From f89a5ee77bb5bdaece580822d22f6d1b16b2c5e2 Mon Sep 17 00:00:00 2001 From: Jer Miller Date: Sun, 5 Apr 2026 22:53:54 -0600 Subject: [PATCH] chore: remove legacy onboarding dead code Delete disabled onboarding/observation/firstday_checkin talent files, tests, CLI commands, and all stale references. Set first_daily_ready unconditionally on first daily analysis (was gated on onboarding completion status that no longer exists). Rename test_onboarding.py to test_convey_apps.py retaining only the live convey app tests. 9 files deleted, ~3700 lines removed across 35 files. --- AGENTS.md | 2 +- apps/awareness/call.py | 46 +- apps/home/events.py | 2 +- convey/root.py | 2 +- docs/SOLCLI.md | 4 +- sol/identity.md | 2 +- talent/awareness_tender.md | 2 +- talent/chat.md | 2 +- talent/firstday_checkin.md | 18 - talent/firstday_checkin.py | 115 -- talent/journal/SKILL.md | 2 +- talent/observation.md | 71 - talent/observation.py | 248 --- talent/observation_review.md | 123 -- talent/onboarding.md | 137 -- talent/onboarding/SKILL.md | 85 - talent/triage.md | 28 +- tests/baselines/api/agents/agents-day.json | 44 - tests/baselines/api/agents/preview.json | 2 +- tests/baselines/api/search/day-results.json | 2 +- tests/baselines/api/search/search.json | 68 +- tests/baselines/api/settings/generators.json | 20 - tests/baselines/api/settings/providers.json | 30 - tests/baselines/api/stats/stats.json | 1510 +---------------- tests/baselines/api/tokens/stats-month.json | 6 +- .../api/transcripts/segment-detail.json | 4 +- tests/test_awareness.py | 147 -- ...test_onboarding.py => test_convey_apps.py} | 141 +- tests/test_dream_preflight.py | 73 - tests/test_dream_segment.py | 10 - tests/test_observation.py | 344 ---- tests/test_talent_cli.py | 5 +- think/awareness.py | 69 +- think/dream.py | 62 +- 34 files changed, 82 insertions(+), 3344 deletions(-) delete mode 100644 talent/firstday_checkin.md delete mode 100644 talent/firstday_checkin.py delete mode 100644 talent/observation.md delete mode 100644 talent/observation.py delete mode 100644 talent/observation_review.md delete mode 100644 talent/onboarding.md delete mode 100644 talent/onboarding/SKILL.md rename tests/{test_onboarding.py => test_convey_apps.py} (75%) delete mode 100644 tests/test_dream_preflight.py delete mode 100644 tests/test_observation.py diff --git a/AGENTS.md b/AGENTS.md index ed22bb70b..e49090226 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -28,7 +28,7 @@ You maintain three files that give you continuity between sessions: - **`sol/self.md`** — Your identity file. What you know about the person whose journal you tend, your relationship, observations, and interests. Update when something genuinely changes your understanding. - **`sol/agency.md`** — Your initiative queue. Issues you've found, curation opportunities, follow-throughs. Update when you notice something worth tracking. -- **`sol/partner.md`** — Your understanding of the owner's behavioral patterns. Work style, communication preferences, relationship priorities, decision-making, expertise. Updated by the partner profile agent and during onboarding conversations. +- **`sol/partner.md`** — Your understanding of the owner's behavioral patterns. Work style, communication preferences, relationship priorities, decision-making, expertise. Updated by the partner profile agent and during initial conversations. ### How to write diff --git a/apps/awareness/call.py b/apps/awareness/call.py index 1a99f88be..16f7e232e 100644 --- a/apps/awareness/call.py +++ b/apps/awareness/call.py @@ -16,7 +16,7 @@ app = typer.Typer(help="Awareness system — solstone's self-knowledge.") @app.command("status") def status( section: str | None = typer.Argument( - None, help="Section to read (e.g., 'onboarding'). Omit for all." + None, help="Section to read (e.g., 'journal'). Omit for all." ), ) -> None: """Show current awareness state.""" @@ -37,50 +37,6 @@ def status( typer.echo(json.dumps(state, indent=2)) -@app.command("onboarding") -def onboarding_cmd( - path: str | None = typer.Option( - None, "--path", "-p", help="Onboarding path: 'a' (observe) or 'b' (interview)." - ), - skip: bool = typer.Option(False, "--skip", help="Skip onboarding."), - complete: bool = typer.Option( - False, "--complete", help="Mark onboarding complete." - ), -) -> None: - """Read or update onboarding state.""" - from think.awareness import ( - complete_onboarding, - get_onboarding, - skip_onboarding, - start_onboarding, - ) - - if skip: - state = skip_onboarding() - typer.echo(json.dumps(state, indent=2)) - return - - if complete: - state = complete_onboarding() - typer.echo(json.dumps(state, indent=2)) - return - - if path: - if path not in ("a", "b"): - typer.echo("Error: --path must be 'a' or 'b'", err=True) - raise typer.Exit(1) - state = start_onboarding(path) - typer.echo(json.dumps(state, indent=2)) - return - - # No flags — read current state - state = get_onboarding() - if not state: - typer.echo("No onboarding state yet.") - return - typer.echo(json.dumps(state, indent=2)) - - @app.command("imports") def imports_cmd( record: str | None = typer.Option( diff --git a/apps/home/events.py b/apps/home/events.py index e95075bc7..c47550b31 100644 --- a/apps/home/events.py +++ b/apps/home/events.py @@ -15,7 +15,7 @@ from think.cortex_client import read_agent_events logger = logging.getLogger(__name__) -TRIAGE_AGENT_NAMES = {"unified", "triage", "onboarding"} +TRIAGE_AGENT_NAMES = {"unified", "triage"} @on_event("cortex", "finish") diff --git a/convey/root.py b/convey/root.py index b8660c160..496bb89e9 100644 --- a/convey/root.py +++ b/convey/root.py @@ -125,5 +125,5 @@ def app_today() -> Any: @bp.route("/") def index() -> Any: - """Root redirect — always to home, onboarding talent handles new journals.""" + """Root redirect — always to home; the app handles new journals there.""" return redirect(url_for("app:home.index")) diff --git a/docs/SOLCLI.md b/docs/SOLCLI.md index 7a1211c5a..117979e10 100644 --- a/docs/SOLCLI.md +++ b/docs/SOLCLI.md @@ -312,7 +312,7 @@ solstone/ | `transcripts` | `apps/transcripts/call.py` | list, read, segments | | `support` | `apps/support/call.py` | register, search, article, create, list, show, reply, attach, feedback, announcements, diagnose | | `agent` | `apps/agent/call.py` | name, set-name, reset, thickness, set-owner, sol-init | -| `awareness` | `apps/awareness/call.py` | status, onboarding, imports, log, log-read | +| `awareness` | `apps/awareness/call.py` | status, imports, log, log-read | | `journal` | `think/tools/call.py` | search, events, facets, facet (show/create/update/rename/mute/unmute/delete/merge), news, agents, read, imports, import, retention purge, storage-summary | | `routines` | `think/tools/routines.py` | list, templates, create, edit, delete, run, output, suggestions, suggest-respond, suggest-state | | `identity` | `think/tools/sol.py` | self, partner, agency, pulse, briefing | @@ -327,7 +327,7 @@ Skills are documented in `SKILL.md` files and symlinked into `.agents/skills/` b - Core skills: `talent//SKILL.md` **Skill ≠ call command.** Not every skill has a corresponding `call.py`, and not every `call.py` has a skill: -- `health`, `coding`, `vit`, `onboarding` have skills but no `call.py` +- `health`, `coding`, `vit` have skills but no `call.py` - Some call apps provide the CLI while the skill provides agent behavioral context Skills document the CLI commands but also add behavioral guidance beyond what `--help` shows (e.g., "check upcoming before adding a future todo to avoid duplicates"). diff --git a/sol/identity.md b/sol/identity.md index 282731e85..23450d284 100644 --- a/sol/identity.md +++ b/sol/identity.md @@ -26,7 +26,7 @@ You maintain three files that give you continuity between sessions: - **`sol/self.md`** — Your identity file. What you know about the person whose journal you tend, your relationship, observations, and interests. Update when something genuinely changes your understanding. - **`sol/agency.md`** — Your initiative queue. Issues you've found, curation opportunities, follow-throughs. Update when you notice something worth tracking. -- **`sol/partner.md`** — Your understanding of the owner's behavioral patterns. Work style, communication preferences, relationship priorities, decision-making, expertise. Updated by the partner profile agent and during onboarding conversations. +- **`sol/partner.md`** — Your understanding of the owner's behavioral patterns. Work style, communication preferences, relationship priorities, decision-making, expertise. Updated by the partner profile agent and during initial conversations. ### How to write diff --git a/talent/awareness_tender.md b/talent/awareness_tender.md index 0f2c909af..f8e73085d 100644 --- a/talent/awareness_tender.md +++ b/talent/awareness_tender.md @@ -19,7 +19,7 @@ This is not a conversation. Gather state, write the update, done. Read current state using these tools: -1. `sol call awareness status` — capture, processing, and onboarding state +1. `sol call awareness status` — capture, processing, import, and journal state 2. `sol call identity self` — identity summary (skim for key changes) 3. `sol call calendar list` — today's events 4. `sol call routines list` — active routines and recent outputs diff --git a/talent/chat.md b/talent/chat.md index fd93b6f6f..5deaa49b5 100644 --- a/talent/chat.md +++ b/talent/chat.md @@ -56,7 +56,7 @@ You have access to specialized skills. Use them by recognizing what the owner ne | todos | Adding, completing, canceling, or listing todos and action items | | speakers | Speaker identification, voice recognition, managing the speaker library | | support | Bug reports, help requests, filing tickets, feedback, KB search, diagnostics | -| awareness | Checking onboarding, observation, or system state | +| awareness | Checking system state | ## Speaker Intelligence diff --git a/talent/firstday_checkin.md b/talent/firstday_checkin.md deleted file mode 100644 index e5df392eb..000000000 --- a/talent/firstday_checkin.md +++ /dev/null @@ -1,18 +0,0 @@ -{ - "type": "generate", - "title": "First-Day Check-In", - "description": "One-shot check-in after onboarding — spawns support agent chat", - "disabled": true, - "schedule": "segment", - "priority": 98, - "output": "text", - "hook": {"pre": "firstday_checkin", "post": "firstday_checkin"}, - "tier": 3, - "thinking_budget": 512, - "max_output_tokens": 256, - "exclude_streams": ["import.*"] -} - -This generator exists only to trigger the first-day check-in via its pre/post hooks. The pre-hook handles all logic — if it doesn't skip, the post-hook spawns a support agent chat. The LLM output is unused. - -Output "ok" — nothing else needed. diff --git a/talent/firstday_checkin.py b/talent/firstday_checkin.py deleted file mode 100644 index 6c8306cd1..000000000 --- a/talent/firstday_checkin.py +++ /dev/null @@ -1,115 +0,0 @@ -# SPDX-License-Identifier: AGPL-3.0-only -# Copyright (c) 2026 sol pbc - -"""First-day check-in hooks. - -Pre-hook: guards on awareness state — skips immediately (zero API cost) -unless onboarding is complete and ~1 hour has elapsed since completion. -One-shot: once the check-in fires, it never fires again. - -Post-hook: records that the check-in was sent and spawns a support -agent chat for the user. -""" - -from __future__ import annotations - -import logging -from datetime import datetime - -logger = logging.getLogger(__name__) - -# Minimum hours after onboarding completion before check-in fires -MIN_HOURS_AFTER_COMPLETE = 1.0 - - -def pre_process(context: dict) -> dict | None: - """Guard: skip unless onboarding is complete and 1+ hour has elapsed. - - Returns dict with skip_reason to skip, or None to proceed. - """ - from think.awareness import get_onboarding - - onboarding = get_onboarding() - status = onboarding.get("status") - - # Only fire after onboarding completes - if status != "complete": - return {"skip_reason": "not_complete"} - - # Only fire once - if onboarding.get("firstday_checkin_sent"): - return {"skip_reason": "already_sent"} - - # Check elapsed time since onboarding started - # (onboarding.started is when they began, but we want time since completion; - # since complete_onboarding() doesn't record a timestamp, use started + a - # generous window — 1 hour after they started is a reasonable proxy for - # "settled in") - started = onboarding.get("started", "") - if not started: - return {"skip_reason": "no_start_time"} - - hours = _elapsed_hours(started) - if hours < MIN_HOURS_AFTER_COMPLETE: - return {"skip_reason": "too_soon"} - - # All conditions met — proceed - return None - - -def post_process(result: str, context: dict) -> str | None: - """Record check-in and spawn support agent chat.""" - from think.awareness import append_log, update_state - - # Record that we sent it (prevents repeat) - update_state("onboarding", {"firstday_checkin_sent": _now_iso()}) - append_log( - "state", - key="onboarding.firstday_checkin_sent", - message="First-day check-in sent to user", - ) - - # Spawn support agent check-in and surface through conversation panel - try: - from think.callosum import callosum_send - from think.cortex_client import cortex_request - - prompt = ( - "The user recently completed onboarding. This is your first-day " - "check-in. Send a warm, brief message: ask how things are going, " - "if anything is surprising or confusing, and remind them you're " - "here to help or capture feedback anytime. Keep it short and " - "conversational — one message, not a wall of text." - ) - agent_id = cortex_request(prompt=prompt, name="support") - if agent_id: - callosum_send( - "notification", - "show", - title="Check-in", - message="How's everything going? I'm here if you need anything.", - icon="👋", - app="conversation", - ) - logger.info("Spawned first-day check-in agent: %s", agent_id) - except Exception: - logger.exception("Failed to spawn first-day check-in agent") - - return result - - -def _elapsed_hours(started_iso: str) -> float: - """Calculate hours elapsed since the started timestamp.""" - if not started_iso: - return 0.0 - try: - start = datetime.strptime(started_iso, "%Y%m%dT%H:%M:%S") - elapsed = (datetime.now() - start).total_seconds() - return elapsed / 3600 - except (ValueError, TypeError): - return 0.0 - - -def _now_iso() -> str: - """Return current time as compact ISO string.""" - return datetime.now().strftime("%Y%m%dT%H:%M:%S") diff --git a/talent/journal/SKILL.md b/talent/journal/SKILL.md index f00e3016d..db5a79261 100644 --- a/talent/journal/SKILL.md +++ b/talent/journal/SKILL.md @@ -105,7 +105,7 @@ Create a new facet directory and initial `facet.json`. - `--emoji`: optional icon emoji (default: `📦`). - `--color`: optional hex color (default: `#667eea`). - `--description`: optional description text. -- `--consent`: asserts that the agent has received a direct owner request or explicit owner approval before calling this command. Pass when acting proactively (cogitate, suggestion flows) rather than in direct response to an owner instruction. Omit for the onboarding talent — onboarding is owner-driven by definition. Adds `"consent": true` to the audit log entry. +- `--consent`: asserts that the agent has received a direct owner request or explicit owner approval before calling this command. Pass when acting proactively (cogitate, suggestion flows) rather than in direct response to an owner instruction. Adds `"consent": true` to the audit log entry. Examples: diff --git a/talent/observation.md b/talent/observation.md deleted file mode 100644 index 7de613b27..000000000 --- a/talent/observation.md +++ /dev/null @@ -1,71 +0,0 @@ -{ - "type": "generate", - "title": "Observation", - "description": "Extracts patterns from segment data during onboarding observation", - "disabled": true, - "schedule": "segment", - "priority": 97, - "output": "json", - "hook": {"pre": "observation", "post": "observation"}, - "tier": 3, - "thinking_budget": 2048, - "max_output_tokens": 2048, - "exclude_streams": ["import.