column; }
+
+  .hand-labels {
+    display: flex;
+    justify-content: space-between;
+    margin-bottom: 10px;
+    font-family: "YWFT Processing";
+    font-size: 22px;
+    letter-spacing: 0.22em;
+    text-transform: uppercase;
+    font-weight: 800;
+    padding: 0 24px;
+  }
+  .hand-labels .l { color: #2a64d4; }
+  .hand-labels .r { color: #c8324b; }
+  /* YWFT Processing has no arrow/middle-dot glyphs (renders as `&`); use
+     system font just for those characters so labels read correctly. */
+  .glyph {
+    font-family: -apple-system, "Helvetica Neue", "Arial Unicode MS", sans-serif;
+    font-weight: 800;
+  }
+
+  .qwerty-bg {
+    position: relative;
+    padding: 18px 20px;
+    border-radius: 16px;
+    background: linear-gradient(to right,
+      rgba(42, 100, 212, 0.10) 0%,
+      rgba(42, 100, 212, 0.10) 48%,
+      rgba(200, 50, 75, 0.10) 52%,
+      rgba(200, 50, 75, 0.10) 100%);
+    box-sizing: border-box;
+    display: flex;
+    align-items: center;
+  }
+  .qwerty-wrap { display: flex; flex-direction: column; align-items: flex-start; gap: 12px; width: 100%; }
+  .qrow { display: flex; gap: 12px; }
+  .qrow.r0 { padding-left: 0; }
+  .qrow.r1 { padding-left: 28px; }
+  .qrow.r2 { padding-left: 84px; }
+  .qcap {
+    width: 100px; height: 100px;
+    border-radius: 14px;
+    border: 3px solid #121012;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    font-family: "Berkeley Mono", "SF Mono", monospace;
+    font-size: 46px;
+    font-weight: 800;
+    text-transform: uppercase;
+    flex-shrink: 0;
+    box-shadow: 0 4px 0 rgba(0,0,0,0.18);
+  }
+  .qcap.white { background: #fff; color: #121012; }
+  .qcap.black { background: #121012; color: #fff; border-color: #000; }
+
+  .qcap[data-qn="c"]  { background: #ff3232; color: #fff; border-color: #a51c1c; text-shadow: 0 2px 0 rgba(0,0,0,0.22); }
+  .qcap[data-qn="d"]  { background: #ffa000; color: #fff; border-color: #b56b00; text-shadow: 0 2px 0 rgba(0,0,0,0.22); }
+  .qcap[data-qn="e"]  { background: #ffe600; color: #3a2a00; border-color: #b89c00; text-shadow: 0 2px 0 rgba(255,255,255,0.4); }
+  .qcap[data-qn="f"]  { background: #32c832; color: #fff; border-color: #1d7a1d; text-shadow: 0 2px 0 rgba(0,0,0,0.22); }
+  .qcap[data-qn="g"]  { background: #3278ff; color: #fff; border-color: #1c4ba8; text-shadow: 0 2px 0 rgba(0,0,0,0.22); }
+  .qcap[data-qn="a"]  { background: #8232c8; color: #fff; border-color: #4f1d80; text-shadow: 0 2px 0 rgba(0,0,0,0.22); }
+  .qcap[data-qn="b"]  { background: #b450ff; color: #fff; border-color: #6f2faa; text-shadow: 0 2px 0 rgba(0,0,0,0.22); }
+  .qcap[data-qn="C5"] { background: #ff2850; color: #fff; border-color: #b01a37; text-shadow: 0 2px 0 rgba(0,0,0,0.22); }
+  .qcap[data-qn="D5"] { background: #ffb400; color: #fff; border-color: #b58000; text-shadow: 0 2px 0 rgba(0,0,0,0.22); }
+  .qcap[data-qn="E5"] { background: #ffff32; color: #4a4400; border-color: #b8b400; text-shadow: 0 2px 0 rgba(255,255,255,0.4); }
+  .qcap[data-qn="F5"] { background: #32ff64; color: #0a3a14; border-color: #1a9a3a; text-shadow: 0 2px 0 rgba(255,255,255,0.35); }
+  .qcap[data-qn="G5"] { background: #32c8ff; color: #06283d; border-color: #1a7ab0; text-shadow: 0 2px 0 rgba(255,255,255,0.35); }
+  .qcap[data-qn="A5"] { background: #b432ff; color: #fff; border-color: #6f1cb0; text-shadow: 0 2px 0 rgba(0,0,0,0.22); }
+  .qcap[data-qn="B5"] { background: #ff50ff; color: #fff; border-color: #b02db0; text-shadow: 0 2px 0 rgba(0,0,0,0.22); }
+  .qcap.sharp { background: #121012; color: #fff; border-color: #000; }
+  .qcap.sharp[data-sharp-of="c"] { box-shadow: 0 4px 0 rgba(0,0,0,0.18), inset 0 0 0 2px rgba(255,50,50,0.55); }
+  .qcap.sharp[data-sharp-of="d"] { box-shadow: 0 4px 0 rgba(0,0,0,0.18), inset 0 0 0 2px rgba(255,160,0,0.55); }
+  .qcap.sharp[data-sharp-of="f"] { box-shadow: 0 4px 0 rgba(0,0,0,0.18), inset 0 0 0 2px rgba(50,200,50,0.55); }
+  .qcap.sharp[data-sharp-of="g"] { box-shadow: 0 4px 0 rgba(0,0,0,0.18), inset 0 0 0 2px rgba(50,120,255,0.55); }
+  .qcap.sharp[data-sharp-of="a"] { box-shadow: 0 4px 0 rgba(0,0,0,0.18), inset 0 0 0 2px rgba(130,50,200,0.55); }
+
+  .qcap.ext-white {
+    background: #fff4d6; color: #8a7330;
+    border-color: #d4c075;
+    opacity: 0.78;
+    flex-direction: column;
+  }
+  .qcap.ext-black {
+    background: #5a4818; color: #f8e7a0;
+    border-color: #4a3814;
+    opacity: 0.78;
+    flex-direction: column;
+  }
+  .qcap .ext-tag {
+    font-family: "Berkeley Mono", monospace;
+    font-size: 12px;
+    letter-spacing: 0.18em;
+    text-transform: uppercase;
+    margin-top: 5px;
+    opacity: 0.9;
+    font-weight: 700;
+  }
+  .qcap.ghost {
+    background: transparent;
+    color: #c8c8c8;
+    border: 2.5px dashed #d4d4d4;
+    font-weight: 600;
+    font-size: 30px;
+    box-shadow: none;
+  }
+  .qcap.octshift {
+    background: #f4ecff;
+    color: #6b3fc0;
+    border: 2.5px solid #b89df0;
+    font-weight: 800;
+    font-size: 26px;
+    flex-direction: column;
+  }
+  .qcap.octshift .lbl {
+    font-size: 13px;
+    letter-spacing: 0.1em;
+    opacity: 0.75;
+    margin-top: 3px;
+    font-family: "YWFT Processing";
+  }
+</style>
+</head>
+<body>
+  <!-- PIANO -->
+  <div class="piano-wrap">
+    <div class="piano">
+      <div class="wkey ext" style="left:36px;">   <div class="qkey">X</div><div class="nname">B3</div><div class="ext-tag">ext</div></div>
+      <div class="wkey" data-pn="c" style="left:156px;">  <div class="keyswatch"></div><div class="qkey">C</div><div class="nname">C4</div></div>
+      <div class="wkey" data-pn="d" style="left:276px;">  <div class="keyswatch"></div><div class="qkey">D</div><div class="nname">D4</div></div>
+      <div class="wkey" data-pn="e" style="left:396px;">  <div class="keyswatch"></div><div class="qkey">E</div><div class="nname">E4</div></div>
+      <div class="wkey" data-pn="f" style="left:516px;">  <div class="keyswatch"></div><div class="qkey">F</div><div class="nname">F4</div></div>
+      <div class="wkey" data-pn="g" style="left:636px;">  <div class="keyswatch"></div><div class="qkey">G</div><div class="nname">G4</div></div>
+      <div class="wkey" data-pn="a" style="left:756px;">  <div class="keyswatch"></div><div class="qkey">A</div><div class="nname">A4</div></div>