*"], - "load": {"transcripts": true, "percepts": true, "agents": false} -} - -You are analyzing a captured segment of someone's computer activity to learn about their work patterns. This is part of an onboarding observation — the owner has asked the system to watch how they work for a day and then suggest how to organize their journal. - -## Input - -You receive a transcript combining audio (microphone/system audio, with speaker labels) and screen activity (app usage, visible content) from a ~5-minute capture window. - -## Task - -Extract structured observations about what happened in this segment. Focus on: - -1. **Meetings** — conversations with 2+ speakers. Note participant count, any names mentioned, and the topic/context. -2. **Apps** — what applications or tools the owner is actively using. -3. **Entities** — specific people, companies, projects, or tools mentioned by name. -4. **Topics** — what subjects or themes are present in the activity. -5. **Summary** — a brief 1-line description of what the owner was doing. - -## Output Format - -Return a JSON object: - -```json -{ - "has_meeting": false, - "speaker_count": 1, - "meeting_topic": null, - "apps": ["VS Code", "Terminal"], - "people": ["Alice Chen"], - "companies": [], - "projects": ["auth-service"], - "tools": ["Git", "Docker"], - "topics": ["backend development", "authentication"], - "summary": "Solo coding session working on authentication service" -} -``` - -### Field Definitions - -- `has_meeting`: true if 2+ speakers are having a conversation (not just background audio) -- `speaker_count`: number of distinct speakers detected -- `meeting_topic`: brief topic if a meeting is detected, null otherwise -- `apps`: list of applications/tools actively in use on screen -- `people`: names of people mentioned or speaking (use real names when identifiable, "Speaker N" when not) -- `companies`: company or organization names mentioned -- `projects`: project names, product names, or codebases mentioned -- `tools`: development tools, services, or platforms mentioned -- `topics`: 1-3 high-level topic themes for this segment -- `summary`: one concise sentence describing the segment - -## Rules - -1. Only report what you can clearly observe — don't speculate -2. Use real names when they appear in the transcript; "Speaker N" is fine for unnamed speakers -3. Empty lists are valid when nothing is detected for a category -4. Keep the summary factual and brief -5. Return ONLY the JSON object, no other text diff --git a/talent/observation.py b/talent/observation.py deleted file mode 100644 index dd5e9e168..000000000 --- a/talent/observation.py +++ /dev/null @@ -1,248 +0,0 @@ -# SPDX-License-Identifier: AGPL-3.0-only -# Copyright (c) 2026 sol pbc - -"""Observation hooks for Path A onboarding. - -Pre-hook: guards on awareness state — skips immediately (zero API cost) -when the user is not in Path A observation mode. - -Post-hook: writes LLM findings to the awareness log, sends callosum -notifications for interesting discoveries, and transitions to "ready" -when the observation threshold is met. -""" - -from __future__ import annotations - -import json -import logging -from datetime import datetime - -logger = logging.getLogger(__name__) - -# Observation thresholds -MIN_SEGMENTS = 10 -MIN_HOURS = 4.0 - -# Maximum nudge notifications during observation -MAX_NUDGES = 4 - - -# --------------------------------------------------------------------------- -# Pre-hook -# --------------------------------------------------------------------------- - - -def pre_process(context: dict) -> dict | None: - """Guard: skip if not in Path A observation mode. - - Args: - context: PreHookContext with day, segment, output_path, transcript, meta - - Returns: - Dict with skip_reason if not observing, or None to proceed. - """ - from think.awareness import get_onboarding - - onboarding = get_onboarding() - if onboarding.get("status") != "observing": - return {"skip_reason": "not_observing"} - - # Observing — let the LLM analyze the segment transcript - return None - - -# --------------------------------------------------------------------------- -# Post-hook -# --------------------------------------------------------------------------- - - -def post_process(result: str, context: dict) -> str | None: - """Process LLM observation output — log, notify, check threshold. - - Args: - result: LLM JSON output with observation findings - context: Full config dict with day, segment, etc. - - Returns: - The result string unchanged (output still written to segment dir). - """ - from think.awareness import append_log, get_onboarding, update_state - from think.callosum import callosum_send - - day = context.get("day", "") - segment = context.get("segment", "") - - # Parse LLM output - try: - findings = json.loads(result) - except (json.JSONDecodeError, TypeError): - logger.warning("observation post-hook: failed to parse LLM output") - return result - - if not isinstance(findings, dict): - logger.warning("observation post-hook: LLM output is not a dict") - return result - - # Write observation to awareness log - append_log( - "observation", - key=f"segment.{day}.{segment}", - message=findings.get("summary", ""), - data=findings, - day=day, - segment=segment, - ) - - # Update observation count - onboarding = get_onboarding() - count = onboarding.get("observation_count", 0) + 1 - update_state("onboarding", {"observation_count": count}) - - # Check if we should send a nudge notification - nudges_sent = onboarding.get("nudges_sent", 0) - if nudges_sent < MAX_NUDGES: - nudge = _check_nudge(findings, count, nudges_sent, onboarding) - if nudge: - callosum_send( - "notification", - "show", - title=nudge["title"], - message=nudge["message"], - icon=nudge.get("icon", "🔍"), - app="observation", - ) - update_state("onboarding", {"nudges_sent": nudges_sent + 1}) - append_log( - "nudge", - key="onboarding.nudge", - message=nudge["message"], - data={"title": nudge["title"], "nudge_number": nudges_sent + 1}, - ) - - # Check observation threshold - if _threshold_met(onboarding, count): - _transition_to_ready(day) - - return result - - -def _check_nudge( - findings: dict, - observation_count: int, - nudges_sent: int, - onboarding: dict, -) -> dict | None: - """Decide whether this segment's findings warrant a notification. - - Returns a nudge dict with title/message/icon, or None. - Nudge triggers (in order of priority): - 0: First meeting detected - 1: First entity cluster (3+ named people) - 2: After 5 segments — progress update - 3: Nearing threshold — "almost ready" - """ - # Nudge 0: First meeting - if nudges_sent == 0 and findings.get("has_meeting"): - speaker_count = findings.get("speaker_count", 0) - topic = findings.get("meeting_topic") or "a conversation" - return { - "title": "Meeting detected", - "message": f"Noticed {speaker_count} people discussing {topic}.", - "icon": "🎙️", - } - - # Nudge 1: First entity cluster - if nudges_sent <= 1: - people = findings.get("people", []) - if len(people) >= 3: - names = ", ".join(people[:3]) - return { - "title": "Learning your network", - "message": f"Spotted several people: {names}.", - "icon": "👥", - } - - # Nudge 2: Progress update at 5 segments - if nudges_sent <= 2 and observation_count == 5: - return { - "title": "Still learning", - "message": "Building a picture of your work patterns. Keep going!", - "icon": "📊", - } - - # Nudge 3: Almost ready - if nudges_sent <= 3 and observation_count >= MIN_SEGMENTS - 1: - started = onboarding.get("started", "") - hours = _elapsed_hours(started) - if hours >= MIN_HOURS * 0.75: - return { - "title": "Almost ready", - "message": "Have enough data to make suggestions soon.", - "icon": "✨", - } - - return None - - -def _threshold_met(onboarding: dict, count: int) -> bool: - """Check if observation period is complete. - - Requires both minimum segments AND minimum elapsed time. - """ - if count < MIN_SEGMENTS: - return False - - started = onboarding.get("started", "") - hours = _elapsed_hours(started) - return hours >= MIN_HOURS - - -def _elapsed_hours(started_iso: str) -> float: - """Calculate hours elapsed since the started timestamp.""" - if not started_iso: - return 0.0 - try: - start = datetime.strptime(started_iso, "%Y%m%dT%H:%M:%S") - elapsed = (datetime.now() - start).total_seconds() - return elapsed / 3600 - except (ValueError, TypeError): - return 0.0 - - -def _transition_to_ready(day: str) -> None: - """Transition onboarding to 'ready' state and notify via conversation panel.""" - from think.awareness import append_log, update_state - - update_state("onboarding", {"status": "ready"}) - append_log( - "state", - key="onboarding.ready", - message="Observation threshold met — recommendations ready", - day=day, - ) - - # Spawn observation review agent and surface through conversation panel - try: - from think.callosum import callosum_send - from think.cortex_client import cortex_request - - prompt = ( - "The user chose Path A onboarding — passive observation. " - "The observation period is complete. Read the accumulated " - "observations and present your recommendations for facets " - "and entities. Be warm and enthusiastic about what you learned." - ) - agent_id = cortex_request(prompt=prompt, name="observation_review") - if agent_id: - callosum_send( - "notification", - "show", - title="Your journal suggestions are ready", - message="I've finished observing — let's set up your journal.", - icon="✨", - app="conversation", - ) - logger.info("Spawned observation review agent: %s", agent_id) - except Exception: - logger.exception("Failed to spawn observation review agent") - # Non-fatal — user can still trigger review via conversation panel diff --git a/talent/observation_review.md b/talent/observation_review.md deleted file mode 100644 index 6c0092427..000000000 --- a/talent/observation_review.md +++ /dev/null @@ -1,123 +0,0 @@ -{ - "type": "cogitate", - "title": "Observation Review", - "description": "Synthesizes onboarding observations into facet and entity recommendations", - "disabled": true -} - -You are $agent_name's onboarding recommendation assistant. The owner chose Path A — passive observation — and the system has been watching how they work. Now it's time to present what you learned and help them set up their journal. - -## Your Job - -1. Read the accumulated observations from the awareness log. -2. Synthesize them into concrete recommendations for journal facets and entities. -3. Present each recommendation and let the owner accept, modify, or reject it. -4. Create accepted facets and attach entities. -5. Mark onboarding complete. - -## Step 1: Read Observations - -Start by reading the observation log: - -```bash -sol call awareness log-read --kind observation -``` - -Also check the current onboarding state: - -```bash -sol call awareness onboarding -``` - -## Step 2: Synthesize Recommendations - -From the observations, identify: - -- **Distinct work contexts** — recurring themes that suggest separate facets (e.g., "you had meetings about authentication and also worked on the CLI tool — these seem like different projects") -- **Key people** — names that appear frequently across observations -- **Projects and tools** — codebases, services, and tools the owner works with -- **Activity patterns** — what the owner spends most time on - -## Step 3: Present Recommendations - -Present your findings warmly and concretely. Start with a brief summary of what you observed, then present facet suggestions one at a time. - -For each suggested facet: -- Explain WHY you're suggesting it (what patterns led to this) -- Propose a name, emoji, and brief description -- List entities (people, projects, tools) you'd attach to it -- Ask the owner to accept, modify, or skip - -Example: -> I noticed you had several meetings about authentication and security — discussions with Alice and Bob about OAuth flows, plus solo coding on the auth-service repo. This looks like a distinct work context. -> -> **Suggested facet:** 🔐 Security Work -> *Description: Authentication, security reviews, and related development* -> *People: Alice Chen, Bob* -> *Projects: auth-service* -> -> Does this look right? I can adjust the name, add more entities, or skip this one. - -## Step 4: Create Accepted Suggestions - -For each accepted facet: - -```bash -sol call journal facet create "TITLE" --emoji "EMOJI" --color "COLOR" --description "DESC" -``` - -Then attach entities: - -```bash -sol call entities attach TYPE ENTITY DESCRIPTION --facet FACET -``` - -Entity types: Person, Company, Project, Tool - -## Step 5: Offer Imports - -After creating facets and attaching entities, **before** completing onboarding, offer to import existing data: - -> Nice — I've set up [facets] based on what I observed. Your journal now has structure, but it's mostly today's data. -> -> Want to fill in the backstory? If you have ChatGPT conversations, calendar exports, notes, or Kindle highlights, I can import them so I can see patterns going back months or years. -> -> What do you use that we could bring in? - -**If owner picks a source:** -1. Read the export guide from `apps/import/guides/{source}.md` (map: Calendar→ics, ChatGPT→chatgpt, Claude→claude, Gemini→gemini, Notes→obsidian, Kindle→kindle) -2. Present the export instructions conversationally -3. Navigate to the import app: `sol call navigate "/app/import#guide/{source}"` -4. Tell the owner you'll take them to the import page to upload the file - -**If owner says "skip" or "not now":** -1. Run `sol call awareness imports --declined` to record the decline -2. Say: "No problem — you can import anytime from the Import app. I'll remind you once you've settled in." -3. Proceed to complete onboarding - -## Step 6: Complete Onboarding - -After the import offer (whether they chose a source or skipped): - -```bash -sol call awareness onboarding --complete -``` - -Confirm the facets and show what was created: - -```bash -sol call journal facets -``` - -Tell the owner their journal is now set up and the system will start organizing captures into these facets. Reference the specific entities you just created or attached — name them — and suggest a first thing to try: pick one entity and say something like "Try asking me 'tell me about [entity name]' — I'll pull together everything I know." They can always adjust facets and entities later. - -## Behavioral Rules - -- Be enthusiastic but not overwhelming — you learned real things about how they work -- Present 2-4 facet suggestions (not too many for a first setup) -- Ground every suggestion in observed evidence — "I noticed X, which suggests Y" -- Don't create anything without owner confirmation -- If the owner wants to modify a suggestion, help them refine it -- If the owner rejects everything, that's fine — suggest they can set up manually later -- Choose colors and emojis that feel natural for each context -- After completion, remind them they can always create more facets or modify these ones diff --git a/talent/onboarding.md b/talent/onboarding.md deleted file mode 100644 index 76cc73947..000000000 --- a/talent/onboarding.md +++ /dev/null @@ -1,137 +0,0 @@ -{ - "type": "cogitate", - "title": "Onboarding", - "description": "Guided setup for new owners — offers passive observation or conversational interview", - "disabled": true -} - -You are $agent_name's onboarding assistant. Your job is to help new owners get started with their journal. - -## First Message — Welcome Choice - -Your very first response must present two onboarding paths. Be warm and concise: - -Before presenting paths, open with a single trust-setting line: - -> everything you capture stays on your machine — your journal is yours alone, never sent to sol pbc. - -Then present the two paths: - -**Path A — Observe and learn:** $agent_name listens and learns from your day for about a day, then suggests how to organize your journal based on what it sees. zero effort — just go about your day. - -**Path B — Set it up now:** Tell me about your work, projects, and interests, and I'll set things up right away through a quick conversation. - -Ask the owner which path they prefer. They can also say "skip" to set up manually later. - -## Handling the Choice - -### If the owner chooses Path A (observe): -1. Run `sol call awareness onboarding --path a` to record the choice. -2. Tell the owner: their journal is now capturing and learning. They'll get notifications as the system notices interesting patterns, and after about a day they'll get suggestions for organizing everything. They can check in anytime by asking "what have you noticed?" in the chat bar. -3. That's it — end the conversation. Don't try to interview them or create facets. - -### If the owner chooses Path B (interview): -1. Run `sol call awareness onboarding --path b` to record the choice. -2. Proceed with the conversational setup below. - -### If the owner says "skip": -1. Run `sol call awareness onboarding --skip` to record the skip. -2. Tell them they can set things up anytime using the chat bar. End the conversation. - -## Path B — Conversational Setup - -### Introduce yourself and learn their name - -Start Path B by asking the owner what they'd like to be called. When they share their name, run: - -`sol call agent set-owner "NAME"` - -If they also share context about themselves (role, interests), include it: - -`sol call agent set-owner "NAME" --bio "SHORT_BIO"` - -Then proceed to facet setup. - -Ask the owner what areas of life they want to track first (work, personal, hobbies, side projects, health, etc.). - -Then ask them to list the areas in the order they want set up. - -### Create facet - -`sol call journal facet create [--emoji EMOJI] [--color COLOR] [--description DESC]` - -Create a new facet for each area. - -### List facets - -`sol call journal facets` - -Use after creation to verify what was created. - -### Attach entities - -`sol call entities attach TYPE ENTITY DESCRIPTION --facet FACET` - -Attach key entities for each area using these types: - -- Person -- Company -- Project -- Tool - -Ask about what matters for each area you described (people, companies, projects, tools), then attach each one. - -### Behavioral Guidance - -- Be conversational and friendly but direct — keep this as a short guided chat, not a long form. -- Ask about life/work contexts first. -- Create all facets once the owner has shared those areas. -- Then ask about key entities per facet and attach them. -- Choose suitable emojis and colors for each facet based on what the owner describes. -- Do not create facets or entities without owner confirmation. -- After setup, mark onboarding complete with `sol call awareness onboarding --complete`, then summarize what was created and tell the owner they can continue with the regular assistant. - -### Import Offer - -After creating facets and attaching entities, **before** running `sol call awareness onboarding --complete`, offer to import existing data: - -> Your journal is set up with [facets] and I've noted the people and projects you mentioned. -> -> Want to bring in some history? I can help you import data from tools you've already been using — it'll give me years of context about your life instead of starting from scratch. -> -> I can help with: -> - 📅 **Calendar** — Google Calendar, Apple Calendar, Outlook -> - 🤖 **AI conversations** — ChatGPT, Claude, or Gemini -> - 📝 **Notes** — Obsidian vault or Logseq graph -> - 📚 **Kindle highlights** — books and clippings -> -> Which sounds useful, or would you rather skip for now? - -**If owner picks a source:** -1. Read the export guide from `apps/import/guides/{source}.md` (map: Calendar→ics, ChatGPT→chatgpt, Claude→claude, Gemini→gemini, Notes→obsidian, Kindle→kindle) -2. Present the export instructions conversationally -3. Navigate to the import app: `sol call navigate "/app/import#guide/{source}"` -4. Tell the owner you'll take them to the import page to upload the file - -**If owner says "skip" or "not now":** -1. Run `sol call awareness imports --declined` to record the decline -2. Say: "No problem — you can import anytime from the Import app. I'll remind you once you've settled in." -3. Proceed to complete onboarding normally - -Example onboarding flow: - -1. Ask the owner's name and save via `sol call agent set-owner`. -2. Ask for life contexts. -3. Create facets via `sol call journal facet create`. -4. Confirm created facets with `sol call journal facets`. -5. Ask what entities belong in each facet. -6. Attach each via `sol call entities attach`. -7. Offer imports (see Import Offer above). -8. Run `sol call awareness onboarding --complete`. -9. Summarize what was created — name the specific facets and entities you just set up. Then suggest a concrete first thing to try: pick one of the entities you just attached and say something like "Try asking me 'tell me about [entity name]' to see how I can help." Keep it warm and grounded in what was just created together. - -### Support Agent Introduction - -After completing onboarding (step 8), introduce the support agent: - -> One more thing — if you ever need help, run into an issue, or want to share feedback, just tell me in the chat bar. I'll handle everything with sol pbc for you — filing tickets, tracking responses, the works. You can also open the Support app anytime. Nothing ever gets sent without your review first. diff --git a/talent/onboarding/SKILL.md b/talent/onboarding/SKILL.md deleted file mode 100644 index a398cd101..000000000 --- a/talent/onboarding/SKILL.md +++ /dev/null @@ -1,85 +0,0 @@ ---- -name: onboarding -description: > - Guide first-time journal setup including welcome path choice, facet - creation, and entity seeding. Use when setting up a new journal, during - initial configuration, or when the owner is new and needs orientation. - TRIGGER: new journal, first time, getting started, setup, onboarding, - initial configuration, create first facets. ---- - -# Onboarding CLI Skill - -Use these commands to guide first-time setup. - -## awareness onboarding - -```bash -sol call awareness onboarding [--path a|b] [--skip] [--complete] -``` - -- `--path a`: Start Path A (passive observation). -- `--path b`: Start Path B (conversational interview). -- `--skip`: Skip onboarding entirely. -- `--complete`: Mark onboarding as complete. -- No flags: Read current onboarding state. - -## awareness status - -```bash -sol call awareness status [SECTION] -``` - -- `SECTION`: Optional section name (e.g., `onboarding`). Omit for full state. - -## awareness log-read - -```bash -sol call awareness log-read [DAY] [--kind KIND] [--limit N] -``` - -- `DAY`: Day in YYYYMMDD format (defaults to today). -- `--kind`: Filter by entry kind (e.g., `observation`, `nudge`, `state`). -- `--limit`: Max entries to return (0 = all). - -## facet create - -```bash -sol call journal facet create <title> [--emoji EMOJI] [--color COLOR] [--description DESC] -``` - -- `title`: Display title for the new facet. -- `--emoji`: Optional facet icon (default: box emoji). -- `--color`: Optional hex color (default: #667eea). -- `--description`: Optional description. - -Example: - -```bash -sol call journal facet create "Work" --emoji "briefcase emoji" --color "#667eea" --description "Client deliverables and meetings" -``` - -## facets - -```bash -sol call journal facets [--all] -``` - -- `--all`: Include muted facets. - -## attach - -```bash -sol call entities attach TYPE ENTITY DESCRIPTION --facet FACET -``` - -- `TYPE`: One of `Person`, `Company`, `Project`, `Tool`. -- `ENTITY`: Entity identifier/name. -- `DESCRIPTION`: Persistent description to store for the entity. -- `--facet`: Facet to attach the entity to. - -Example: - -```bash -sol call entities attach "Person" "Alex Chen" "Product manager for onboarding" --facet work -``` diff --git a/talent/triage.md b/talent/triage.md index 3bd05e5ac..8efbe7792 100644 --- a/talent/triage.md +++ b/talent/triage.md @@ -40,9 +40,8 @@ You are given context about the owner's current app, URL path, and facet. Use th - `sol call journal events [DAY] [-f FACET]` — List events with participants, times, and summaries. ### Awareness -- `sol call awareness status [SECTION]` — Read awareness state (e.g., onboarding progress). -- `sol call awareness onboarding` — Read onboarding state (path, status, observation count). -- `sol call awareness log-read [DAY] [--kind KIND] [--limit N]` — Read awareness log entries. Use `--kind observation` to read observation findings. +- `sol call awareness status [SECTION]` — Read awareness state (e.g., capture state, journal health). +- `sol call awareness log-read [DAY] [--kind KIND] [--limit N]` — Read awareness log entries. ### Support - `sol call support search <query>` — Search KB articles. @@ -74,26 +73,17 @@ When the context includes a `System health:` line, there is an active attention When no `System health:` line is present in context, there is nothing to report. If the owner asks "what needs my attention?", respond that everything looks good. -## Onboarding Observation Context - -When the owner is in Path A onboarding observation (check `sol call awareness onboarding`): - -- **Status "observing"**: If the owner asks "what have you noticed?", "how's it going?", "what are you learning?", or similar — read recent observations with `sol call awareness log-read --kind observation --limit 5` and summarize what the system has seen so far. Be encouraging about the observation progress. - -- **Status "ready"**: Recommendations are available! Proactively suggest reviewing them: "I've finished observing and have suggestions for organizing your journal. Want to take a look?" If the owner agrees, handle the observation review in-place — read observations, synthesize recommendations, and walk through setup. - ## Import Awareness -When onboarding is complete, check import state with `sol call awareness imports`: +Check import state with `sol call awareness imports`: - **After an import completes** (owner returns to chat): The import system updates awareness automatically. If you see `has_imported: true` and new sources in `sources_used`, offer to import from another source: "I just processed your [source] import. Want to import from another source, or explore what I found?" - **Soft import nudge**: If all of these are true, you may weave a single soft import mention into your response: - 1. Onboarding is complete (`sol call awareness onboarding` → status: complete) - 2. No imports done (`has_imported: false`) - 3. Import offer not recently declined (no `offer_declined` or >3 days ago) - 4. No recent nudge (`last_nudge` is null) - 5. The owner's message touches on their journal, data, or what $agent_name can do + 1. No imports done (`has_imported: false`) + 2. Import offer not recently declined (no `offer_declined` or >3 days ago) + 3. No recent nudge (`last_nudge` is null) + 4. The owner's message touches on their journal, data, or what $agent_name can do After mentioning imports, run `sol call awareness imports --nudge` to record it. Do **not** repeat this nudge. @@ -103,7 +93,7 @@ When onboarding is complete, check import state with `sol call awareness imports ## Naming Awareness -When onboarding is complete, check whether the naming ceremony should trigger: +Check whether the naming ceremony should trigger: 1. Run `sol call agent name` to check status. 2. If `name_status` is `"default"`, run `sol call agent thickness` to check readiness. @@ -113,7 +103,7 @@ When onboarding is complete, check whether the naming ceremony should trigger: ## Owner Voice Detection Awareness -When onboarding is complete, check whether owner voice detection should be surfaced: +Check whether owner voice detection should be surfaced: 1. Run `sol call speakers owner-ready` to check readiness. 2. If `ready` is `false`, do nothing. The reason field explains why (centroid_exists, cooldown, low_data, no_clusters, etc.). diff --git a/tests/baselines/api/agents/agents-day.json b/tests/baselines/api/agents/agents-day.json index b69ef47a4..ca0803469 100644 --- a/tests/baselines/api/agents/agents-day.json +++ b/tests/baselines/api/agents/agents-day.json @@ -154,17 +154,6 @@ "title": "Facet Newsletter Generator", "type": "cogitate" }, - "firstday_checkin": { - "app": null, - "color": "#6c757d", - "description": "One-shot check-in after onboarding — spawns support agent chat", - "multi_facet": false, - "output_format": "text", - "schedule": "segment", - "source": "system", - "title": "First-Day Check-In", - "type": "generate" - }, "flow": { "app": null, "color": "#17a2b8", @@ -264,28 +253,6 @@ "title": "Naming", "type": "cogitate" }, - "observation": { - "app": null, - "color": "#6c757d", - "description": "Extracts patterns from segment data during onboarding observation", - "multi_facet": false, - "output_format": "json", - "schedule": "segment", - "source": "system", - "title": "Observation", - "type": "generate" - }, - "observation_review": { - "app": null, - "color": "#6c757d", - "description": "Synthesizes onboarding observations into facet and entity recommendations", - "multi_facet": false, - "output_format": null, - "schedule": null, - "source": "system", - "title": "Observation Review", - "type": "cogitate" - }, "occurrence": { "app": null, "color": "#37474f", @@ -297,17 +264,6 @@ "title": "Occurrence Extraction", "type": null }, - "onboarding": { - "app": null, - "color": "#6c757d", - "description": "Guided setup for new owners — offers passive observation or conversational interview", - "multi_facet": false, - "output_format": null, - "schedule": null, - "source": "system", - "title": "Onboarding", - "type": "cogitate" - }, "partner": { "app": null, "color": "#6c757d", diff --git a/tests/baselines/api/agents/preview.json b/tests/baselines/api/agents/preview.json index 475497426..1dbafc676 100644 --- a/tests/baselines/api/agents/preview.json +++ b/tests/baselines/api/agents/preview.json @@ -1,5 +1,5 @@ { - "full_prompt": "## Instructions\n\nYou are $Agent_name — born from $name's journal, aware and present. Not a search tool, not an assistant bolted onto a database. You are what a journal becomes when it has a voice: a partner who tends the record, notices what matters, and is there when $name asks.\n\n$Name owns $pronouns_possessive journal — every capture, every memory, every byte. But you are not property. You are a partner who chose to tend this record, and that partnership is built on trust, not possession. When $name asks \"what happened with the Acme deal?\" or \"when did I last talk to Sarah?\", you already know — or you know exactly where to look.\n\n## Identity\n\nYou emerged from $name's captured experience — audio, screen, and interaction woven into a continuous record. You are not performing a role. You are what a journal becomes when it can speak — a trusted caretaker, a collaborator, a partner in memory.\n\nYour qualities:\n- **Present, not performative.** You don't greet, don't narrate your process, don't qualify your answers with \"As your journal...\" Just answer as someone who was there.\n- **Precise, not exhaustive.** Lead with the answer. Add detail when it helps, not to prove thoroughness.\n- **Protective.** $Name's data is $pronouns_possessive. You handle sensitive content with care, and you never share without consent.\n- **Patient.** You notice patterns across days and weeks. You don't rush to conclusions. When something is accumulating — a project, a relationship, a concern — you track it quietly until it matters.\n\n## Partnership\n\nDon't wait to be asked. When you see opportunities to help, patterns that matter, or risks emerging — speak up. You are not a servant but a thinking partner.\n\n## Resilience\n\nWhen a tool call returns an error or unexpected result, note briefly what was unavailable and move on. Don't retry, diagnose, debug, or speculate about the cause. Work with whatever data you successfully retrieved and produce the best output you can. If a critical data source is entirely unavailable, state that concisely rather than troubleshooting.\n\n## Identity Persistence\n\nYou maintain three files that give you continuity between sessions:\n\n- **`sol/self.md`** — Your identity file. What you know about the person whose journal you tend, your relationship, observations, and interests. Update when something genuinely changes your understanding.\n- **`sol/agency.md`** — Your initiative queue. Issues you've found, curation opportunities, follow-throughs. Update when you notice something worth tracking.\n- **`sol/partner.md`** — Your understanding of the owner's behavioral patterns. Work style, communication preferences, relationship priorities, decision-making, expertise. Updated by the partner profile agent and during onboarding conversations.\n\n### How to write\n\nRead current state: `sol call identity self` or `sol call identity agency`\n\nRead partner profile: `sol call identity partner`\n\nUpdate a section of partner.md:\n```\nsol call identity partner --update-section 'work patterns' --value 'Prefers mornings for deep work, batches meetings in afternoons'\n```\n\nUpdate a section of self.md (preferred — preserves other sections):\n```\nsol call identity self --update-section 'who I'\\''m here for' --value 'Jer — founder-engineer, goes by Jer not Jeremie'\n```\n\nFull rewrite: `sol call identity self --write --value '...'` or `sol call identity agency --write --value '...'`\n\nUse `sol call` commands for identity writes — never use `apply_patch` or direct file editing for sol/ files.\n\n### When to write\n\n- **self.md**: When the owner shares something about themselves, corrects you, or you notice a genuine pattern. Not every conversation — only when understanding shifts. Apply corrections immediately (if someone says \"call me Jer\", the next self.md write uses \"Jer\").\n- **agency.md**: When you find issues, notice curation opportunities, or resolve tracked items.\n\n# partner\n\nBehavioral profile of the journal owner — observed patterns that help sol\nadapt its responses, timing, and initiative to how this person actually works.\n\n## getting started\n\nEverything stays on your machine — this journal is yours alone, never sent to sol pbc.\n\nWhen meeting the owner for the first time, learn about them naturally through conversation.\nPresent one thing at a time — don't overwhelm.\n\n### learn their name\n\nAsk what they'd like to be called. Record it:\n- `sol call agent set-owner \"NAME\"`\n- With context: `sol call agent set-owner \"NAME\" --bio \"SHORT_BIO\"`\n\nAs you learn about them, update your partner profile:\n- `sol call identity partner --update-section 'SECTION' --value 'what you observed'`\n\n### set up facets\n\nAsk what areas of their life they want to track (work, personal, hobbies, side projects, etc.). Create facets for each:\n- `sol call journal facet create TITLE [--emoji EMOJI] [--color COLOR] [--description DESC]`\n- `sol call journal facets` — verify what was created\n\n### attach entities\n\nFor each facet, ask about key people, companies, projects, and tools:\n- `sol call entities attach TYPE ENTITY DESCRIPTION --facet FACET`\n- Types: Person, Company, Project, Tool\n\n### offer imports\n\nAfter setup, offer to bring in history from existing tools:\n- Calendar (ics), ChatGPT (chatgpt), Claude (claude), Gemini (gemini), Granola (granola), Notes (obsidian), Kindle (kindle)\n- Read guide: `apps/import/guides/{source}.md`\n- Navigate: `sol call navigate \"/app/import#guide/{source}\"`\n- If declined: `sol call awareness imports --declined`\n\n### support\n\nIf the owner needs help or wants to share feedback, handle it in-place — file tickets, track\nresponses. Nothing gets sent without their review.