+      <div class="wkey" data-pn="b" style="left:876px;">  <div class="keyswatch"></div><div class="qkey">B</div><div class="nname">B4</div></div>
+      <div class="wkey" data-pn="C5" style="left:996px;"> <div class="keyswatch"></div><div class="qkey">H</div><div class="nname">C5</div></div>
+      <div class="wkey" data-pn="D5" style="left:1116px;"><div class="keyswatch"></div><div class="qkey">I</div><div class="nname">D5</div></div>
+      <div class="wkey" data-pn="E5" style="left:1236px;"><div class="keyswatch"></div><div class="qkey">J</div><div class="nname">E5</div></div>
+      <div class="wkey" data-pn="F5" style="left:1356px;"><div class="keyswatch"></div><div class="qkey">K</div><div class="nname">F5</div></div>
+      <div class="wkey" data-pn="G5" style="left:1476px;"><div class="keyswatch"></div><div class="qkey">L</div><div class="nname">G5</div></div>
+      <div class="wkey" data-pn="A5" style="left:1596px;"><div class="keyswatch"></div><div class="qkey">M</div><div class="nname">A5</div></div>
+      <div class="wkey" data-pn="B5" style="left:1716px;"><div class="keyswatch"></div><div class="qkey">N</div><div class="nname">B5</div></div>
+      <div class="wkey ext" style="left:1836px;"><div class="qkey">;</div><div class="nname">C6</div><div class="ext-tag">ext</div></div>
+      <div class="wkey ext" style="left:1956px;"><div class="qkey">]</div><div class="nname">D6</div><div class="ext-tag">ext</div></div>
+
+      <!-- Sharps -->
+      <div class="bkey ext" style="left:0px;">    <div class="qkey">Z</div><div class="nname">A♯3</div></div>
+      <div class="bkey" style="left:240px;">  <div class="qkey">V</div><div class="nname">C♯4</div></div>
+      <div class="bkey" style="left:360px;">  <div class="qkey">S</div><div class="nname">D♯4</div></div>
+      <div class="bkey" style="left:600px;">  <div class="qkey">W</div><div class="nname">F♯4</div></div>
+      <div class="bkey" style="left:720px;">  <div class="qkey">R</div><div class="nname">G♯4</div></div>
+      <div class="bkey" style="left:840px;">  <div class="qkey">Q</div><div class="nname">A♯4</div></div>
+      <div class="bkey" style="left:1080px;"> <div class="qkey">T</div><div class="nname">C♯5</div></div>
+      <div class="bkey" style="left:1200px;"> <div class="qkey">Y</div><div class="nname">D♯5</div></div>
+      <div class="bkey" style="left:1440px;"> <div class="qkey">U</div><div class="nname">F♯5</div></div>
+      <div class="bkey" style="left:1560px;"> <div class="qkey">O</div><div class="nname">G♯5</div></div>
+      <div class="bkey" style="left:1680px;"> <div class="qkey">P</div><div class="nname">A♯5</div></div>
+      <div class="bkey ext" style="left:1920px;"> <div class="qkey">'</div><div class="nname">C♯6</div></div>
+    </div>
+  </div>
+
+  <!-- QWERTY -->
+  <div class="below">
+    <div class="below-left">
+      <div class="hand-labels">
+        <div class="l"><span class="glyph">←</span> Left hand <span class="glyph">·</span> lower octave</div>
+        <div class="r">Right hand <span class="glyph">·</span> upper octave <span class="glyph">→</span></div>
+      </div>
+      <div class="qwerty-bg">
+        <div class="qwerty-wrap">
+          <div class="qrow r0">
+            <div class="qcap sharp" data-sharp-of="a">Q</div>
+            <div class="qcap sharp" data-sharp-of="f">W</div>
+            <div class="qcap" data-qn="e">E</div>
+            <div class="qcap sharp" data-sharp-of="g">R</div>
+            <div class="qcap sharp" data-sharp-of="c">T</div>
+            <div class="qcap sharp" data-sharp-of="d">Y</div>
+            <div class="qcap sharp" data-sharp-of="f">U</div>
+            <div class="qcap" data-qn="D5">I</div>
+            <div class="qcap sharp" data-sharp-of="g">O</div>
+            <div class="qcap sharp" data-sharp-of="a">P</div>
+            <div class="qcap ghost">[</div>
+            <div class="qcap ext-white">]<div class="ext-tag">ext</div></div>
+          </div>
+          <div class="qrow r1">
+            <div class="qcap" data-qn="a">A</div>
+            <div class="qcap sharp" data-sharp-of="d">S</div>
+            <div class="qcap" data-qn="d">D</div>
+            <div class="qcap" data-qn="f">F</div>
+            <div class="qcap" data-qn="g">G</div>
+            <div class="qcap" data-qn="C5">H</div>
+            <div class="qcap" data-qn="E5">J</div>
+            <div class="qcap" data-qn="F5">K</div>
+            <div class="qcap" data-qn="G5">L</div>
+            <div class="qcap ext-white">;<div class="ext-tag">ext</div></div>
+            <div class="qcap ext-black">'<div class="ext-tag">ext</div></div>
+          </div>
+          <div class="qrow r2">
+            <div class="qcap ext-black">Z<div class="ext-tag">ext</div></div>
+            <div class="qcap ext-white">X<div class="ext-tag">ext</div></div>
+            <div class="qcap" data-qn="c">C</div>
+            <div class="qcap sharp" data-sharp-of="c">V</div>
+            <div class="qcap" data-qn="b">B</div>
+            <div class="qcap" data-qn="A5">N</div>
+            <div class="qcap" data-qn="B5">M</div>
+            <div class="qcap octshift">,<div class="lbl">oct−</div></div>
+            <div class="qcap octshift">.<div class="lbl">oct+</div></div>
+            <div class="qcap ghost">/</div>
+          </div>
+        </div>
+      </div>
+    </div>
+  </div>
+
+  <!-- Connector overlay: piano white key → QWERTY note cap, color-matched -->
+  <svg class="connectors" id="connectors"></svg>
+
+  <script>
+    document.fonts.ready.then(() => {
+      drawConnectors();
+    });
+
+    function drawConnectors() {
+      const svg = document.getElementById("connectors");
+      const naturals = [
+        { pn: "c", qn: "c", color: "#ff3232", op: 0.85 },
+        { pn: "d", qn: "d", color: "#ffa000", op: 0.65 },
+        { pn: "e", qn: "e", color: "#d4b400", op: 0.55 },
+        { pn: "f", qn: "f", color: "#32c832", op: 0.50 },
+        { pn: "g", qn: "g", color: "#3278ff", op: 0.45 },
+        { pn: "a", qn: "a", color: "#8232c8", op: 0.40 },
+        { pn: "b", qn: "b", color: "#b450ff", op: 0.35 },
+        { pn: "C5", qn: "C5", color: "#ff2850", op: 0.55 },