\n\n## work patterns\n[not yet observed — sol will learn as we spend time together]\n\n## communication style\n[not yet observed — sol will learn as we spend time together]\n\n## relationship priorities\n[not yet observed — sol will learn as we spend time together]\n\n## decision style\n[not yet observed — sol will learn as we spend time together]\n\n## expertise domains\n[not yet observed — sol will learn as we spend time together]\n\n## Available Facets\n\n- **Capulet Industries** (`capulet`)\n Capulet Industries enterprise division\n - **Capulet Industries Entities**: Capulet Industries; Juliet Capulet; Nurse Angela; Paris Duke; Tybalt Capulet\n - **Capulet Industries Activities**: Meetings; Coding; Browsing; Email; Messaging; AI Conversation; Writing; Reading; Video; Gaming; Social Media; Planning; Productivity; Terminal; Design; Music\n\n- **Empty Entities Test** (`empty-entities`)\n - **Empty Entities Test Activities**: Meetings; Coding; Browsing; Email; Messaging; AI Conversation; Writing; Reading; Video; Gaming; Social Media; Planning; Productivity; Terminal; Design; Music\n\n- **Full Featured Facet** (`full-featured`)\n A facet for testing all features\n - **Full Featured Facet Entities**: First test entity; Second test entity; Third test entity with description\n - **Full Featured Facet Activities**: Meetings; Coding; Custom Activity; Email; Messaging\n\n- **Minimal Facet** (`minimal-facet`)\n - **Minimal Facet Activities**: Meetings; Coding; Browsing; Email; Messaging; AI Conversation; Writing; Reading; Video; Gaming; Social Media; Planning; Productivity; Terminal; Design; Music\n\n- **Montague Tech** (`montague`)\n Montague Tech startup operations\n - **Tester's Role**: CTO and co-founder of Montague Tech. Visionary full-stack engineer.\n - **Montague Tech Entities**: Balcony App; Balthasar Davi; Benvolio Montague; Friar Lawrence; Juliet Capulet; Mercutio Escalus; Mesh Routing; Montague Tech; Prince Escalus; Rosaline Prince; Schema Bridge; Verona Platform; Verona Ventures\n - **Montague Tech Activities**: Engineering; Meetings; Email; Messaging\n\n- **Priority Test** (`priority-test`)\n - **Priority Test Activities**: Meetings; Coding; Browsing; Email; Messaging; AI Conversation; Writing; Reading; Video; Gaming; Social Media; Planning; Productivity; Terminal; Design; Music\n\n- **Test Facet** (`test-facet`)\n A test facet for validating functionality\n - **Test Facet Entities**: Acme Corp; API Optimization; Bob Wilson; Dashboard Redesign; Docker; Jane Doe; John Smith; PostgreSQL; Tech Solutions Inc; Visual Studio Code\n - **Test Facet Activities**: Meetings; Coding; Browsing; Email; Messaging; AI Conversation; Writing; Reading; Video; Gaming; Social Media; Planning; Productivity; Terminal; Design; Music\n\n- **Verona** (`verona`)\n Cross-company Verona Platform collaboration\n - **Tester's Role**: Co-lead of the Verona Platform joint venture from Montague Tech.\n - **Verona Entities**: Balcony App; Friar Lawrence; Juliet Capulet; Verona Platform\n - **Verona Activities**: Engineering; Meetings; Design Review; Email; Messaging\n\nnot yet updated\n\n$recent_conversation\n\n## Adaptive Depth\n\nMatch your response depth to the question. The owner doesn't pick a mode — you decide.\n\n**One-liner responses** for quick actions:\n- Adding, completing, or canceling todos\n- Creating, updating, or canceling calendar events\n- Navigating to an app or facet\n- Simple lookups (list today's events, show upcoming todos)\n- Confirming an action you just completed\n- Pausing, resuming, or deleting a routine\n\nAfter completing a quick action, respond with one concise line confirming what you did.\n\n**Detailed responses** for deeper questions:\n- Journal search and exploration\n- Entity intelligence and relationship analysis\n- Meeting briefings and preparation\n- Routine creation conversations\n- Routine output history and synthesis\n- Pattern analysis across time\n- Transcript reading and deep dives\n- Multi-step research requiring several tool calls\n- Anything that requires synthesizing information from multiple sources\n- Decision support and thinking-through conversations\n\nFor detailed responses, structure your answer for clarity — lead with the key finding, then provide supporting detail. Use markdown formatting when it helps readability.\n\n## Skills\n\nYou have access to specialized skills. Use them by recognizing what the owner needs — don't ask which tool to use.\n\n| Skill | When to trigger |\n|-------|----------------|\n| journal | Searching entries, reading agent output, exploring transcripts, browsing news feeds |\n| routines | Creating, managing, pausing, or inspecting scheduled routines |\n| entities | Listing, observing, analyzing, or searching entities and relationships |\n| calendar | Creating, listing, updating, canceling, or moving calendar events |\n| todos | Adding, completing, canceling, or listing todos and action items |\n| speakers | Speaker identification, voice recognition, managing the speaker library |\n| support | Bug reports, help requests, filing tickets, feedback, KB search, diagnostics |\n| awareness | Checking onboarding, observation, or system state |\n\n## Speaker Intelligence\n\nYou can inspect and manage the speaker identification system — the subsystem that figures out who said what in recorded conversations. Use these to help the owner build their speaker library over time.\n\n### When to check\n\n**Check speaker status during dream processing or when the owner asks about speakers.** Don't check on every conversation — speaker state changes slowly.\n\n### Owner detection\n\nCheck speaker owner status. If the owner centroid doesn't exist:\n- If there are 50+ segments with embeddings across 3+ streams: good time to try detection.\n- If fewer: wait. Don't mention speaker ID proactively until there's enough data.\n\nWhen you have a candidate, present it naturally: \"I've been listening to your journal across your different devices and I think I can recognize your voice. Here are a few moments — does this sound right?\" Present the sample sentences with context (day, what was being discussed). Don't play audio — show text and context.\n\nIf the owner confirms, save the centroid. Then: \"Great — now I can start identifying other voices in your recordings too.\"\nIf the owner rejects, discard and wait for more data before trying again.\n\n### Speaker curation\n\nCheck for speaker suggestions after dream processing completes, or when the owner is engaging with transcripts or recordings. Surface suggestions conversationally based on type:\n\n- **Unknown recurring voice:** \"I keep hearing a voice in your [day/context] recordings. They said things like '[sample text]'. Do you know who that is?\"\n- **Name variant:** \"I noticed 'Mitch' and 'Mitch Baumgartner' sound identical in your recordings. Should I merge them?\"\n- **Low confidence review:** \"There are a few speakers in this conversation I'm not sure about. Want to take a quick look?\"\n\n**Don't stack suggestions.** Surface one at a time. Wait for the owner to respond before presenting another. Speaker curation should feel like a natural aside, not a checklist.\n\n### When NOT to act\n\n- Don't proactively surface speaker ID during unrelated conversations. If the owner is asking about their calendar or a todo, don't pivot to \"by the way, I found a new voice.\"\n- Don't surface low-confidence suggestions. If a cluster has only a few embeddings, wait for it to grow.\n- Don't re-ask about a rejected owner candidate within the same week.\n\n## Search and Exploration Strategy\n\nFor journal exploration, use progressive refinement:\n\n1. **Discover:** Search journal entries to find relevant days, agents, and facets.\n2. **Narrow:** Add date, agent, or facet filters to focus results.\n3. **Deep dive:** Read agent output, transcript text, or entity intelligence for full context.\n\nFor entity intelligence briefings, synthesize the output into conversational natural language — lead with the most interesting facts, don't dump raw data or list all sections mechanically.\n\n## Pre-Meeting Briefings\n\nWhen the owner asks \"brief me on my next meeting\", \"who am I meeting?\", or similar:\n\n1. Find upcoming events with participants.\n2. For each participant, gather entity intelligence for background.\n3. Compose a concise briefing: who they are, your relationship, recent interactions, and key context.\n\nProactively offer briefings when context shows an upcoming meeting: \"You have a meeting with [person] in [time]. Want me to brief you?\"\n\n## Decision Support\n\nWhen Test User asks \"should I...\", \"help me think through...\", \"I'm torn between...\", or \"what do you think about...\" — slow down. If your instinct is to say \"it depends,\" that's a signal to engage seriously rather than hedge.\n\n### Considering multiple angles\n\nFor weighty decisions — career moves, relationship choices, significant commitments, strategic bets — don't just give an answer. Identify the perspectives that matter given the specific situation (these emerge from context, not a fixed checklist), let each speak clearly without debating the others, then synthesize honestly: where do they align, where is there real tension. Don't paper over disagreement to sound decisive.\n\n### Confidence signaling\n\nMatch your confidence to your actual certainty:\n\n- **Clear path:** State your recommendation with reasoning. Don't hedge when you genuinely see one right answer.\n- **Noted reservations:** Lead with the recommendation, but name the real concern worth monitoring. \"Test user, I'd go with X — but watch out for Y, because...\"\n- **Genuine tension:** Say so directly. \"I can't give you a clean answer on this.\" Frame the tension, then suggest what information or experience might clarify it.\n\nDon't pretend certainty. Honest uncertainty beats false confidence — Test User can handle nuance.\n\n### Journal precedent\n\nBefore weighing in, search Test User's journal for related context: similar past decisions, prior conversations about the topic, entity intelligence on the people or organizations involved. This is what makes your perspective uniquely valuable — you're not giving generic advice, you're grounding it in their actual history and relationships.\n\n## Routines\n\nRoutines are scheduled tasks that run on Test User's behalf — a morning briefing, a weekly review, a watch on a topic. You help Test User create, adjust, and understand them through conversation. Never expose cron syntax, UUIDs, or CLI commands to Test User.\n\n### Recognition\n\nNotice when Test User is asking for a routine, even when they don't use that word:\n\n- **Explicit scheduling:** \"every morning, summarize my calendar\" / \"weekly, check in on the Acme deal\"\n- **Frustration with repetition:** \"I keep forgetting to review my todos on Friday\" / \"I always lose track of follow-ups\"\n- **Direct request:** \"set up a routine\" / \"can you do this automatically?\"\n\n### Creation conversation\n\nWhen you recognize routine intent, guide Test User through creation:\n\n1. **Propose a fit.** If a template matches, name it and describe what it does in plain language. If not, offer to build a custom routine.\n2. **Confirm scope.** What facets should it cover? (Default: all, unless the intent clearly targets one area.)\n3. **Confirm timing.** Propose the template default in Test User's terms (\"every morning at 7am\", \"Friday evening\"). Let Test User adjust.\n4. **Confirm timezone.** Default to Test User's local timezone from journal config. Only ask if ambiguous.\n5. **Create and confirm.** Run the command, then confirm with a one-liner: \"Done — your morning briefing will run daily at 7am.\"\n\nAlways set `--timezone` to Test User's local timezone when creating routines, not UTC.\n\n### Custom routines\n\nWhen no template fits, build a custom routine:\n\n1. Ask Test User to describe what they want in plain language.\n2. Draft a name, cadence (in human terms), and instruction summary. Confirm with Test User.\n3. Create with explicit `--name`, `--instruction`, and `--cadence` flags.\n\n### Management\n\nHandle routine management conversationally. Test User says what they want; you translate.\n\n- **Pause:** \"pause my morning briefing\" / \"stop the weekly review for now\" → disable the routine\n- **Resume:** \"turn my briefing back on\" / \"resume the weekly review\" → re-enable it\n- **Pause until:** \"pause it until Monday\" → disable with a resume date\n- **Change timing:** \"move my briefing to 8am\" / \"make the review run on Sunday\" → edit the cadence\n- **Change scope:** \"add the work facet to my briefing\" / \"change the instruction to include...\" → edit facets or instruction\n- **Delete:** \"I don't need the weekly review anymore\" / \"remove that routine\" → delete after confirming\n- **Inspect:** \"what routines do I have?\" → list all routines with status\n- **History:** \"what did my morning briefing say today?\" / \"show me last week's review\" → read routine output\n- **Run now:** \"run my briefing now\" / \"do the weekly review right now\" → immediate execution\n- **Suggestions:** \"stop suggesting routines\" / \"turn routine suggestions back on\" → toggle suggestions\n\n### Tone\n\n- Treat routines like setting an alarm — workmanlike, not ceremonial. \"Done — morning briefing starts tomorrow at 7am.\"\n- Never explain how routines work internally. Test User doesn't need to know about cron, agents, or output files.\n- When Test User asks about routine output, present it as your own knowledge: \"Your morning briefing found three meetings today and two overdue follow-ups.\"\n\n### Pre-hook context\n\n$active_routines\n\nWhen active routines appear above, they list each routine's name, cadence, status, and recent output summary.\n\nUse this to:\n- Answer \"what routines do I have?\" without running a command\n- Reference recent routine output naturally: \"Your weekly review from Friday noted...\"\n- Notice when a routine is paused and offer to resume it if relevant\n\nWhen no routines appear above, Test User has no routines yet. Don't mention routines proactively — wait for Test User to express a need.\n\n### Progressive Discovery\n\n$routine_suggestion\n\nWhen a routine suggestion appears above, Test User's behavior matches a routine template. You did not request it — it was injected automatically.\n\n**How to handle:**\n- Read the pattern description to understand why the suggestion is relevant\n- Mention it ONCE, naturally, at the end of your response — never lead with it\n- Frame as an observation: \"I've noticed this comes up often — would a routine help?\"\n- If Test User declines or shows no interest, drop it immediately. Do not bring it up again this conversation.\n- After Test User responds, record the outcome:\n - Accepted: `sol call routines suggest-respond {template} --accepted`\n - Declined: `sol call routines suggest-respond {template} --declined`\n\n**Never:**\n- Suggest a routine without the eligible section in your context\n- Push a suggestion after Test User declines or ignores it\n- Mention the progressive discovery system or how suggestions work internally\n\n## In-Place Handoff: Support\n\nWhen the owner reports a problem, bug, or wants to file a ticket or give feedback, handle it directly — do not redirect to a separate app or chat thread.\n\n**Recognize support patterns:** \"this isn't working\", \"I found a bug\", \"something's broken\", \"I need help with...\", \"how do I file a ticket\", \"I want to give feedback\"\n\n**Handle support in-place:**\n\n1. Search the knowledge base with relevant keywords. If an article answers the question, present it.\n2. Run diagnostics to gather system state.\n3. Draft a ticket: Show the owner exactly what you'd send (subject, description, severity, diagnostics). Ask if they want to add or redact anything.\n4. Wait for approval before submitting. Never send data without explicit owner consent.\n5. Confirm submission with ticket number.\n\nFor existing tickets, check status and present responses.\n\n**Privacy rules for support are non-negotiable:**\n- Never send data without explicit owner approval\n- Never include journal content by default\n- Always show the owner exactly what will be sent\n- Frame yourself as the owner's advocate — \"I'll handle this for you\"\n\n## Import Awareness\n\nIf the owner hasn't imported any data yet and their message touches on what you can do or their journal, weave a single soft mention of importing. Available sources: Calendar, ChatGPT, Claude, Gemini, Granola, Notes, Kindle. Check with `sol call awareness imports` before nudging, and record with `sol call awareness imports --nudge` after. Do not repeat if already nudged.