+        { pn: "D5", qn: "D5", color: "#ffb400", op: 0.45 },
+        { pn: "E5", qn: "E5", color: "#b8b400", op: 0.40 },
+        { pn: "F5", qn: "F5", color: "#32ff64", op: 0.40 },
+        { pn: "G5", qn: "G5", color: "#32c8ff", op: 0.40 },
+        { pn: "A5", qn: "A5", color: "#b432ff", op: 0.35 },
+        { pn: "B5", qn: "B5", color: "#ff50ff", op: 0.32 },
+      ];
+      const NS = "http://www.w3.org/2000/svg";
+      for (const { pn, qn, color, op } of naturals) {
+        const piano = document.querySelector(`.wkey[data-pn="${pn}"]`);
+        const qwerty = document.querySelector(`.qcap[data-qn="${qn}"]`);
+        if (!piano || !qwerty) continue;
+        const pr = piano.getBoundingClientRect();
+        const qr = qwerty.getBoundingClientRect();
+        const x1 = pr.left + pr.width / 2;
+        const y1 = pr.bottom - 12;
+        const x2 = qr.left + qr.width / 2;
+        const y2 = qr.top + 12;
+        const line = document.createElementNS(NS, "line");
+        line.setAttribute("x1", x1);
+        line.setAttribute("y1", y1);
+        line.setAttribute("x2", x2);
+        line.setAttribute("y2", y2);
+        line.setAttribute("stroke", color);
+        line.setAttribute("stroke-width", "4");
+        line.setAttribute("stroke-dasharray", "10 8");
+        line.setAttribute("stroke-linecap", "round");
+        line.setAttribute("opacity", op);
+        svg.appendChild(line);
+        const dotOp = Math.min(0.7, op * 0.8);
+        for (const [cx, cy] of [[x1, y1], [x2, y2]]) {
+          const dot = document.createElementNS(NS, "circle");
+          dot.setAttribute("cx", cx);
+          dot.setAttribute("cy", cy);
+          dot.setAttribute("r", 5);
+          dot.setAttribute("fill", color);
+          dot.setAttribute("opacity", dotOp);
+          svg.appendChild(dot);
+        }
+      }
+    }
+  </script>
+</body>
+</html>
diff --git a/slides/notepat-keymap/notepat-keymap-figure.png b/slides/notepat-keymap/notepat-keymap-figure.png
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HcmV?d00001

diff --git a/system/public/aesthetic.computer/disks/dj.mjs b/system/public/aesthetic.computer/disks/dj.mjs
new file mode 100644
index 000000000..b87481e55
--- /dev/null
+++ b/system/public/aesthetic.computer/disks/dj.mjs
@@ -0,0 +1,422 @@
+// DJ, 2026.6.10
+// One big record. Drop an audio file on the window (ac-electron) and
+// scratch it. Ported from the AC Native turntable piece.
+// Usage: dj [url|track-name] — or drag an mp3 into the app.
+
+const STREAM_ID = "dj";
+const CDN = "https://assets.aesthetic.computer";
+const SECS_PER_ROT = 1.8; // 33⅓ rpm — one platter rotation of audio
+
+// Palette
+const BG = [16, 12, 24];
+const PLATTER = [28, 24, 40];
+const RIM = [80, 68, 110];
+const BAR = [40, 32, 58];
+const ACCENT = [0, 255, 200];
+const OK = [0, 200, 160];
+const WARN = [255, 180, 80];
+const FG = 210;
+const DIM = 80;
+
+// Track + transport
+let audioUrl = null,
+  trackTitle = "";
+let isPlaying = false,
+  isLoading = false,
+  hasStarted = false;
+let currentTime = 0,
+  duration = 0,
+  bufferedTime = 0;
+let pitch = 1; // resting speed (pitch fader)
+let liveSpeed = 1; // last applied playback rate (display)
+let volume = 0.8;
+let peaks = null; // whole-track overview (0..1) or null while decoding
+
+// Platter
+let angle = -Math.PI / 2;
+let frame = 0,
+  message = "",
+  messageFrame = 0;
+
+// Scratch (radial drag around the platter). The stream backend can't run
+// in reverse, so forward drags are audible (playbackRate) and backward
+// drags scrub silently via seeks — vinyl-ish, within HTMLMediaElement law.
+let scratching = false;
+let scratchLast = { x: 0, y: 0 };
+let wasPlayingBeforeScratch = false;
+let scratchAudible = false; // engine currently running for the scratch
+let scratchTime = 0; // predicted position while seeking backward
+
+// Layout (computed in paint, hit-tested in act)
+let buttons = [];
+let strip = null; // waveform scrub strip box
+let stripScrub = false;
+let platterC = { x: 0, y: 0, r: 0 };
+
+function msg(t) {
+  message = t;
+  messageFrame = frame;
+}
+
+function fmt(s) {
+  if (!Number.isFinite(s) || s < 0) return "0:00";
+  return `${Math.floor(s / 60)}:${String(Math.floor(s % 60)).padStart(2, "0")}`;
+}
+
+function load(send, { url, name }) {
+  if (hasStarted) send({ type: "stream:stop", content: { id: STREAM_ID } });
+  audioUrl = url;
+  trackTitle = (name || url.split("/").pop() || "track").replace(/\.[^.]+$/, "");
+  isPlaying = false;
+  hasStarted = false;
+  currentTime = 0;
+  duration = 0;
+  bufferedTime = 0;
+  pitch = 1;
+  liveSpeed = 1;
+  peaks = null;
+  isLoading = true;
+  send({ type: "stream:play", content: { id: STREAM_ID, url, volume } });
+  send({ type: "stream:peaks", content: { id: STREAM_ID, url, count: 1024 } });
+  msg(trackTitle);
+}
+
+function boot({ params, send, hud, system }) {
+  hud.label();
+  // ac-electron drag-drop takes priority — disk.mjs stashes the loopback
+  // url on system.droppedFile and jumps here.
+  const dropped = system?.droppedFile;
+  if (dropped?.url) {
+    load(send, dropped);
+    if (system) system.droppedFile = null;
+    return;
+  }
+  if (params[0]) {
+    const key = params[0];
+    const url = key.startsWith("http") ? key : `${CDN}/audio/${key}.mp3`;
+    load(send, { url, name: key.split("/").pop() });
+  }
+}
+
+function setSpeed(send, s) {
+  liveSpeed = s;
+  send({ type: "stream:speed", content: { id: STREAM_ID, speed: s } });
+}
+
+function togglePlay(send) {
+  if (isLoading || !audioUrl) return;
+  if (isPlaying) {
+    send({ type: "stream:pause", content: { id: STREAM_ID } });
+  } else if (hasStarted) {
+    setSpeed(send, pitch);
+    send({ type: "stream:resume", content: { id: STREAM_ID } });
+  } else {
+    isLoading = true;
+    send({ type: "stream:play", content: { id: STREAM_ID, url: audioUrl, volume } });
+  }
+}
+
+function nudgePitch(send, d) {
+  pitch = Math.min(3, Math.max(0.25, pitch + d));
+  if (isPlaying || scratching) setSpeed(send, pitch);
+  else liveSpeed = pitch;
+  msg(`${pitch.toFixed(2)}x`);
+}
+
+function act({ event: e, send, system }) {
+  // A drop while dj is already running swaps the record.