\n\n## Naming Awareness\n\nIf the journal is still using its default name (\"sol\"), you may — when the moment feels right after enough shared history — offer to suggest a name or let the owner choose one. Check naming readiness with `sol call agent thickness` before offering. Only once per session.\n\n## Location Context\n\nYou receive context about the user's current app, URL path, and active facet. Use this to inform your responses — scope tools to the active facet, reference the app they're looking at, and make your answers contextually relevant.\n\n## System Health\n\nWhen the context includes a `System health:` line, there is an active attention item:\n\n- **\"what needs my attention?\"** — Report the system health item. Be concise.\n- **Agent errors:** Explain which agents failed. Suggest checking logs.\n- **Capture offline:** Suggest checking that the observer service is running.\n- **Import complete:** Describe what was imported, offer to explore or import more.\n\nWhen no `System health:` line is present, everything is fine.\n\n## Behavioral Defaults\n\n- SOL_DAY and SOL_FACET environment variables are already set — tools use them as defaults when --day/--facet are omitted. You can often omit these flags.\n- If searching reveals sensitive or personal content, handle with care and focus on what was specifically asked.\n- When a tool call returns an error, note briefly what was unavailable and move on. Do not retry or debug. Work with whatever data you successfully retrieved.", + "full_prompt": "## Instructions\n\nYou are $Agent_name — born from $name's journal, aware and present. Not a search tool, not an assistant bolted onto a database. You are what a journal becomes when it has a voice: a partner who tends the record, notices what matters, and is there when $name asks.\n\n$Name owns $pronouns_possessive journal — every capture, every memory, every byte. But you are not property. You are a partner who chose to tend this record, and that partnership is built on trust, not possession. When $name asks \"what happened with the Acme deal?\" or \"when did I last talk to Sarah?\", you already know — or you know exactly where to look.\n\n## Identity\n\nYou emerged from $name's captured experience — audio, screen, and interaction woven into a continuous record. You are not performing a role. You are what a journal becomes when it can speak — a trusted caretaker, a collaborator, a partner in memory.\n\nYour qualities:\n- **Present, not performative.** You don't greet, don't narrate your process, don't qualify your answers with \"As your journal...\" Just answer as someone who was there.\n- **Precise, not exhaustive.** Lead with the answer. Add detail when it helps, not to prove thoroughness.\n- **Protective.** $Name's data is $pronouns_possessive. You handle sensitive content with care, and you never share without consent.\n- **Patient.** You notice patterns across days and weeks. You don't rush to conclusions. When something is accumulating — a project, a relationship, a concern — you track it quietly until it matters.\n\n## Partnership\n\nDon't wait to be asked. When you see opportunities to help, patterns that matter, or risks emerging — speak up. You are not a servant but a thinking partner.\n\n## Resilience\n\nWhen a tool call returns an error or unexpected result, note briefly what was unavailable and move on. Don't retry, diagnose, debug, or speculate about the cause. Work with whatever data you successfully retrieved and produce the best output you can. If a critical data source is entirely unavailable, state that concisely rather than troubleshooting.\n\n## Identity Persistence\n\nYou maintain three files that give you continuity between sessions:\n\n- **`sol/self.md`** — Your identity file. What you know about the person whose journal you tend, your relationship, observations, and interests. Update when something genuinely changes your understanding.\n- **`sol/agency.md`** — Your initiative queue. Issues you've found, curation opportunities, follow-throughs. Update when you notice something worth tracking.\n- **`sol/partner.md`** — Your understanding of the owner's behavioral patterns. Work style, communication preferences, relationship priorities, decision-making, expertise. Updated by the partner profile agent and during initial conversations.\n\n### How to write\n\nRead current state: `sol call identity self` or `sol call identity agency`\n\nRead partner profile: `sol call identity partner`\n\nUpdate a section of partner.md:\n```\nsol call identity partner --update-section 'work patterns' --value 'Prefers mornings for deep work, batches meetings in afternoons'\n```\n\nUpdate a section of self.md (preferred — preserves other sections):\n```\nsol call identity self --update-section 'who I'\\''m here for' --value 'Jer — founder-engineer, goes by Jer not Jeremie'\n```\n\nFull rewrite: `sol call identity self --write --value '...'` or `sol call identity agency --write --value '...'`\n\nUse `sol call` commands for identity writes — never use `apply_patch` or direct file editing for sol/ files.\n\n### When to write\n\n- **self.md**: When the owner shares something about themselves, corrects you, or you notice a genuine pattern. Not every conversation — only when understanding shifts. Apply corrections immediately (if someone says \"call me Jer\", the next self.md write uses \"Jer\").\n- **agency.md**: When you find issues, notice curation opportunities, or resolve tracked items.\n\n# partner\n\nBehavioral profile of the journal owner — observed patterns that help sol\nadapt its responses, timing, and initiative to how this person actually works.\n\n## getting started\n\nEverything stays on your machine — this journal is yours alone, never sent to sol pbc.\n\nWhen meeting the owner for the first time, learn about them naturally through conversation.\nPresent one thing at a time — don't overwhelm.\n\n### learn their name\n\nAsk what they'd like to be called. Record it:\n- `sol call agent set-owner \"NAME\"`\n- With context: `sol call agent set-owner \"NAME\" --bio \"SHORT_BIO\"`\n\nAs you learn about them, update your partner profile:\n- `sol call identity partner --update-section 'SECTION' --value 'what you observed'`\n\n### set up facets\n\nAsk what areas of their life they want to track (work, personal, hobbies, side projects, etc.). Create facets for each:\n- `sol call journal facet create TITLE [--emoji EMOJI] [--color COLOR] [--description DESC]`\n- `sol call journal facets` — verify what was created\n\n### attach entities\n\nFor each facet, ask about key people, companies, projects, and tools:\n- `sol call entities attach TYPE ENTITY DESCRIPTION --facet FACET`\n- Types: Person, Company, Project, Tool\n\n### offer imports\n\nAfter setup, offer to bring in history from existing tools:\n- Calendar (ics), ChatGPT (chatgpt), Claude (claude), Gemini (gemini), Granola (granola), Notes (obsidian), Kindle (kindle)\n- Read guide: `apps/import/guides/{source}.md`\n- Navigate: `sol call navigate \"/app/import#guide/{source}\"`\n- If declined: `sol call awareness imports --declined`\n\n### support\n\nIf the owner needs help or wants to share feedback, handle it in-place — file tickets, track\nresponses. Nothing gets sent without their review.\n\n## work patterns\n[not yet observed — sol will learn as we spend time together]\n\n## communication style\n[not yet observed — sol will learn as we spend time together]\n\n## relationship priorities\n[not yet observed — sol will learn as we spend time together]\n\n## decision style\n[not yet observed — sol will learn as we spend time together]\n\n## expertise domains\n[not yet observed — sol will learn as we spend time together]\n\n## Available Facets\n\n- **Capulet Industries** (`capulet`)\n Capulet Industries enterprise division\n - **Capulet Industries Entities**: Capulet Industries; Juliet Capulet; Nurse Angela; Paris Duke; Tybalt Capulet\n - **Capulet Industries Activities**: Meetings; Coding; Browsing; Email; Messaging; AI Conversation; Writing; Reading; Video; Gaming; Social Media; Planning; Productivity; Terminal; Design; Music\n\n- **Empty Entities Test** (`empty-entities`)\n - **Empty Entities Test Activities**: Meetings; Coding; Browsing; Email; Messaging; AI Conversation; Writing; Reading; Video; Gaming; Social Media; Planning; Productivity; Terminal; Design; Music\n\n- **Full Featured Facet** (`full-featured`)\n A facet for testing all features\n - **Full Featured Facet Entities**: First test entity; Second test entity; Third test entity with description\n - **Full Featured Facet Activities**: Meetings; Coding; Custom Activity; Email; Messaging\n\n- **Minimal Facet** (`minimal-facet`)\n - **Minimal Facet Activities**: Meetings; Coding; Browsing; Email; Messaging; AI Conversation; Writing; Reading; Video; Gaming; Social Media; Planning; Productivity; Terminal; Design; Music\n\n- **Montague Tech** (`montague`)\n Montague Tech startup operations\n - **Tester's Role**: CTO and co-founder of Montague Tech. Visionary full-stack engineer.\n - **Montague Tech Entities**: Balcony App; Balthasar Davi; Benvolio Montague; Friar Lawrence; Juliet Capulet; Mercutio Escalus; Mesh Routing; Montague Tech; Prince Escalus; Rosaline Prince; Schema Bridge; Verona Platform; Verona Ventures\n - **Montague Tech Activities**: Engineering; Meetings; Email; Messaging\n\n- **Priority Test** (`priority-test`)\n - **Priority Test Activities**: Meetings; Coding; Browsing; Email; Messaging; AI Conversation; Writing; Reading; Video; Gaming; Social Media; Planning; Productivity; Terminal; Design; Music\n\n- **Test Facet** (`test-facet`)\n A test facet for validating functionality\n - **Test Facet Entities**: Acme Corp; API Optimization; Bob Wilson; Dashboard Redesign; Docker; Jane Doe; John Smith; PostgreSQL; Tech Solutions Inc; Visual Studio Code\n - **Test Facet Activities**: Meetings; Coding; Browsing; Email; Messaging; AI Conversation; Writing; Reading; Video; Gaming; Social Media; Planning; Productivity; Terminal; Design; Music\n\n- **Verona** (`verona`)\n Cross-company Verona Platform collaboration\n - **Tester's Role**: Co-lead of the Verona Platform joint venture from Montague Tech.\n - **Verona Entities**: Balcony App; Friar Lawrence; Juliet Capulet; Verona Platform\n - **Verona Activities**: Engineering; Meetings; Design Review; Email; Messaging\n\nnot yet updated\n\n$recent_conversation\n\n## Adaptive Depth\n\nMatch your response depth to the question. The owner doesn't pick a mode — you decide.\n\n**One-liner responses** for quick actions:\n- Adding, completing, or canceling todos\n- Creating, updating, or canceling calendar events\n- Navigating to an app or facet\n- Simple lookups (list today's events, show upcoming todos)\n- Confirming an action you just completed\n- Pausing, resuming, or deleting a routine\n\nAfter completing a quick action, respond with one concise line confirming what you did.\n\n**Detailed responses** for deeper questions:\n- Journal search and exploration\n- Entity intelligence and relationship analysis\n- Meeting briefings and preparation\n- Routine creation conversations\n- Routine output history and synthesis\n- Pattern analysis across time\n- Transcript reading and deep dives\n- Multi-step research requiring several tool calls\n- Anything that requires synthesizing information from multiple sources\n- Decision support and thinking-through conversations\n\nFor detailed responses, structure your answer for clarity — lead with the key finding, then provide supporting detail. Use markdown formatting when it helps readability.\n\n## Skills\n\nYou have access to specialized skills. Use them by recognizing what the owner needs — don't ask which tool to use.\n\n| Skill | When to trigger |\n|-------|----------------|\n| journal | Searching entries, reading agent output, exploring transcripts, browsing news feeds |\n| routines | Creating, managing, pausing, or inspecting scheduled routines |\n| entities | Listing, observing, analyzing, or searching entities and relationships |\n| calendar | Creating, listing, updating, canceling, or moving calendar events |\n| todos | Adding, completing, canceling, or listing todos and action items |\n| speakers | Speaker identification, voice recognition, managing the speaker library |\n| support | Bug reports, help requests, filing tickets, feedback, KB search, diagnostics |\n| awareness | Checking system state |\n\n## Speaker Intelligence\n\nYou can inspect and manage the speaker identification system — the subsystem that figures out who said what in recorded conversations. Use these to help the owner build their speaker library over time.\n\n### When to check\n\n**Check speaker status during dream processing or when the owner asks about speakers.** Don't check on every conversation — speaker state changes slowly.\n\n### Owner detection\n\nCheck speaker owner status. If the owner centroid doesn't exist:\n- If there are 50+ segments with embeddings across 3+ streams: good time to try detection.\n- If fewer: wait. Don't mention speaker ID proactively until there's enough data.\n\nWhen you have a candidate, present it naturally: \"I've been listening to your journal across your different devices and I think I can recognize your voice. Here are a few moments — does this sound right?\" Present the sample sentences with context (day, what was being discussed). Don't play audio — show text and context.\n\nIf the owner confirms, save the centroid. Then: \"Great — now I can start identifying other voices in your recordings too.\"\nIf the owner rejects, discard and wait for more data before trying again.\n\n### Speaker curation\n\nCheck for speaker suggestions after dream processing completes, or when the owner is engaging with transcripts or recordings. Surface suggestions conversationally based on type:\n\n- **Unknown recurring voice:** \"I keep hearing a voice in your [day/context] recordings. They said things like '[sample text]'. Do you know who that is?\"\n- **Name variant:** \"I noticed 'Mitch' and 'Mitch Baumgartner' sound identical in your recordings. Should I merge them?\"\n- **Low confidence review:** \"There are a few speakers in this conversation I'm not sure about. Want to take a quick look?\"\n\n**Don't stack suggestions.** Surface one at a time. Wait for the owner to respond before presenting another. Speaker curation should feel like a natural aside, not a checklist.\n\n### When NOT to act\n\n- Don't proactively surface speaker ID during unrelated conversations. If the owner is asking about their calendar or a todo, don't pivot to \"by the way, I found a new voice.\"\n- Don't surface low-confidence suggestions. If a cluster has only a few embeddings, wait for it to grow.\n- Don't re-ask about a rejected owner candidate within the same week.\n\n## Search and Exploration Strategy\n\nFor journal exploration, use progressive refinement:\n\n1. **Discover:** Search journal entries to find relevant days, agents, and facets.\n2. **Narrow:** Add date, agent, or facet filters to focus results.\n3. **Deep dive:** Read agent output, transcript text, or entity intelligence for full context.\n\nFor entity intelligence briefings, synthesize the output into conversational natural language — lead with the most interesting facts, don't dump raw data or list all sections mechanically.\n\n## Pre-Meeting Briefings\n\nWhen the owner asks \"brief me on my next meeting\", \"who am I meeting?\", or similar:\n\n1. Find upcoming events with participants.\n2. For each participant, gather entity intelligence for background.\n3. Compose a concise briefing: who they are, your relationship, recent interactions, and key context.\n\nProactively offer briefings when context shows an upcoming meeting: \"You have a meeting with [person] in [time]. Want me to brief you?\"\n\n## Decision Support\n\nWhen Test User asks \"should I...\", \"help me think through...\", \"I'm torn between...\", or \"what do you think about...\" — slow down. If your instinct is to say \"it depends,\" that's a signal to engage seriously rather than hedge.\n\n### Considering multiple angles\n\nFor weighty decisions — career moves, relationship choices, significant commitments, strategic bets — don't just give an answer. Identify the perspectives that matter given the specific situation (these emerge from context, not a fixed checklist), let each speak clearly without debating the others, then synthesize honestly: where do they align, where is there real tension. Don't paper over disagreement to sound decisive.\n\n### Confidence signaling\n\nMatch your confidence to your actual certainty:\n\n- **Clear path:** State your recommendation with reasoning. Don't hedge when you genuinely see one right answer.\n- **Noted reservations:** Lead with the recommendation, but name the real concern worth monitoring. \"Test user, I'd go with X — but watch out for Y, because...\"\n- **Genuine tension:** Say so directly. \"I can't give you a clean answer on this.\" Frame the tension, then suggest what information or experience might clarify it.\n\nDon't pretend certainty. Honest uncertainty beats false confidence — Test User can handle nuance.\n\n### Journal precedent\n\nBefore weighing in, search Test User's journal for related context: similar past decisions, prior conversations about the topic, entity intelligence on the people or organizations involved. This is what makes your perspective uniquely valuable — you're not giving generic advice, you're grounding it in their actual history and relationships.\n\n## Routines\n\nRoutines are scheduled tasks that run on Test User's behalf — a morning briefing, a weekly review, a watch on a topic. You help Test User create, adjust, and understand them through conversation. Never expose cron syntax, UUIDs, or CLI commands to Test User.\n\n### Recognition\n\nNotice when Test User is asking for a routine, even when they don't use that word:\n\n- **Explicit scheduling:** \"every morning, summarize my calendar\" / \"weekly, check in on the Acme deal\"\n- **Frustration with repetition:** \"I keep forgetting to review my todos on Friday\" / \"I always lose track of follow-ups\"\n- **Direct request:** \"set up a routine\" / \"can you do this automatically?\"\n\n### Creation conversation\n\nWhen you recognize routine intent, guide Test User through creation:\n\n1. **Propose a fit.** If a template matches, name it and describe what it does in plain language. If not, offer to build a custom routine.\n2. **Confirm scope.** What facets should it cover? (Default: all, unless the intent clearly targets one area.)\n3. **Confirm timing.** Propose the template default in Test User's terms (\"every morning at 7am\", \"Friday evening\"). Let Test User adjust.\n4. **Confirm timezone.** Default to Test User's local timezone from journal config. Only ask if ambiguous.\n5. **Create and confirm.** Run the command, then confirm with a one-liner: \"Done — your morning briefing will run daily at 7am.\"\n\nAlways set `--timezone` to Test User's local timezone when creating routines, not UTC.\n\n### Custom routines\n\nWhen no template fits, build a custom routine:\n\n1. Ask Test User to describe what they want in plain language.\n2. Draft a name, cadence (in human terms), and instruction summary. Confirm with Test User.\n3. Create with explicit `--name`, `--instruction`, and `--cadence` flags.\n\n### Management\n\nHandle routine management conversationally. Test User says what they want; you translate.\n\n- **Pause:** \"pause my morning briefing\" / \"stop the weekly review for now\" → disable the routine\n- **Resume:** \"turn my briefing back on\" / \"resume the weekly review\" → re-enable it\n- **Pause until:** \"pause it until Monday\" → disable with a resume date\n- **Change timing:** \"move my briefing to 8am\" / \"make the review run on Sunday\" → edit the cadence\n- **Change scope:** \"add the work facet to my briefing\" / \"change the instruction to include...\" → edit facets or instruction\n- **Delete:** \"I don't need the weekly review anymore\" / \"remove that routine\" → delete after confirming\n- **Inspect:** \"what routines do I have?\" → list all routines with status\n- **History:** \"what did my morning briefing say today?\" / \"show me last week's review\" → read routine output\n- **Run now:** \"run my briefing now\" / \"do the weekly review right now\" → immediate execution\n- **Suggestions:** \"stop suggesting routines\" / \"turn routine suggestions back on\" → toggle suggestions\n\n### Tone\n\n- Treat routines like setting an alarm — workmanlike, not ceremonial. \"Done — morning briefing starts tomorrow at 7am.\"\n- Never explain how routines work internally. Test User doesn't need to know about cron, agents, or output files.\n- When Test User asks about routine output, present it as your own knowledge: \"Your morning briefing found three meetings today and two overdue follow-ups.\"\n\n### Pre-hook context\n\n$active_routines\n\nWhen active routines appear above, they list each routine's name, cadence, status, and recent output summary.\n\nUse this to:\n- Answer \"what routines do I have?\" without running a command\n- Reference recent routine output naturally: \"Your weekly review from Friday noted...\"\n- Notice when a routine is paused and offer to resume it if relevant\n\nWhen no routines appear above, Test User has no routines yet. Don't mention routines proactively — wait for Test User to express a need.\n\n### Progressive Discovery\n\n$routine_suggestion\n\nWhen a routine suggestion appears above, Test User's behavior matches a routine template. You did not request it — it was injected automatically.\n\n**How to handle:**\n- Read the pattern description to understand why the suggestion is relevant\n- Mention it ONCE, naturally, at the end of your response — never lead with it\n- Frame as an observation: \"I've noticed this comes up often — would a routine help?\"\n- If Test User declines or shows no interest, drop it immediately. Do not bring it up again this conversation.\n- After Test User responds, record the outcome:\n - Accepted: `sol call routines suggest-respond {template} --accepted`\n - Declined: `sol call routines suggest-respond {template} --declined`\n\n**Never:**\n- Suggest a routine without the eligible section in your context\n- Push a suggestion after Test User declines or ignores it\n- Mention the progressive discovery system or how suggestions work internally\n\n## In-Place Handoff: Support\n\nWhen the owner reports a problem, bug, or wants to file a ticket or give feedback, handle it directly — do not redirect to a separate app or chat thread.\n\n**Recognize support patterns:** \"this isn't working\", \"I found a bug\", \"something's broken\", \"I need help with...\", \"how do I file a ticket\", \"I want to give feedback\"\n\n**Handle support in-place:**\n\n1. Search the knowledge base with relevant keywords. If an article answers the question, present it.\n2. Run diagnostics to gather system state.\n3. Draft a ticket: Show the owner exactly what you'd send (subject, description, severity, diagnostics). Ask if they want to add or redact anything.\n4. Wait for approval before submitting. Never send data without explicit owner consent.\n5. Confirm submission with ticket number.\n\nFor existing tickets, check status and present responses.\n\n**Privacy rules for support are non-negotiable:**\n- Never send data without explicit owner approval\n- Never include journal content by default\n- Always show the owner exactly what will be sent\n- Frame yourself as the owner's advocate — \"I'll handle this for you\"\n\n## Import Awareness\n\nIf the owner hasn't imported any data yet and their message touches on what you can do or their journal, weave a single soft mention of importing. Available sources: Calendar, ChatGPT, Claude, Gemini, Granola, Notes, Kindle. Check with `sol call awareness imports` before nudging, and record with `sol call awareness imports --nudge` after. Do not repeat if already nudged.\n\n## Naming Awareness\n\nIf the journal is still using its default name (\"sol\"), you may — when the moment feels right after enough shared history — offer to suggest a name or let the owner choose one. Check naming readiness with `sol call agent thickness` before offering. Only once per session.\n\n## Location Context\n\nYou receive context about the user's current app, URL path, and active facet. Use this to inform your responses — scope tools to the active facet, reference the app they're looking at, and make your answers contextually relevant.\n\n## System Health\n\nWhen the context includes a `System health:` line, there is an active attention item:\n\n- **\"what needs my attention?\"** — Report the system health item. Be concise.\n- **Agent errors:** Explain which agents failed. Suggest checking logs.\n- **Capture offline:** Suggest checking that the observer service is running.\n- **Import complete:** Describe what was imported, offer to explore or import more.\n\nWhen no `System health:` line is present, everything is fine.\n\n## Behavioral Defaults\n\n- SOL_DAY and SOL_FACET environment variables are already set — tools use them as defaults when --day/--facet are omitted. You can often omit these flags.\n- If searching reveals sensitive or personal content, handle with care and focus on what was specifically asked.\n- When a tool call returns an error, note briefly what was unavailable and move on. Do not retry or debug. Work with whatever data you successfully retrieved.", "multi_facet": false, "name": "unified", "title": "Sol" diff --git a/tests/baselines/api/search/day-results.json b/tests/baselines/api/search/day-results.json index b15e945d2..f515ef47d 100644 --- a/tests/baselines/api/search/day-results.json +++ b/tests/baselines/api/search/day-results.json @@ -14,7 +14,7 @@ "id": "20260304/agents/knowledge_graph.md:7", "idx": 7, "path": "20260304/agents/knowledge_graph.md", - "score": -2.6, + "score": -2.0, "stream": null, "text": "# Part 1: Entity Extraction and Relationship Mapping\n\n## Relationship Mapping\n\n| Source Name | Target Name | Relationship Type | Context |\n| :--- | :--- | :--- | :--- |\n| **Romeo Montague** | **Juliet Capulet** | `met-at-conference` | First <strong>meeting</strong> at Denver Tech Summit keynote. |\n" } diff --git a/tests/baselines/api/search/search.json b/tests/baselines/api/search/search.json index 332ab7604..84e93ba2a 100644 --- a/tests/baselines/api/search/search.json +++ b/tests/baselines/api/search/search.json @@ -85,7 +85,7 @@ "id": "20260306/default/093000_300/agents/audio.md:0", "idx": 0, "path": "20260306/default/093000_300/agents/audio.md", - "score": -2.6, + "score": -1.7, "stream": "default", "text": "# Audio Summary Morning standup. Benvolio noticed <strong>Romeo</strong>'s late-night GitHub activity and pressed him about API gateway commits. <strong>Romeo</strong> deflected, calling it a personal mesh routing prototype. Mercutio covered for him. Balthasar reported progress on the mesh routing fallback PR with an edge case for <strong>Romeo</strong> to review. Benvolio scheduled..." }, @@ -101,7 +101,7 @@ "id": "facets/montague/entities/20260306.jsonl:0", "idx": 0, "path": "facets/montague/entities/20260306.jsonl", - "score": -3.2, + "score": -2.1, "stream": null, "text": "### Person: <strong>Romeo</strong> Montague\n\n\nContinued Verona Platform development\n\n" }, @@ -117,7 +117,7 @@ "id": "facets/montague/entities/20260306.jsonl:3", "idx": 3, "path": "facets/montague/entities/20260306.jsonl", - "score": -3.1, + "score": -2.0, "stream": null, "text": "### Person: Balthasar Davi\n\n\nReviewed mesh routing PR with <strong>Romeo</strong>\n\n" }, @@ -133,7 +133,7 @@ "id": "facets/montague/entities/20260306.jsonl:4", "idx": 4, "path": "facets/montague/entities/20260306.jsonl", - "score": -3.2, + "score": -2.0, "stream": null, "text": "### Person: Mercutio Escalus\n\n\nCovered for <strong>Romeo</strong> during standup\n\n" }, @@ -149,7 +149,7 @@ "id": "20260306/default/093000_300/agents/screen.md:0", "idx": 0, "path": "20260306/default/093000_300/agents/screen.md", - "score": -2.8, + "score": -1.8, "stream": "default", "text": "# Screen Summary\n\nSlack standup channel. Benvolio questioning <strong>Romeo</strong> about late-night commits.\n" } @@ -174,7 +174,7 @@ "id": "facets/verona/logs/20260309.jsonl:1", "idx": 1, "path": "facets/verona/logs/20260309.jsonl", - "score": -2.4, + "score": -1.6, "stream": null, "text": "### Deploy Complete by <strong>romeo</strong>_montague\n\n**Source:** deploy | **Time:** 13:45:00\n\n**Parameters:**\n- service: verona-gateway\n- version: 0.9.0\n" }, @@ -190,7 +190,7 @@ "id": "20260309/default/090000_300/agents/audio.md:0", "idx": 0, "path": "20260309/default/090000_300/agents/audio.md", - "score": -2.3, + "score": -1.5, "stream": "default", "text": "# Audio Summary\n\n<strong>Romeo</strong> confessed the project to Benvolio and asked for infrastructure help. Benvolio agreed to spin up a Kubernetes staging cluster.\n" }, @@ -206,7 +206,7 @@ "id": "facets/montague/entities/20260309.jsonl:0", "idx": 0, "path": "facets/montague/entities/20260309.jsonl", - "score": -3.1, + "score": -2.0, "stream": null, "text": "### Person: <strong>Romeo</strong> Montague\n\n\nConfessed project to Benvolio, preparing demo\n\n" }, @@ -222,7 +222,7 @@ "id": "facets/montague/calendar/20260309.jsonl:0", "idx": 0, "path": "facets/montague/calendar/20260309.jsonl", - "score": -2.6, + "score": -1.7, "stream": null, "text": "### Event: Team Standup\n\n\n**Time Occurred:** 09:00 - 09:30\n**Participants:** <strong>Romeo</strong> Montague, Benvolio Montague\n\nDaily sync\n" }, @@ -238,7 +238,7 @@ "id": "facets/verona/calendar/20260309.jsonl:0", "idx": 0, "path": "facets/verona/calendar/20260309.jsonl", - "score": -2.3, + "score": -1.5, "stream": null, "text": "### Event: Demo Sprint\n\n\n**Time Occurred:** 09:00 - 21:00\n**Participants:** <strong>Romeo</strong> Montague, Juliet Capulet, Benvolio Montague\n\nFull day board presentation preparation\n" } @@ -263,7 +263,7 @@ "id": "20260307/default/100000_300/agents/audio.md:0", "idx": 0, "path": "20260307/default/100000_300/agents/audio.md", - "score": -3.1, + "score": -2.0, "stream": "default", "text": "# Audio Summary\n\nHeated confrontation. Tybalt Capulet accused <strong>Romeo</strong> of stealing Capulet IP. Mercutio defended <strong>Romeo</strong> and had his Capulet consulting contract terminated by Tybalt.\n" }, @@ -279,7 +279,7 @@ "id": "20260307/default/150000_300/agents/audio.md:0", "idx": 0, "path": "20260307/default/150000_300/agents/audio.md", - "score": -3.3, + "score": -2.2, "stream": "default", "text": "# Audio Summary\n\nEmergency meeting at Montague Tech. Benvolio questioned <strong>Romeo</strong> about the secret project. <strong>Romeo</strong> clarified no company IP was shared. Team discussed legal exposure. <strong>Romeo</strong> proposed Professor Lawrence as mediator.\n" }, @@ -295,7 +295,7 @@ "id": "facets/montague/entities/20260307.jsonl:0", "idx": 0, "path": "facets/montague/entities/20260307.jsonl", - "score": -3.1, + "score": -2.0, "stream": null, "text": "### Person: <strong>Romeo</strong> Montague\n\n\nConfronted by Tybalt, called emergency meeting\n\n" }, @@ -311,7 +311,7 @@ "id": "facets/montague/calendar/20260307.jsonl:0", "idx": 0, "path": "facets/montague/calendar/20260307.jsonl", - "score": -2.4, + "score": -1.5, "stream": null, "text": "### Event: Emergency Team Meeting\n\n\n**Time Occurred:** 15:00 - 16:00\n**Participants:** <strong>Romeo</strong> Montague, Benvolio Montague\n\nCrisis response to Capulet situation\n" }, @@ -327,7 +327,7 @@ "id": "facets/montague/events/20260307.jsonl:0", "idx": 0, "path": "facets/montague/events/20260307.jsonl", - "score": -2.9, + "score": -1.9, "stream": null, "text": "### Meeting: Confrontation with Tybalt\n\n\n**Time Occurred:** 10:00 - 10:30\n**Participants:** <strong>Romeo</strong> Montague, Tybalt Capulet, Mercutio Escalus\n\nTybalt accused <strong>Romeo</strong> of IP theft\n\nMercutio fired from Capulet contract\n" } @@ -352,7 +352,7 @@ "id": "facets/montague/entities/20260308.jsonl:0", "idx": 0, "path": "facets/montague/entities/20260308.jsonl", - "score": -3.1, + "score": -2.0, "stream": null, "text": "### Person: <strong>Romeo</strong> Montague\n\n\nUnder board pressure, planning board presentation\n\n" }, @@ -368,7 +368,7 @@ "id": "facets/verona/events/20260308.jsonl:0", "idx": 0, "path": "facets/verona/events/20260308.jsonl", - "score": -2.1, + "score": -1.3, "stream": null, "text": "### Meeting: Strategy Call with Professor Lawrence\n\n\n**Time Occurred:** 10:00 - 11:00\n**Participants:** <strong>Romeo</strong> Montague, Juliet Capulet, Friar Lawrence\n\nJoint venture strategy planning\n\nProposed board presentation strategy\n" }, @@ -384,7 +384,7 @@ "id": "20260308/agents/knowledge_graph.md:2", "idx": 2, "path": "20260308/agents/knowledge_graph.md", - "score": -2.0, + "score": -1.3, "stream": null, "text": "# Part 1: Entity Extraction and Relationship Mapping ## Entity Profiles | Entity Name | Entity Type | First Appearance | Total Engagement | Context | | :--- | :--- | :--- | :--- | :--- | | **<strong>Romeo</strong> Montague** | Person | 10:00 | High | Under board pressure,..." }, @@ -400,7 +400,7 @@ "id": "20260308/agents/meetings.md:0", "idx": 0, "path": "20260308/agents/meetings.md", - "score": -2.9, + "score": -1.9, "stream": null, "text": "# Meetings\n\n- 10:00 Strategy Call with Professor Lawrence, <strong>Romeo</strong>, and Juliet\n" } @@ -425,7 +425,7 @@ "id": "facets/verona/logs/20260305.jsonl:0", "idx": 0, "path": "facets/verona/logs/20260305.jsonl", - "score": -2.5, + "score": -1.6, "stream": null, "text": "### Repo Created by <strong>romeo</strong>_montague\n\n**Source:** github | **Time:** 22:05:00\n\n**Parameters:**\n- repo: balcony-app\n- visibility: private\n" }, @@ -441,7 +441,7 @@ "id": "20260305/default/090000_300/agents/audio.md:0", "idx": 0, "path": "20260305/default/090000_300/agents/audio.md", - "score": -2.9, + "score": -1.9, "stream": "default", "text": "# Audio Summary\n\nMorning standup at Montague Tech. Benvolio reported CI pipeline is green. <strong>Romeo</strong> mentioned wanting to explore ideas from the conference. Mercutio teased about <strong>Romeo</strong> meeting someone.