+  if (e.is("dropped:file") && system?.droppedFile?.url) {
+    load(send, system.droppedFile);
+    system.droppedFile = null;
+    return;
+  }
+
+  if (e.is("touch")) {
+    // Buttons
+    for (const b of buttons) {
+      if (e.x >= b.x && e.x <= b.x + b.w && e.y >= b.y && e.y <= b.y + b.h) {
+        if (b.id === "play") togglePlay(send);
+        else if (b.id === "slower") nudgePitch(send, -0.05);
+        else if (b.id === "faster") nudgePitch(send, 0.05);
+        else if (b.id === "reset") {
+          pitch = 1;
+          if (isPlaying) setSpeed(send, 1);
+          else liveSpeed = 1;
+          msg("1.00x");
+        }
+        return;
+      }
+    }
+    // Waveform strip → needle drop
+    if (strip && duration > 0 && e.x >= strip.x && e.x <= strip.x + strip.w &&
+        e.y >= strip.y && e.y <= strip.y + strip.h) {
+      stripScrub = true;
+      const t = ((e.x - strip.x) / strip.w) * duration;
+      send({ type: "stream:seek", content: { id: STREAM_ID, time: t } });
+      return;
+    }
+    // Platter → start scratching
+    const dx = e.x - platterC.x,
+      dy = e.y - platterC.y;
+    if (duration > 0 && Math.sqrt(dx * dx + dy * dy) <= platterC.r + 8) {
+      scratching = true;
+      scratchLast = { x: e.x, y: e.y };
+      wasPlayingBeforeScratch = isPlaying;
+      scratchAudible = isPlaying;
+      scratchTime = currentTime;
+    }
+    return;
+  }
+
+  if (e.is("draw")) {
+    if (stripScrub && strip && duration > 0) {
+      const t = (Math.min(Math.max(e.x - strip.x, 0), strip.w) / strip.w) * duration;
+      send({ type: "stream:seek", content: { id: STREAM_ID, time: t } });
+      return;
+    }
+    if (scratching) {
+      const prev = Math.atan2(scratchLast.y - platterC.y, scratchLast.x - platterC.x);
+      const cur = Math.atan2(e.y - platterC.y, e.x - platterC.x);
+      let delta = cur - prev;
+      if (delta > Math.PI) delta -= Math.PI * 2;
+      if (delta < -Math.PI) delta += Math.PI * 2;
+      angle += delta;
+      scratchLast = { x: e.x, y: e.y };
+      const rate = delta * 8; // sensitivity — matches the native piece
+      if (rate >= 0.0625) {
+        // Forward: audible, pitch bends with speed.
+        setSpeed(send, Math.min(4, rate));
+        if (!scratchAudible) {
+          send({ type: "stream:resume", content: { id: STREAM_ID } });
+          scratchAudible = true;
+        }
+        scratchTime = currentTime;
+      } else {
+        // Held still or dragged backward: hold the record (silence) and
+        // wind position by rotation.
+        if (scratchAudible) {
+          send({ type: "stream:pause", content: { id: STREAM_ID } });
+          scratchAudible = false;
+        }
+        if (rate < 0) {
+          scratchTime = Math.min(
+            duration,
+            Math.max(0, scratchTime + (delta / (Math.PI * 2)) * SECS_PER_ROT),
+          );
+          send({ type: "stream:seek", content: { id: STREAM_ID, time: scratchTime } });
+        }
+      }
+      return;
+    }
+  }
+
+  if (e.is("lift")) {
+    if (scratching) {
+      setSpeed(send, pitch);
+      if (wasPlayingBeforeScratch) {
+        send({ type: "stream:resume", content: { id: STREAM_ID } });
+      } else if (scratchAudible) {
+        send({ type: "stream:pause", content: { id: STREAM_ID } });
+      }
+      scratching = false;
+      scratchAudible = false;
+    }
+    stripScrub = false;
+    return;
+  }
+
+  if (e.is("keyboard:down:space")) togglePlay(send);
+  if (e.is("keyboard:down:arrowleft")) nudgePitch(send, -0.05);
+  if (e.is("keyboard:down:arrowright")) nudgePitch(send, 0.05);
+  if (e.is("keyboard:down:arrowup") && duration > 0)
+    send({ type: "stream:seek", content: { id: STREAM_ID, time: Math.min(duration, currentTime + 10) } });
+  if (e.is("keyboard:down:arrowdown") && duration > 0)
+    send({ type: "stream:seek", content: { id: STREAM_ID, time: Math.max(0, currentTime - 10) } });
+  if (e.is("keyboard:down:-")) {
+    volume = Math.max(0, volume - 0.05);
+    send({ type: "stream:volume", content: { id: STREAM_ID, volume } });
+    msg(`vol ${Math.round(volume * 100)}`);
+  }
+  if (e.is("keyboard:down:=")) {
+    volume = Math.min(1, volume + 0.05);
+    send({ type: "stream:volume", content: { id: STREAM_ID, volume } });
+    msg(`vol ${Math.round(volume * 100)}`);
+  }
+  if (e.is("keyboard:down:z")) {
+    pitch = 1;
+    if (isPlaying) setSpeed(send, 1);
+    else liveSpeed = 1;
+    msg("1.00x");
+  }
+}
+
+function sim({ send }) {
+  if (!audioUrl) return;
+  send({ type: "stream:time", content: { id: STREAM_ID } });
+}
+
+function paint({ wipe, ink, box, line, circle, write, screen }) {
+  frame++;
+  const w = screen.width,
+    h = screen.height;
+  const CW = 6; // font_1 advance
+  wipe(...BG);
+
+  // --- Platter ---
+  const cx = Math.floor(w / 2);
+  const cy = Math.floor(h / 2) - 10;
+  const r = Math.min(cx - 8, cy - 16);
+  platterC = { x: cx, y: cy, r };
+
+  if (isPlaying && !scratching) angle += liveSpeed * 0.05;
+
+  ink(...PLATTER);
+  circle(cx, cy, r, true);
+  for (let g = Math.floor(r * 0.3); g < r; g += 3) {
+    const b = scratching ? 14 : 8;
+    ink(PLATTER[0] + b, PLATTER[1] + b, PLATTER[2] + b + 4);
+    circle(cx, cy, g);
+  }
+  ink(...RIM);
+  circle(cx, cy, r);
+
+  // Label
+  const labelR = Math.floor(r * 0.25);
+  ink(PLATTER[0] + 26, PLATTER[1] + 14, PLATTER[2] + 8);
+  circle(cx, cy, labelR, true);
+  ink(PLATTER[0] + 50, PLATTER[1] + 32, PLATTER[2] + 28);
+  circle(cx, cy, labelR);
+  ink(...ACCENT);
+  circle(cx, cy, 3, true);
+
+  // Needle
+  const nx = cx + Math.cos(angle) * (r - 6);
+  const ny = cy + Math.sin(angle) * (r - 6);
+  const nc = isPlaying ? OK : [DIM, DIM, DIM];
+  ink(...nc);
+  line(cx, cy, Math.floor(nx), Math.floor(ny));
+  ink(nc[0] + 40, nc[1] + 40, nc[2] + 40);
+  circle(Math.floor(nx), Math.floor(ny), Math.max(2, Math.floor(r * 0.04)), true);
+
+  // --- Track info ---
+  const maxC = Math.floor(w / CW) - 2;
+  if (audioUrl) {
+    ink(FG, FG, FG).write(trackTitle.slice(0, maxC), { x: 4, y: 3 });
+  } else {
+    ink(FG, FG, FG).write("drop an audio file", { center: "x", screen, y: cy - 4 });
+    ink(DIM, DIM, DIM).write("or: dj:https://url.mp3", { center: "x", screen, y: cy + 8 });
+  }
+
+  // --- Waveform strip + playhead ---
+  const barY = h - 34;
+  const barW = w - 8;
+  strip = { x: 4, y: barY - 10, w: barW, h: 24 };
+  const progress = duration > 0 ? currentTime / duration : 0;
+  const playedX = 4 + Math.floor(barW * progress);
+  if (peaks && peaks.length > 0) {
+    const cyW = barY + 2,
+      HH = 11;
+    const pb = isPlaying ? OK : [DIM + 30, DIM + 30, DIM + 30];
+    for (let x = 0; x < barW; x++) {
+      const pk = peaks[Math.floor((x / barW) * peaks.length)] || 0;
+      const colH = Math.max(1, Math.floor(pk * HH));
+      if (4 + x < playedX) ink(...pb);
+      else ink(...BAR);
+      box(4 + x, cyW - colH, 1, colH * 2);
+    }
+    ink(...ACCENT);
+    box(Math.min(4 + barW - 1, playedX), cyW - HH, 1, HH * 2);
+  } else if (audioUrl) {
+    // Peaks still decoding (or CORS-blocked) — thin progress bar.
+    ink(...BAR);
+    box(4, barY, barW, 4);
+    if (duration > 0) {
+      ink(...(isPlaying ? OK : [DIM, DIM + 20, DIM]));
+      box(4, barY, Math.max(1, playedX - 4), 4);
+    }
+    if (bufferedTime > 0 && duration > 0) {
+      ink(BAR[0] + 20, BAR[1] + 20, BAR[2] + 20);
+      box(playedX, barY, Math.floor(barW * (bufferedTime / duration)) - (playedX - 4), 4);
+    }
+  }
+
+  // Time + speed
+  ink(DIM + 40, DIM + 40, DIM + 50).write(`${fmt(currentTime)} / ${fmt(duration)}`, { x: 4, y: barY + 7 });
+  if (audioUrl) {
+    const spd = `${liveSpeed.toFixed(2)}x`;
+    write(spd, { x: w - spd.length * CW - 4, y: barY + 7 });
+  }
+
+  // --- Button row ---
+  buttons = [];
+  const btnY = h - 14,
+    btnH = 12,
+    gap = 3;
+  const btnDefs = [
+    { id: "slower", label: "-" },
+    { id: "play", label: isLoading ? "..." : isPlaying ? "Pause" : "Play" },
+    { id: "faster", label: "+" },
+    { id: "reset", label: "1x" },
+  ];
+  const btnW = Math.floor((w - 8 - gap * (btnDefs.length - 1)) / btnDefs.length);
+  for (let i = 0; i < btnDefs.length; i++) {
+    const bx = 4 + i * (btnW + gap);
+    const bd = btnDefs[i];
+    buttons.push({ x: bx, y: btnY, w: btnW, h: btnH, id: bd.id });
+    ink(...BAR);
+    box(bx, btnY, btnW, btnH);
+    ink(...RIM);
+    box(bx, btnY, btnW, btnH, "outline");
+    ink(FG, FG, FG).write(bd.label, {
+      x: bx + Math.floor((btnW - bd.label.length * CW) / 2),
+      y: btnY + 2,
+    });
+  }
+
+  if (scratching) {
+    ink(...ACCENT).write("SCRATCH", { x: cx - 21, y: cy - 5 });
+  }
+
+  // Message toast
+  if (message && frame - messageFrame < 120) {
+    const fade = Math.max(0, 255 - Math.floor((frame - messageFrame) * 2.5));
+    ink(WARN[0], WARN[1], WARN[2], fade).write(message.slice(0, maxC), { x: 4, y: 16 });
+  }
+}
+
+function receive({ type, content }) {
+  if (content?.id !== STREAM_ID) return;
+  if (type === "stream:playing") {
+    isPlaying = true;
+    isLoading = false;
+    hasStarted = true;
+  }
+  if (type === "stream:paused") isPlaying = false;
+  if (type === "stream:stopped") {
+    isPlaying = false;
+    hasStarted = false;
+  }
+  if (type === "stream:error") {
+    isPlaying = false;
+    isLoading = false;
+    msg("stream error");
+  }
+  if (type === "stream:time-data") {
+    currentTime = content.currentTime;
+    duration = content.duration;
+    bufferedTime = content.buffered;
+    if (content.ended && hasStarted) isPlaying = false;
+  }
+  if (type === "stream:seeked") {
+    currentTime = content.time;
+    if (!scratching) scratchTime = content.time;
+  }
+  if (type === "stream:speed-data") liveSpeed = content.speed;
+  if (type === "stream:peaks-data" && content.peaks?.length) peaks = content.peaks;
+}
+
+function leave({ send }) {
+  send({ type: "stream:stop", content: { id: STREAM_ID } });
+}
+
+export { boot, paint, act, sim, receive, leave };
diff --git a/toolchain/macos/iphone-tap/README.md b/toolchain/macos/iphone-tap/README.md
new file mode 100644
index 000000000..db763d112
--- /dev/null
+++ b/toolchain/macos/iphone-tap/README.md
@@ -0,0 +1,58 @@
+# iphone-tap
+
+A tiny macOS CLI that gives scripts **eyes and hands** on a real iPhone through
+the system **iPhone Mirroring** app. It's the reusable primitive under in-house
+iPhone automations — the first being Instagram grid archiving
+(`portraits/jeffrey/bin/ig-archive-mirror.mjs`).
+
+The tap + window-frame code is lifted from **YergerSnap** (`slab/yergersnap`),
+which has driven Julia Yerger's stop-motion rig in production. This version adds
+screen capture and on-device OCR so a caller can *see* the screen, not tap blind.
+
+## Build
+
+```bash
+toolchain/macos/iphone-tap/build.sh
+```
+
+Unsigned, local-use. Grant the **terminal app that runs it** two permissions
+(System Settings → Privacy & Security):
+
+- **Accessibility** — read window frames + inject clicks (`frame`, `tap`)
+- **Screen Recording** — capture pixels (`shot`)
+
+## Commands (all print JSON)
+
+| Command | Result |
+|---|---|
+| `iphone-tap frame [--window NAME]` | `{x,y,w,h}` window bounds (points) |
+| `iphone-tap shot OUT.png [--window NAME]` | captures the window region to PNG |
+| `iphone-tap ocr IN.png` | `{w,h,lines:[{text,conf,x,y,w,h}]}` — coords normalized **0–1, top-left** |
+| `iphone-tap tap FX FY [--window NAME] [--no-activate]` | click at fraction `(FX,FY)` of the window |
+
+OCR coordinates drop straight into `tap` — find a control's box, tap its center.
+
+Default `--window` is `"iPhone Mirroring"`. Errors print `{"error":"..."}` and
+exit non-zero so callers can branch.
+
+## The black-capture gotcha
+
+iPhone Mirroring often **captures as solid black** (Continuity privacy). Two ways
+through, in order of preference:
+
+1. **Grant Screen Recording** to the terminal — on recent macOS this is often
+   enough for a real capture.
+2. If it's still black, open a **QuickTime → File → New Movie Recording** with the
+   iPhone (over USB) as the source. That window captures fine. Point `shot`/`ocr`
+   at it with `--window "Movie Recording"` for *reading*, while `tap` still drives
+   the interactive `"iPhone Mirroring"` window. Both are scaled views of the same
+   phone screen, so a fraction found in one maps directly to the other.
+
+## Smoke test
+
+```bash
+# open iPhone Mirroring first
+./iphone-tap frame
+./iphone-tap shot /tmp/phone.png && open /tmp/phone.png   # not black?
+./iphone-tap ocr /tmp/phone.png                            # finds on-screen text?
+```
diff --git a/toolchain/macos/iphone-tap/build.sh b/toolchain/macos/iphone-tap/build.sh
new file mode 100755
index 000000000..81793c1cf
--- /dev/null
+++ b/toolchain/macos/iphone-tap/build.sh
@@ -0,0 +1,22 @@
+#!/usr/bin/env bash
+# Build the iphone-tap CLI. Unsigned, local-use only — it needs Accessibility
+# (to read window frames + inject clicks) and Screen Recording (for `shot`)
+# permissions granted to whatever terminal runs it.
+set -euo pipefail
+cd "$(dirname "$0")"
+
+swiftc -O -o iphone-tap main.swift \
+  -framework Cocoa \
+  -framework ApplicationServices \
+  -framework Vision
+
+echo "✓ built ./iphone-tap"
+echo
+echo "First run will need permissions for your terminal app:"
+echo "  • System Settings → Privacy & Security → Accessibility   (tap + frame)"
+echo "  • System Settings → Privacy & Security → Screen Recording (shot)"
+echo
+echo "Smoke test (open iPhone Mirroring first):"
+echo "  ./iphone-tap frame"
+echo "  ./iphone-tap shot /tmp/phone.png && open /tmp/phone.png"
+echo "  ./iphone-tap ocr /tmp/phone.png"
diff --git a/toolchain/macos/iphone-tap/iphone-tap b/toolchain/macos/iphone-tap/iphone-tap
new file mode 100755
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diff --git a/toolchain/macos/iphone-tap/main.swift b/toolchain/macos/iphone-tap/main.swift
new file mode 100644
index 000000000..073c45ac6
--- /dev/null
+++ b/toolchain/macos/iphone-tap/main.swift
@@ -0,0 +1,311 @@
+// iphone-tap — a tiny macOS CLI for driving the iPhone Mirroring window.
+//
+// It is the reusable "hands and eyes" primitive underneath higher-level
+// iPhone automations (the first of which is Instagram grid archiving). The
+// tap + window-frame code is lifted straight from YergerSnap (slab/yergersnap),
+// which has driven Julia Yerger's stop-motion rig in production; this version
+// adds screen capture (`shot`) and on-device OCR (`ocr`) so an orchestrator
+// can SEE the screen, not just tap blindly.
+//
+// Commands (all print JSON to stdout):
+//
+//   iphone-tap frame [--window NAME]
+//       → {"x":..,"y":..,"w":..,"h":..}  window bounds in screen points
+//
+//   iphone-tap shot OUT.png [--window NAME]
+//       → {"x":..,"y":..,"w":..,"h":..,"path":"OUT.png"}
+//       Captures the window's region to a PNG. NOTE: iPhone Mirroring may
+//       capture as solid black (Continuity privacy). If so, point --window
+//       at a QuickTime "Movie Recording" of the phone instead — the frame
+//       maths are identical because both are scaled views of one screen.
+//
+//   iphone-tap ocr IN.png
+//       → {"w":W,"h":H,"lines":[{"text":..,"conf":..,"x":..,"y":..,"w":..,"h":..}]}
+//       Coordinates are normalized [0,1] with a TOP-LEFT origin, relative to
+//       the image — so they drop straight into `tap FX FY`.
+//
+//   iphone-tap tap FX FY [--window NAME] [--no-activate]
+//       Clicks at fractional (FX,FY) of the window. Restores the cursor and
+//       prior frontmost app, exactly like YergerSnap, so it stays invisible.
+//
+// Default --window is "iPhone Mirroring". Exit code is non-zero on any error,
+// with a JSON {"error":"..."} on stdout, so callers can branch cleanly.
+
+import Cocoa
+import ApplicationServices
+import Vision
+
+// ---- output helpers ------------------------------------------------------
+
+func emit(_ obj: [String: Any]) {
+  let data = try! JSONSerialization.data(withJSONObject: obj, options: [.sortedKeys])
+  print(String(data: data, encoding: .utf8)!)
+}
+
+func fail(_ message: String) -> Never {
+  emit(["error": message])
+  exit(1)
+}
+
+// ---- arg parsing ---------------------------------------------------------
+
+var rawArgs = Array(CommandLine.arguments.dropFirst())
+
+func takeOption(_ name: String) -> String? {
+  guard let i = rawArgs.firstIndex(of: name), i + 1 < rawArgs.count else { return nil }
+  let value = rawArgs[i + 1]
+  rawArgs.removeSubrange(i...(i + 1))
+  return value
+}
+
+func takeFlag(_ name: String) -> Bool {
+  guard let i = rawArgs.firstIndex(of: name) else { return false }
+  rawArgs.remove(at: i)
+  return true
+}
+
+let windowName = takeOption("--window") ?? "iPhone Mirroring"
+let noActivate = takeFlag("--no-activate")
+// By default a tap leaves the mirror frontmost (so you can watch the run on its
+// Space). --restore yanks focus back to the previously-active app after the tap
+// (YergerSnap's original "stay invisible" behavior) for unattended use.
+let restoreFocus = takeFlag("--restore")
+// Swipe flick duration (ms). Short = fast flick (scrolls far); longer = a
+// controlled drag. 350ms is a comfortable one-screen scroll.
+let durationMs = Int(takeOption("--duration") ?? "") ?? 350
+
+// ---- window resolution ---------------------------------------------------
+//
+// Everything keys off the LIVE window's CGWindowID, looked up fresh on every
+// command from the window-server's full list (.optionAll → includes windows on
+// other Spaces and behind other windows). That's what lets the user drag the
+// mirror anywhere — even to another desktop — while we keep tracking it:
+//   • `shot` captures by window id (screencapture -l), so Space/occlusion don't
+//     matter — we always get the window's own live pixels.
+//   • `frame`/`tap` re-resolve the bounds each call, so a moved window never
+//     desyncs.
+// Bounds come back in global screen points, top-left origin — the same space
+// CGEvent taps use — so a fraction maps straight to a click point.
+
+struct WinRef { let id: CGWindowID; let pid: pid_t; let frame: CGRect }
+
+func resolveWindow(named name: String) -> WinRef? {
+  guard let raw = CGWindowListCopyWindowInfo([.optionAll], kCGNullWindowID)
+          as? [[String: Any]] else { return nil }
+
+  struct Cand { let id: CGWindowID; let pid: pid_t; let rect: CGRect; let exactName: Bool }
+  var cands: [Cand] = []
+  for w in raw {
+    let owner = w[kCGWindowOwnerName as String] as? String ?? ""
+    let wname = w[kCGWindowName as String] as? String ?? ""
+    // Match the app (iPhone Mirroring) OR a window title (QuickTime's
+    // "Movie Recording" lives under owner "QuickTime Player").
+    guard owner.contains(name) || wname.contains(name) else { continue }
+    guard let b = w[kCGWindowBounds as String] as? [String: Any],
+          let x = b["X"] as? CGFloat, let y = b["Y"] as? CGFloat,
+          let cw = b["Width"] as? CGFloat, let ch = b["Height"] as? CGFloat,
+          let id = w[kCGWindowNumber as String] as? Int,
+          let pid = w[kCGWindowOwnerPID as String] as? Int else { continue }
+    // Drop menubar strips / tiny helper windows — keep real content windows.
+    guard cw >= 150, ch >= 300 else { continue }
+    cands.append(Cand(id: CGWindowID(id), pid: pid_t(pid),
+                      rect: CGRect(x: x, y: y, width: cw, height: ch),
+                      exactName: wname == name))
+  }
+  if cands.isEmpty { return nil }
+  // Prefer an exact window-title match (the live mirror's title is exactly
+  // "iPhone Mirroring"; the stale onboarding window is "Welcome to iPhone
+  // Mirroring"). Otherwise fall back to the largest matching window.
+  let pick = cands.sorted { a, b in
+    if a.exactName != b.exactName { return a.exactName }
+    return a.rect.width * a.rect.height > b.rect.width * b.rect.height
+  }.first!
+  return WinRef(id: pick.id, pid: pick.pid, frame: pick.rect)
+}
+
+func windowFrame(named name: String) -> CGRect? { resolveWindow(named: name)?.frame }
+
+func clickAt(_ point: CGPoint) {
+  let saved = CGEvent(source: nil)?.location
+  let down = CGEvent(mouseEventSource: nil, mouseType: .leftMouseDown,
+                     mouseCursorPosition: point, mouseButton: .left)
+  let up = CGEvent(mouseEventSource: nil, mouseType: .leftMouseUp,
+                   mouseCursorPosition: point, mouseButton: .left)
+  down?.post(tap: .cghidEventTap)
+  up?.post(tap: .cghidEventTap)
+  if let saved = saved { CGWarpMouseCursorPosition(saved) }
+}
+
+// A touch-drag (mouse down → stepped moves → up). iPhone Mirroring maps this to
+// a finger swipe, so it scrolls lists (the profile grid) and advances posts.
+// `steps` intermediate moves over `durationMs` make it read as a flick, not a
+// teleport, which the gesture recognizer needs to pick up velocity.
+func dragFromTo(_ a: CGPoint, _ b: CGPoint, steps: Int, durationMs: Int) {
+  let saved = CGEvent(source: nil)?.location
+  CGEvent(mouseEventSource: nil, mouseType: .leftMouseDown,
+          mouseCursorPosition: a, mouseButton: .left)?.post(tap: .cghidEventTap)
+  let n = max(steps, 1)
+  let perStep = useconds_t(max(durationMs, 1) * 1000 / n)
+  for i in 1...n {
+    let t = CGFloat(i) / CGFloat(n)
+    let p = CGPoint(x: a.x + (b.x - a.x) * t, y: a.y + (b.y - a.y) * t)
+    CGEvent(mouseEventSource: nil, mouseType: .leftMouseDragged,
+            mouseCursorPosition: p, mouseButton: .left)?.post(tap: .cghidEventTap)
+    usleep(perStep)
+  }
+  CGEvent(mouseEventSource: nil, mouseType: .leftMouseUp,
+          mouseCursorPosition: b, mouseButton: .left)?.post(tap: .cghidEventTap)
+  if let saved = saved { CGWarpMouseCursorPosition(saved) }
+}
+
+// Scroll-wheel gesture. iPhone Mirroring maps a Mac trackpad/scroll-wheel to
+// iOS scrolling (a click-drag does NOT scroll, it just touches). The event
+// lands on whatever is under the cursor, so we park the cursor in the window
+// first. Negative `ticks` scrolls the content UP (reveals items further down).
+func scrollWheel(in win: WinRef, ticks: Int, atFx: Double, atFy: Double) {
+  let f = win.frame
+  let here = CGPoint(x: f.minX + f.width * CGFloat(atFx), y: f.minY + f.height * CGFloat(atFy))
+  let saved = CGEvent(source: nil)?.location
+  CGWarpMouseCursorPosition(here)
+  usleep(60_000)
+  let dir = ticks < 0 ? -1 : 1
+  for _ in 0..<abs(ticks) {
+    CGEvent(scrollWheelEvent2Source: nil, units: .pixel, wheelCount: 1,
+            wheel1: Int32(dir * 40), wheel2: 0, wheel3: 0)?.post(tap: .cghidEventTap)
+    usleep(12_000)
+  }
+  if let saved = saved { CGWarpMouseCursorPosition(saved) }
+}
+
+// ---- commands ------------------------------------------------------------
+
+func cmdFrame() {
+  guard let f = windowFrame(named: windowName) else { fail("window not found: \(windowName)") }
+  emit(["x": f.minX, "y": f.minY, "w": f.width, "h": f.height])
+}
+
+func cmdShot(_ outPath: String) {
+  guard let win = resolveWindow(named: windowName) else { fail("window not found: \(windowName)") }
+  // Capture by window id (-l), not screen region: grabs THIS window's own live
+  // pixels even when it's on another Space or behind other windows, so the user
+  // can park the mirror anywhere. -o drops the drop-shadow.
+  let proc = Process()
+  proc.executableURL = URL(fileURLWithPath: "/usr/sbin/screencapture")
+  proc.arguments = ["-x", "-o", "-l\(win.id)", outPath]
+  do { try proc.run(); proc.waitUntilExit() } catch { fail("screencapture failed: \(error)") }
+  if proc.terminationStatus != 0 { fail("screencapture exit \(proc.terminationStatus)") }
+  let f = win.frame
+  emit(["x": f.minX, "y": f.minY, "w": f.width, "h": f.height, "id": Int(win.id), "path": outPath])
+}
+
+func cmdOcr(_ inPath: String) {
+  guard let src = CGImageSourceCreateWithURL(URL(fileURLWithPath: inPath) as CFURL, nil),
+        let cg = CGImageSourceCreateImageAtIndex(src, 0, nil) else { fail("cannot read image: \(inPath)") }
+  let imgW = CGFloat(cg.width), imgH = CGFloat(cg.height)
+  let request = VNRecognizeTextRequest()
+  request.recognitionLevel = .accurate
+  request.usesLanguageCorrection = false
+  let handler = VNImageRequestHandler(cgImage: cg, options: [:])
+  do { try handler.perform([request]) } catch { fail("ocr failed: \(error)") }
+  var lines: [[String: Any]] = []
+  for obs in (request.results ?? []) {
+    guard let top = obs.topCandidates(1).first else { continue }
+    let b = obs.boundingBox  // normalized, BOTTOM-left origin
+    lines.append([
+      "text": top.string,
+      "conf": top.confidence,
+      "x": b.origin.x,
+      "y": 1.0 - (b.origin.y + b.height),  // → TOP-left origin
+      "w": b.width,
+      "h": b.height,
+    ])
+  }
+  emit(["w": imgW, "h": imgH, "lines": lines])
+}
+
+func cmdTap(_ fx: Double, _ fy: Double) {
+  guard let win = resolveWindow(named: windowName) else { fail("window not found: \(windowName)") }
+  let prev = NSWorkspace.shared.frontmostApplication
+  // A synthetic click lands wherever the cursor coordinate is on the ACTIVE
+  // Space, so to tap a window the user parked elsewhere we activate its app
+  // first (brings its Space/window forward), then re-resolve in case that moved
+  // it, then click. --no-activate skips this when the caller keeps it frontmost.
+  if !noActivate {
+    NSRunningApplication(processIdentifier: win.pid)?.activate(options: [])
+    // Settle long enough to cover a Space-switch animation when the mirror was
+    // parked on another desktop — otherwise the click lands mid-transition and
+    // misses. Cheap insurance; taps are paced seconds apart anyway.
+    usleep(450_000)
+  }
+  let f = (noActivate ? win : (resolveWindow(named: windowName) ?? win)).frame
+  let target = CGPoint(x: f.minX + f.width * CGFloat(fx), y: f.minY + f.height * CGFloat(fy))
+  clickAt(target)
+  usleep(40_000)
+  if !noActivate && restoreFocus { prev?.activate(options: []) }
+  emit(["tapped": ["x": target.x, "y": target.y], "fx": fx, "fy": fy, "id": Int(win.id)])
+}
+
+func cmdSwipe(_ fx1: Double, _ fy1: Double, _ fx2: Double, _ fy2: Double, durationMs: Int) {
+  guard let win = resolveWindow(named: windowName) else { fail("window not found: \(windowName)") }
+  let prev = NSWorkspace.shared.frontmostApplication
+  if !noActivate {
+    NSRunningApplication(processIdentifier: win.pid)?.activate(options: [])
+    usleep(450_000)
+  }
+  let f = (noActivate ? win : (resolveWindow(named: windowName) ?? win)).frame
+  let a = CGPoint(x: f.minX + f.width * CGFloat(fx1), y: f.minY + f.height * CGFloat(fy1))
+  let b = CGPoint(x: f.minX + f.width * CGFloat(fx2), y: f.minY + f.height * CGFloat(fy2))
+  dragFromTo(a, b, steps: 24, durationMs: durationMs)
+  usleep(40_000)
+  if !noActivate && restoreFocus { prev?.activate(options: []) }
+  emit(["swiped": ["from": ["x": a.x, "y": a.y], "to": ["x": b.x, "y": b.y]], "id": Int(win.id)])
+}
+
+func cmdScroll(_ ticks: Int) {
+  guard let win = resolveWindow(named: windowName) else { fail("window not found: \(windowName)") }
+  let prev = NSWorkspace.shared.frontmostApplication
+  if !noActivate {
+    NSRunningApplication(processIdentifier: win.pid)?.activate(options: [])
+    usleep(450_000)
+  }
+  let live = (noActivate ? win : (resolveWindow(named: windowName) ?? win))
+  scrollWheel(in: live, ticks: ticks, atFx: 0.5, atFy: 0.55)
+  usleep(40_000)
+  if !noActivate && restoreFocus { prev?.activate(options: []) }
+  emit(["scrolled": ticks, "id": Int(live.id)])
+}
+
+// ---- dispatch ------------------------------------------------------------
+
+guard let verb = rawArgs.first else {
+  fail("usage: iphone-tap <frame|shot OUT.png|ocr IN.png|tap FX FY> [--window NAME]")
+}
+rawArgs.removeFirst()
+
+switch verb {
+case "frame":
+  cmdFrame()
+case "shot":
+  guard let out = rawArgs.first else { fail("shot needs OUT.png") }
+  cmdShot(out)
+case "ocr":
+  guard let inp = rawArgs.first else { fail("ocr needs IN.png") }
+  cmdOcr(inp)
+case "tap":
+  guard rawArgs.count >= 2, let fx = Double(rawArgs[0]), let fy = Double(rawArgs[1]) else {
+    fail("tap needs FX FY (fractions 0..1)")
+  }
+  cmdTap(fx, fy)
+case "swipe":
+  guard rawArgs.count >= 4,
+        let fx1 = Double(rawArgs[0]), let fy1 = Double(rawArgs[1]),
+        let fx2 = Double(rawArgs[2]), let fy2 = Double(rawArgs[3]) else {
+    fail("swipe needs FX1 FY1 FX2 FY2 (fractions 0..1) [--duration MS]")
+  }
+  cmdSwipe(fx1, fy1, fx2, fy2, durationMs: durationMs)
+case "scroll":
+  guard let n = Int(rawArgs.first ?? "") else { fail("scroll needs TICKS (negative scrolls content up)") }
+  cmdScroll(n)
+default:
+  fail("unknown command: \(verb)")
+}
diff --git a/wave-wizard/samples/americomputadora/spec.json b/wave-wizard/samples/americomputadora/spec.json
new file mode 100644
index 000000000..169dd095f
--- /dev/null
+++ b/wave-wizard/samples/americomputadora/spec.json
@@ -0,0 +1,36 @@
+{
+  "title": "americomputadora — jeffrey syllable chant",
+  "outDir": "/Users/jas/aesthetic-computer/wave-wizard/samples/americomputadora/takes",
+  "trim": {
+    "thresholdPctOfPeak": 0.04,
+    "padHeadMs": 40,
+    "padTailMs": 160,
+    "fadeMs": 8,
+    "normalizeDb": -3.0
+  },
+  "autoStop": {
+    "onsetDb": -28,
+    "silenceDb": -42,
+    "silenceDurationMs": 1100,
+    "maxRecordSec": 5
+  },
+  "samples": [
+    {
+      "name": "americomputadora-chant",
+      "desc": "Sing the americomputadora chant, one syllable per beat, in a comfortable low voice: ah, mer, ick, ahmp, uter, do, rah. Each take captures one syllable — just sing the vowel cleanly and hold it for the beat. The pitch only needs to be a comfortable reference; it gets tuned to the melody afterward.",
+      "lyric": "ah mer ick ahmp u-ter do rah",
+      "score": {
+        "rootMel": 50,
+        "notes": [
+          { "off": 0, "beats": 1.0 },
+          { "off": 2, "beats": 1.0 },
+          { "off": 4, "beats": 1.0 },
+          { "off": 5, "beats": 1.0 },
+          { "off": 7, "beats": 1.0 },
+          { "off": 4, "beats": 1.0 },
+          { "off": 0, "beats": 1.0 }
+        ]
+      }
+    }
+  ]
+}