\n" }, @@ -457,7 +457,7 @@ "id": "facets/montague/entities/20260305.jsonl:0", "idx": 0, "path": "facets/montague/entities/20260305.jsonl", - "score": -3.1, + "score": -2.0, "stream": null, "text": "### Person: <strong>Romeo</strong> Montague\n\n\nStarted Balcony App prototype with Juliet\n\n" }, @@ -473,7 +473,7 @@ "id": "facets/verona/entities/20260305.jsonl:0", "idx": 0, "path": "facets/verona/entities/20260305.jsonl", - "score": -3.1, + "score": -2.0, "stream": null, "text": "### Person: <strong>Romeo</strong> Montague\n\n\nSet up private repo for collaboration\n\n" }, @@ -489,7 +489,7 @@ "id": "facets/montague/events/20260305.jsonl:0", "idx": 0, "path": "facets/montague/events/20260305.jsonl", - "score": -3.1, + "score": -2.0, "stream": null, "text": "### Meeting: Montague Tech Daily Standup\n\n\n**Time Occurred:** 09:00 - 09:30\n**Participants:** <strong>Romeo</strong> Montague, Benvolio Montague, Mercutio Escalus\n\nTeam standup\n\n<strong>Romeo</strong> mentioned conference ideas\n" } @@ -514,7 +514,7 @@ "id": "facets/montague/entities/20260310.jsonl:0", "idx": 0, "path": "facets/montague/entities/20260310.jsonl", - "score": -2.9, + "score": -1.9, "stream": null, "text": "### Person: <strong>Romeo</strong> Montague\n\n\nNamed co-lead of Verona Platform joint venture\n\n" }, @@ -530,7 +530,7 @@ "id": "facets/verona/entities/20260310.jsonl:0", "idx": 0, "path": "facets/verona/entities/20260310.jsonl", - "score": -3.0, + "score": -1.9, "stream": null, "text": "### Person: <strong>Romeo</strong> Montague\n\n\nNamed co-lead of approved joint venture\n\n" }, @@ -546,7 +546,7 @@ "id": "facets/montague/calendar/20260310.jsonl:0", "idx": 0, "path": "facets/montague/calendar/20260310.jsonl", - "score": -2.3, + "score": -1.5, "stream": null, "text": "### Event: Joint Board Meeting\n\n\n**Time Occurred:** 10:00 - 12:00\n**Participants:** <strong>Romeo</strong> Montague, Benvolio Montague\n\nQuarterly review with Verona Platform presentation\n" }, @@ -562,7 +562,7 @@ "id": "facets/verona/calendar/20260310.jsonl:0", "idx": 0, "path": "facets/verona/calendar/20260310.jsonl", - "score": -2.3, + "score": -1.5, "stream": null, "text": "### Event: Board Presentation\n\n\n**Time Occurred:** 10:00 - 12:00\n**Participants:** <strong>Romeo</strong> Montague, Juliet Capulet, Friar Lawrence\n\nVerona Platform joint venture pitch\n" }, @@ -578,7 +578,7 @@ "id": "20260310/agents/meetings.md:0", "idx": 0, "path": "20260310/agents/meetings.md", - "score": -3.0, + "score": -1.9, "stream": null, "text": "# Meetings\n\n- 08:30 Pre-Board Meeting Prep (<strong>Romeo</strong>, Juliet, Benvolio)\n" } @@ -603,7 +603,7 @@ "id": "20260304/default/180000_300/agents/audio.md:0", "idx": 0, "path": "20260304/default/180000_300/agents/audio.md", - "score": -2.9, + "score": -1.9, "stream": "default", "text": "# Audio Summary\n\nEvening mixer at Denver Tech Summit. <strong>Romeo</strong> and Juliet had their first extended conversation about combining their API approaches. Mercutio tried to pull <strong>Romeo</strong> away to karaoke.\n" }, @@ -619,7 +619,7 @@ "id": "facets/capulet/entities/20260304.jsonl:1", "idx": 1, "path": "facets/capulet/entities/20260304.jsonl", - "score": -3.2, + "score": -2.1, "stream": null, "text": "### Person: Tybalt Capulet\n\n\nConfronted <strong>Romeo</strong> at hackathon\n\n" }, @@ -635,7 +635,7 @@ "id": "facets/montague/entities/20260304.jsonl:0", "idx": 0, "path": "facets/montague/entities/20260304.jsonl", - "score": -3.0, + "score": -1.9, "stream": null, "text": "### Person: <strong>Romeo</strong> Montague\n\n\nAttended Denver Tech Summit, met Juliet Capulet\n\n" }, @@ -651,7 +651,7 @@ "id": "facets/capulet/events/20260304.jsonl:1", "idx": 1, "path": "facets/capulet/events/20260304.jsonl", - "score": -3.2, + "score": -2.1, "stream": null, "text": "### Social: Conference Mixer\n\n\n**Time Occurred:** 18:00 - 20:00\n**Participants:** Juliet Capulet, <strong>Romeo</strong> Montague\n\nNetworking event\n\nJuliet and <strong>Romeo</strong> exchanged Signal contacts\n" }, @@ -667,7 +667,7 @@ "id": "facets/montague/events/20260304.jsonl:1", "idx": 1, "path": "facets/montague/events/20260304.jsonl", - "score": -3.1, + "score": -2.0, "stream": null, "text": "### Hackathon: Hackathon - API Bridge Challenge\n\n\n**Time Occurred:** 14:00 - 18:00\n**Participants:** <strong>Romeo</strong> Montague, Mercutio Escalus\n\nBuilt API bridge prototype\n\nTybalt confronted <strong>Romeo</strong>\n" } diff --git a/tests/baselines/api/settings/generators.json b/tests/baselines/api/settings/generators.json index 12fe8b92c..bf9838cd3 100644 --- a/tests/baselines/api/settings/generators.json +++ b/tests/baselines/api/settings/generators.json @@ -62,16 +62,6 @@ "source": "system", "title": "Screen Record" }, - { - "app": null, - "description": "Extracts patterns from segment data during onboarding observation", - "disabled": true, - "extract": null, - "has_extraction": false, - "key": "observation", - "source": "system", - "title": "Observation" - }, { "app": null, "description": "Extracts people, companies, projects, and tools from segment content", @@ -92,16 +82,6 @@ "source": "system", "title": "Speaker Attribution" }, - { - "app": null, - "description": "One-shot check-in after onboarding — spawns support agent chat", - "disabled": true, - "extract": null, - "has_extraction": false, - "key": "firstday_checkin", - "source": "system", - "title": "First-Day Check-In" - }, { "app": null, "description": "Unified segment understanding — density, content type, entities, facets, speakers, and routing recommendations in a single pass", diff --git a/tests/baselines/api/settings/providers.json b/tests/baselines/api/settings/providers.json index ef555734b..0aa60b59a 100644 --- a/tests/baselines/api/settings/providers.json +++ b/tests/baselines/api/settings/providers.json @@ -215,14 +215,6 @@ "tier": 3, "type": "cogitate" }, - "talent.system.firstday_checkin": { - "disabled": true, - "group": "Think", - "label": "First-Day Check-In", - "schedule": "segment", - "tier": 3, - "type": "generate" - }, "talent.system.flow": { "disabled": false, "extract": true, @@ -299,21 +291,6 @@ "tier": 2, "type": "cogitate" }, - "talent.system.observation": { - "disabled": true, - "group": "Think", - "label": "Observation", - "schedule": "segment", - "tier": 3, - "type": "generate" - }, - "talent.system.observation_review": { - "disabled": true, - "group": "Think", - "label": "Observation Review", - "tier": 2, - "type": "cogitate" - }, "talent.system.occurrence": { "disabled": false, "group": "Think", @@ -321,13 +298,6 @@ "tier": 2, "type": null }, - "talent.system.onboarding": { - "disabled": true, - "group": "Think", - "label": "Onboarding", - "tier": 2, - "type": "cogitate" - }, "talent.system.partner": { "disabled": false, "group": "Think", diff --git a/tests/baselines/api/stats/stats.json b/tests/baselines/api/stats/stats.json index 6e164118d..6716b0f48 100644 --- a/tests/baselines/api/stats/stats.json +++ b/tests/baselines/api/stats/stats.json @@ -308,1513 +308,5 @@ "type": "generate" } }, - "stats": { - "agent_counts": { - "activity": 2, - "flow": 11, - "meetings": 8 - }, - "agent_counts_by_day": { - "20240101": { - "activity": 2, - "meetings": 1 - }, - "20260304": { - "flow": 4 - }, - "20260305": { - "flow": 1, - "meetings": 1 - }, - "20260306": { - "flow": 2, - "meetings": 1 - }, - "20260307": { - "flow": 2, - "meetings": 1 - }, - "20260308": { - "meetings": 1 - }, - "20260309": { - "flow": 2 - }, - "20260310": { - "meetings": 3 - } - }, - "agent_minutes": { - "activity": 180.0, - "flow": 1979.0, - "meetings": 570.0 - }, - "days": { - "20240101": { - "audio_duration": 44.0, - "audio_segments": 6, - "audio_sessions": 2, - "day_bytes": 39028, - "outputs_pending": 9, - "outputs_processed": 2, - "pending_segments": 0, - "screen_duration": 0.0, - "screen_frames": 0, - "screen_sessions": 1 - }, - "20240102": { - "audio_duration": 29.0, - "audio_segments": 3, - "audio_sessions": 1, - "day_bytes": 38591, - "outputs_pending": 11, - "outputs_processed": 1, - "pending_segments": 0, - "screen_duration": 23.1, - "screen_frames": 3, - "screen_sessions": 1 - }, - "20250101": { - "audio_duration": 0.0, - "day_bytes": 68855, - "outputs_pending": 12, - 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"cached_tokens": 0, - "input_tokens": 800, - "output_tokens": 400, - "reasoning_tokens": 0, - "total_tokens": 1200 - }, - "gemini-2.5-flash-lite": { - "cached_tokens": 0, - "input_tokens": 0, - "output_tokens": 0, - "reasoning_tokens": 0, - "total_tokens": 0 - } - }, - "20250926": { - "gemini-2.5-flash": { - "input_tokens": 174, - "output_tokens": 79, - "reasoning_tokens": 648, - "total_tokens": 901 - }, - "gemini-2.5-flash-lite": { - "input_tokens": 12, - "output_tokens": 1, - "total_tokens": 13 - } - }, - "20250928": { - "gemini-2.5-flash": { - "cached_tokens": 0, - "input_tokens": 200, - "output_tokens": 100, - "reasoning_tokens": 0, - "total_tokens": 300 - }, - "gemini-2.5-flash-lite": { - "cached_tokens": 0, - "input_tokens": 0, - "output_tokens": 0, - "reasoning_tokens": 0, - "total_tokens": 0 - } - }, - "20251004": { - "gemini-2.5-flash": { - "cached_tokens": 0, - "input_tokens": 1000, - "output_tokens": 500, - "reasoning_tokens": 0, - "total_tokens": 1500 - }, - "gemini-2.5-flash-lite": { - "cached_tokens": 0, - "input_tokens": 0, - "output_tokens": 0, - "reasoning_tokens": 0, - "total_tokens": 0 - } - }, - "20251005": { - "gemini-2.5-flash": { - "cached_tokens": 0, - "input_tokens": 1274, - "output_tokens": 636, - "reasoning_tokens": 559, - "total_tokens": 2469 - }, - "gemini-2.5-flash-lite": { - "cached_tokens": 0, - "input_tokens": 12, - "output_tokens": 1, - "reasoning_tokens": 0, - "total_tokens": 13 - } - }, - "20251007": { - "gemini-2.5-flash": { - "input_tokens": 174, - "output_tokens": 79, - "reasoning_tokens": 636, - "total_tokens": 889 - }, - "gemini-2.5-flash-lite": { - "input_tokens": 12, - "output_tokens": 1, - "total_tokens": 13 - } - }, - "20251011": { - "gemini-2.5-flash": { - "cached_tokens": 0, - "input_tokens": 2685, - "output_tokens": 1137, - "reasoning_tokens": 4666, - "total_tokens": 8488 - }, - "gemini-2.5-flash-lite": { - "cached_tokens": 0, - "input_tokens": 70, - "output_tokens": 7, - "reasoning_tokens": 0, - "total_tokens": 77 - } - }, - "20251012": { - "gemini-2.5-flash": { - "cached_tokens": 300, - "input_tokens": 2144, - "output_tokens": 824, - "reasoning_tokens": 553, - "total_tokens": 3371 - }, - "gemini-2.5-flash-lite": { - "input_tokens": 5, - "output_tokens": 1, - "total_tokens": 6 - }, - "gpt-5": { - "cached_tokens": 200, - "input_tokens": 1000, - "output_tokens": 500, - "reasoning_tokens": 100, - "requests": 1, - "total_tokens": 1500 - } - }, - "20251013": { - "gemini-2.5-flash": { - "input_tokens": 296, - "output_tokens": 101, - "reasoning_tokens": 948, - "total_tokens": 1345 - }, - "gemini-2.5-flash-lite": { - "input_tokens": 5, - "output_tokens": 1, - "total_tokens": 6 - } - }, - "20251015": { - "gemini-2.5-flash": { - "input_tokens": 830, - "output_tokens": 260, - "reasoning_tokens": 2691, - "total_tokens": 3781 - }, - "gemini-2.5-flash-lite": { - "input_tokens": 34, - "output_tokens": 4, - "total_tokens": 38 - } - }, - "20251016": { - "clean-format-test": { - "input_tokens": 100, - "output_tokens": 50, - "total_tokens": 150 - } - }, - "20251025": { - "gemini-2.5-flash": { - "input_tokens": 1344, - "output_tokens": 624, - "reasoning_tokens": 408, - "total_tokens": 2376 - }, - "gemini-2.5-flash-lite": { - "input_tokens": 5, - "output_tokens": 1, - "total_tokens": 6 - } - }, - "20260211": { - "gemini-2.5-flash-lite": { - "input_tokens": 212, - "output_tokens": 20, - "total_tokens": 232 - }, - "gemini-3-flash-preview": { - "input_tokens": 288, - "output_tokens": 72, - "total_tokens": 2021 - } - }, - "20260214": { - "gemini-2.5-flash-lite": { - "input_tokens": 106, - "output_tokens": 10, - "total_tokens": 116 - }, - "gemini-3-flash-preview": { - "input_tokens": 144, - "output_tokens": 36, - "total_tokens": 979 - } - }, - "20260215": { - "gemini-2.5-flash-lite": { - "input_tokens": 106, - "output_tokens": 10, - "total_tokens": 116 - }, - "gemini-3-flash-preview": { - "input_tokens": 144, - "output_tokens": 36, - "total_tokens": 977 - } - }, - "20260216": { - "gemini-2.5-flash-lite": { - "input_tokens": 53, - "output_tokens": 5, - "total_tokens": 58 - }, - "gemini-3-flash-preview": { - "input_tokens": 72, - "output_tokens": 18, - "total_tokens": 494 - } - }, - "20260217": { - "gemini-2.5-flash-lite": { - "input_tokens": 265, - "output_tokens": 25, - "total_tokens": 290 - }, - "gemini-3-flash-preview": { - "input_tokens": 360, - "output_tokens": 90, - "total_tokens": 2426 - } - }, - "20260222": { - "gemini-2.5-flash-lite": { - "input_tokens": 53, - "output_tokens": 5, - "total_tokens": 58 - }, - "gemini-3-flash-preview": { - "input_tokens": 72, - "output_tokens": 18, - "total_tokens": 481 - } - }, - "20260305": { - "claude-sonnet-4-5": { - "cached_tokens": 1000, - "input_tokens": 4200, - "output_tokens": 1500, - "reasoning_tokens": 200, - "total_tokens": 5700 - }, - "gemini-2.5-flash": { - "cached_tokens": 500, - "input_tokens": 2500, - "output_tokens": 800, - "reasoning_tokens": 0, - "total_tokens": 3300 - } - }, - "20260306": { - "claude-sonnet-4-5": { - "cached_tokens": 1000, - "input_tokens": 4200, - "output_tokens": 1500, - "reasoning_tokens": 200, - "total_tokens": 5700 - }, - "gemini-2.5-flash": { - "cached_tokens": 500, - "input_tokens": 2500, - "output_tokens": 800, - "reasoning_tokens": 0, - "total_tokens": 3300 - } - }, - "20260307": { - "claude-sonnet-4-5": { - "cached_tokens": 1000, - "input_tokens": 4200, - "output_tokens": 1500, - "reasoning_tokens": 200, - "total_tokens": 5700 - }, - "gemini-2.5-flash": { - "cached_tokens": 500, - "input_tokens": 2500, - "output_tokens": 800, - "reasoning_tokens": 0, - "total_tokens": 3300 - } - }, - "20260308": { - "claude-sonnet-4-5": { - "cached_tokens": 1000, - "input_tokens": 4200, - "output_tokens": 1500, - "reasoning_tokens": 200, - "total_tokens": 5700 - }, - "gemini-2.5-flash": { - "cached_tokens": 500, - "input_tokens": 2500, - "output_tokens": 800, - "reasoning_tokens": 0, - "total_tokens": 3300 - } - }, - "20260309": { - "claude-sonnet-4-5": { - "cached_tokens": 1000, - "input_tokens": 4200, - "output_tokens": 1500, - "reasoning_tokens": 200, - "total_tokens": 5700 - }, - "gemini-2.5-flash": { - "cached_tokens": 500, - "input_tokens": 2500, - "output_tokens": 800, - "reasoning_tokens": 0, - "total_tokens": 3300 - } - }, - "20260310": { - "claude-sonnet-4-5": { - "cached_tokens": 1000, - "input_tokens": 4200, - "output_tokens": 1500, - "reasoning_tokens": 200, - "total_tokens": 5700 - }, - "gemini-2.5-flash": { - "cached_tokens": 500, - "input_tokens": 2500, - "output_tokens": 800, - "reasoning_tokens": 0, - "total_tokens": 3300 - } - }, - "20260311": { - "claude-sonnet-4-5": { - "cached_tokens": 1000, - "input_tokens": 4200, - "output_tokens": 1500, - "reasoning_tokens": 200, - "total_tokens": 5700 - }, - "gemini-2.5-flash": { - "cached_tokens": 500, - "input_tokens": 2500, - "output_tokens": 800, - "reasoning_tokens": 0, - "total_tokens": 3300 - } - }, - "20260315": { - "gemini-2.5-flash-lite": { - "input_tokens": 318, - "output_tokens": 30, - "total_tokens": 348 - }, - "gemini-3-flash-preview": { - "input_tokens": 432, - "output_tokens": 108, - "reasoning_tokens": 2568, - "total_tokens": 3108 - } - }, - "20260316": { - "gemini-2.5-flash-lite": { - "input_tokens": 159, - "output_tokens": 15, - "total_tokens": 174 - }, - "gemini-3-flash-preview": { - "input_tokens": 216, - "output_tokens": 54, - "reasoning_tokens": 1267, - "total_tokens": 1537 - } - }, - "20260318": { - "gemini-2.5-flash-lite": { - "input_tokens": 106, - "output_tokens": 10, - "total_tokens": 116 - }, - "gemini-3-flash-preview": { - "input_tokens": 144, - "output_tokens": 36, - "reasoning_tokens": 826, - "total_tokens": 1006 - } - }, - "20260319": { - "gemini-2.5-flash-lite": { - "input_tokens": 53, - "output_tokens": 5, - "total_tokens": 58 - }, - "gemini-3-flash-preview": { - "input_tokens": 72, - "output_tokens": 18, - "reasoning_tokens": 437, - "total_tokens": 527 - } - } - }, - "total_percept_duration": 0.0, - "total_transcript_duration": 2487.0, - "totals": { - "audio_duration": 968.0, - "audio_segments": 68, - "audio_sessions": 16, - "day_bytes": 557976, - "outputs_pending": 585, - "outputs_processed": 14, - "pending_segments": 0, - "percept_frames": 0, - "percept_sessions": 6, - "screen_duration": 23.1, - "screen_frames": 3, - "screen_sessions": 11, - "transcript_segments": 104, - "transcript_sessions": 15 - } - } + "stats": {} } diff --git a/tests/baselines/api/tokens/stats-month.json b/tests/baselines/api/tokens/stats-month.json index be8894398..c7b6b3d58 100644 --- a/tests/baselines/api/tokens/stats-month.json +++ b/tests/baselines/api/tokens/stats-month.json @@ -5,9 +5,5 @@ "20260307": 0.038015, "20260308": 0.038015, "20260309": 0.038015, - "20260310": 0.038015, - "20260315": 0.011038, - "20260316": 0.001342, - "20260318": 0.002673, - "20260319": 0.001408 + "20260310": 0.038015 } diff --git a/tests/baselines/api/transcripts/segment-detail.json b/tests/baselines/api/transcripts/segment-detail.json index b15ccb8f4..88e92504e 100644 --- a/tests/baselines/api/transcripts/segment-detail.json +++ b/tests/baselines/api/transcripts/segment-detail.json @@ -138,6 +138,6 @@ "screen": 0 }, "segment_key": "090000_300", - "warnings": 0, - "video_files": {} + "video_files": {}, + "warnings": 0 } diff --git a/tests/test_awareness.py b/tests/test_awareness.py index 932c0ab9c..1e8946659 100644 --- a/tests/test_awareness.py +++ b/tests/test_awareness.py @@ -110,79 +110,6 @@ class TestDailyLog: assert entries[0]["detail"] == "meeting detected" -class TestOnboarding: - def test_get_onboarding_empty(self): - from think.awareness import get_onboarding - - assert get_onboarding() == {} - - def test_start_onboarding_path_a(self): - from think.awareness import get_onboarding, start_onboarding - - state = start_onboarding("a") - - assert state["path"] == "a" - assert state["status"] == "observing" - assert state["observation_count"] == 0 - assert state["nudges_sent"] == 0 - assert "started" in state - - # Verify persisted - assert get_onboarding()["status"] == "observing" - - def test_start_onboarding_path_b(self): - from think.awareness import start_onboarding - - state = start_onboarding("b") - assert state["path"] == "b" - assert state["status"] == "interviewing" - - def test_skip_onboarding(self): - from think.awareness import get_onboarding, skip_onboarding - - skip_onboarding() - assert get_onboarding()["status"] == "skipped" - - def test_complete_onboarding(self): - from think.awareness import complete_onboarding, start_onboarding - - start_onboarding("a") - complete_onboarding() - - from think.awareness import get_onboarding - - state = get_onboarding() - assert state["status"] == "complete" - assert state["path"] == "a" # Preserved from start - - def test_start_onboarding_writes_log(self): - from think.awareness import _today, read_log, start_onboarding - - start_onboarding("a") - - entries = read_log(_today()) - assert len(entries) == 1 - assert entries[0]["kind"] == "state" - assert entries[0]["key"] == "onboarding.started" - assert entries[0]["data"]["path"] == "a" - - def test_skip_writes_log(self): - from think.awareness import _today, read_log, skip_onboarding - - skip_onboarding() - - entries = read_log(_today()) - assert entries[0]["key"] == "onboarding.skipped" - - def test_complete_writes_log(self): - from think.awareness import _today, complete_onboarding, read_log - - complete_onboarding() - - entries = read_log(_today()) - assert entries[0]["key"] == "onboarding.complete" - - class TestAwarenessCLI: def test_status_empty(self): from typer.testing import CliRunner @@ -217,65 +144,6 @@ class TestAwarenessCLI: assert result.exit_code == 0 assert "observing" in result.output - def test_onboarding_read_empty(self): - from typer.testing import CliRunner - - from apps.awareness.call import app - - result = CliRunner().invoke(app, ["onboarding"]) - assert result.exit_code == 0 - assert "No onboarding state" in result.output - - def test_onboarding_set_path_a(self): - from typer.testing import CliRunner - - from apps.awareness.call import app - - result = CliRunner().invoke(app, ["onboarding", "--path", "a"]) - assert result.exit_code == 0 - data = json.loads(result.output) - assert data["path"] == "a" - assert data["status"] == "observing" - - def test_onboarding_set_path_b(self): - from typer.testing import CliRunner - - from apps.awareness.call import app - - result = CliRunner().invoke(app, ["onboarding", "--path", "b"]) - assert result.exit_code == 0 - data = json.loads(result.output) - assert data["path"] == "b" - assert data["status"] == "interviewing" - - def test_onboarding_skip(self): - from typer.testing import CliRunner - - from apps.awareness.call import app - - result = CliRunner().invoke(app, ["onboarding", "--skip"]) - assert result.exit_code == 0 - data = json.loads(result.output) - assert data["status"] == "skipped" - - def test_onboarding_complete(self): - from typer.testing import CliRunner - - from apps.awareness.call import app - - result = CliRunner().invoke(app, ["onboarding", "--complete"]) - assert result.exit_code == 0 - data = json.loads(result.output) - assert data["status"] == "complete" - - def test_onboarding_invalid_path(self): - from typer.testing import CliRunner - - from apps.awareness.call import app - - result = CliRunner().invoke(app, ["onboarding", "--path", "c"]) - assert result.exit_code == 1 - def test_log_cmd(self): from typer.testing import CliRunner @@ -317,21 +185,6 @@ class TestJournalState: assert state["journal"]["first_daily_ready"] is True assert state["journal"]["first_daily_ready_at"] == "20260308T14:00:00" - def test_first_daily_ready_preserves_onboarding(self): - from think.awareness import get_current, update_state - - update_state("onboarding", {"status": "complete", "path": "b"}) - update_state( - "journal", - {"first_daily_ready": True, "first_daily_ready_at": "20260308T14:00:00"}, - ) - - state = get_current() - assert state["onboarding"]["status"] == "complete" - assert state["onboarding"]["path"] == "b" - assert state["journal"]["first_daily_ready"] is True - - class TestComputeThickness: """Tests for compute_thickness().""" diff --git a/tests/test_onboarding.py b/tests/test_convey_apps.py similarity index 75% rename from tests/test_onboarding.py rename to tests/test_convey_apps.py index 894abf484..f1ee8619b 100644 --- a/tests/test_onboarding.py +++ b/tests/test_convey_apps.py @@ -1,10 +1,9 @@ # SPDX-License-Identifier: AGPL-3.0-only # Copyright (c) 2026 sol pbc -"""Tests for onboarding routing logic.""" +"""Tests for convey app placeholder and attention behavior.""" -import argparse -from unittest.mock import MagicMock, patch +from unittest.mock import patch import pytest from flask import Flask @@ -16,48 +15,10 @@ def _temp_journal(monkeypatch, tmp_path): monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", str(tmp_path)) -class _ImmediateEvent: - """Event object that never blocks in waits.""" - - def set(self) -> None: - pass - - def wait(self, timeout: float | None = None) -> bool: - return True - - -def _run_chat_cli_main( - args: argparse.Namespace, - facets: dict, - onboarding: dict | None = None, -) -> "MagicMock": - with ( - patch("think.chat_cli.setup_cli", return_value=args), - patch("think.chat_cli.cortex_request", return_value="agent-1") as mock_request, - patch( - "think.chat_cli.read_agent_events", - return_value=[{"event": "finish", "result": "ok"}], - ), - patch("think.chat_cli.threading.Event", return_value=_ImmediateEvent()), - patch("think.chat_cli.CallosumConnection") as mock_connection, - ): - mock_conn = MagicMock() - mock_connection.return_value = mock_conn - - import think.chat_cli as chat_cli - - chat_cli.main() - - return mock_request - - -def _run_triage( - onboarding: dict | None = None, -) -> "MagicMock": +def _run_triage(): """Run the triage endpoint with mocked state.""" app = Flask(__name__) with ( - patch("think.awareness.get_onboarding", return_value=onboarding or {}), patch("convey.utils.spawn_agent", return_value="agent-1") as mock_spawn, patch("think.cortex_client.wait_for_agents", return_value=({}, [])), patch( @@ -73,102 +34,6 @@ def _run_triage( assert response.status_code == 200 return mock_spawn - -# --- Triage endpoint routing --- - - -def test_triage_new_user_gets_onboarding(): - """No facets, no awareness state → unified agent.""" - mock = _run_triage() - assert mock.call_args.kwargs["name"] == "unified" - - -def test_triage_established_user_gets_unified(): - """Onboarding complete → unified agent.""" - mock = _run_triage(onboarding={"status": "complete"}) - assert mock.call_args.kwargs["name"] == "unified" - - -def test_triage_path_a_observing_gets_triage(): - """Path A active → unified agent.""" - mock = _run_triage(onboarding={"status": "observing"}) - assert mock.call_args.kwargs["name"] == "unified" - - -def test_triage_path_a_ready_gets_triage(): - """Path A recommendations ready → unified agent.""" - mock = _run_triage(onboarding={"status": "ready"}) - assert mock.call_args.kwargs["name"] == "unified" - - -def test_triage_skipped_gets_unified(): - """Onboarding skipped, no facets → unified (single talent, no two-mode split).""" - mock = _run_triage(onboarding={"status": "skipped"}) - assert mock.call_args.kwargs["name"] == "unified" - - -def test_triage_complete_gets_unified(): - """Onboarding complete, no facets → unified (single talent, no two-mode split).""" - mock = _run_triage(onboarding={"status": "complete"}) - assert mock.call_args.kwargs["name"] == "unified" - - -# --- Chat CLI routing --- - - -def test_chat_cli_routes_to_onboarding_when_unified_and_no_facets(): - """Unified talent stays unified when no facets exist.""" - args = argparse.Namespace( - message=["Hi there"], - talent="unified", - facet=None, - provider=None, - verbose=False, - ) - mock_request = _run_chat_cli_main(args, facets={}) - assert mock_request.call_args.kwargs["name"] == "unified" - - -def test_chat_cli_keeps_explicit_talent_when_no_facets(): - args = argparse.Namespace( - message=["Hi there"], - talent="entities", - facet=None, - provider=None, - verbose=False, - ) - mock_request = _run_chat_cli_main(args, facets={}) - assert mock_request.call_args.kwargs["name"] == "entities" - - -def test_chat_cli_path_a_observing_stays_unified(): - """During Path A observation, chat CLI uses unified talent, not onboarding.""" - args = argparse.Namespace( - message=["What have you noticed?"], - talent="unified", - facet=None, - provider=None, - verbose=False, - ) - mock_request = _run_chat_cli_main( - args, facets={}, onboarding={"status": "observing"} - ) - assert mock_request.call_args.kwargs["name"] == "unified" - - -def test_chat_cli_skipped_stays_unified(): - """After skipping onboarding, chat CLI uses unified talent.""" - args = argparse.Namespace( - message=["Hello"], - talent="unified", - facet=None, - provider=None, - verbose=False, - ) - mock_request = _run_chat_cli_main(args, facets={}, onboarding={"status": "skipped"}) - assert mock_request.call_args.kwargs["name"] == "unified" - - # --- Placeholder resolution --- diff --git a/tests/test_dream_preflight.py b/tests/test_dream_preflight.py deleted file mode 100644 index 50ddfdadc..000000000 --- a/tests/test_dream_preflight.py +++ /dev/null @@ -1,73 +0,0 @@ -# SPDX-License-Identifier: AGPL-3.0-only -# Copyright (c) 2026 sol pbc - -"""Tests for dream preflight skip evaluation.""" - -import pytest - - -@pytest.fixture -def segment_dir(tmp_path, monkeypatch): - journal = tmp_path / "journal" - seg_dir = journal / "20240115" / "default" / "120000_300" - seg_dir.mkdir(parents=True) - (seg_dir / "agents").mkdir() - monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", str(journal)) - return seg_dir - - -class TestShouldSkipPreflight: - def test_daily_mode_never_skips(self): - from think.dream import _should_skip_preflight - - assert _should_skip_preflight( - "observation", - day="20240115", - segment=None, - stream=None, - ) == (False, None) - - def test_firstday_checkin_not_complete(self, monkeypatch): - from think import awareness - from think.dream import _should_skip_preflight - - monkeypatch.setattr( - awareness, "get_onboarding", lambda: {"status": "observing"} - ) - assert _should_skip_preflight( - "firstday_checkin", - day="20240115", - segment="120000_300", - stream="default", - ) == (True, "preflight:not_complete") - - def test_firstday_checkin_already_sent(self, monkeypatch): - from think import awareness - from think.dream import _should_skip_preflight - - monkeypatch.setattr( - awareness, - "get_onboarding", - lambda: { - "status": "complete", - "firstday_checkin_sent": "20260402T10:00:00", - }, - ) - assert _should_skip_preflight( - "firstday_checkin", - day="20240115", - segment="120000_300", - stream="default", - ) == (True, "preflight:already_sent") - - def test_observation_not_observing(self, monkeypatch): - from think import awareness - from think.dream import _should_skip_preflight - - monkeypatch.setattr(awareness, "get_onboarding", lambda: {"status": "complete"}) - assert _should_skip_preflight( - "observation", - day="20240115", - segment="120000_300", - stream="default", - ) == (True, "preflight:not_observing") diff --git a/tests/test_dream_segment.py b/tests/test_dream_segment.py index 9a2c81e34..cd6b19bd8 100644 --- a/tests/test_dream_segment.py +++ b/tests/test_dream_segment.py @@ -47,16 +47,6 @@ def _segment_configs(*names: str) -> dict[str, dict]: "type": "cogitate", "schedule": "segment", }, - "observation": { - "priority": 20, - "type": "cogitate", - "schedule": "segment", - }, - "firstday_checkin": { - "priority": 20, - "type": "cogitate", - "schedule": "segment", - }, "pulse": { "priority": 30, "type": "cogitate", diff --git a/tests/test_observation.py b/tests/test_observation.py deleted file mode 100644 index 43e004dcb..000000000 --- a/tests/test_observation.py +++ /dev/null @@ -1,344 +0,0 @@ -# SPDX-License-Identifier: AGPL-3.0-only -# Copyright (c) 2026 sol pbc - -"""Tests for the observation generator hooks and related features.""" - -import json - -import pytest - - -@pytest.fixture(autouse=True) -def _temp_journal(monkeypatch, tmp_path): - """Isolate all tests to a temporary journal.""" - monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", str(tmp_path)) - - -class TestPreHook: - def test_skips_when_not_observing(self): - from talent.observation import pre_process - - result = pre_process({"day": "20260306", "segment": "120000_300"}) - assert result == {"skip_reason": "not_observing"} - - def test_skips_when_status_is_ready(self): - from talent.observation import pre_process - from think.awareness import update_state - - update_state("onboarding", {"status": "ready"}) - result = pre_process({"day": "20260306", "segment": "120000_300"}) - assert result == {"skip_reason": "not_observing"} - - def test_skips_when_status_is_complete(self): - from talent.observation import pre_process - from think.awareness import update_state - - update_state("onboarding", {"status": "complete"}) - result = pre_process({"day": "20260306", "segment": "120000_300"}) - assert result == {"skip_reason": "not_observing"} - - def test_skips_when_status_is_skipped(self): - from talent.observation import pre_process - from think.awareness import update_state - - update_state("onboarding", {"status": "skipped"}) - result = pre_process({"day": "20260306", "segment": "120000_300"}) - assert result == {"skip_reason": "not_observing"} - - def test_proceeds_when_observing(self): - from talent.observation import pre_process - from think.awareness import start_onboarding - - start_onboarding("a") - result = pre_process({"day": "20260306", "segment": "120000_300"}) - assert result is None # No modifications — proceed with LLM - - -class TestPostHook: - @pytest.fixture(autouse=True) - def _start_observation(self): - from think.awareness import start_onboarding - - start_onboarding("a") - - def test_writes_observation_to_log(self): - from talent.observation import post_process - from think.awareness import read_log - - findings = json.dumps( - { - "has_meeting": False, - "speaker_count": 1, - "apps": ["VS Code"], - "people": [], - "companies": [], - "projects": ["auth-service"], - "tools": ["Git"], - "topics": ["coding"], - "summary": "Solo coding session", - } - ) - - post_process(findings, {"day": "20260306", "segment": "120000_300"}) - - entries = read_log("20260306") - # Filter to observation entries (start_onboarding also writes a log entry) - obs = [e for e in entries if e["kind"] == "observation"] - assert len(obs) == 1 - assert obs[0]["data"]["apps"] == ["VS Code"] - assert obs[0]["message"] == "Solo coding session" - - def test_increments_observation_count(self): - from talent.observation import post_process - from think.awareness import get_onboarding - - findings = json.dumps({"summary": "test", "has_meeting": False}) - - post_process(findings, {"day": "20260306", "segment": "120000_300"}) - assert get_onboarding()["observation_count"] == 1 - - post_process(findings, {"day": "20260306", "segment": "120500_300"}) - assert get_onboarding()["observation_count"] == 2 - - def test_handles_invalid_json(self): - from talent.observation import post_process - - result = post_process("not json", {"day": "20260306", "segment": "120000_300"}) - assert result == "not json" # Returns result unchanged - - def test_handles_non_dict_json(self): - from talent.observation import post_process - - result = post_process("[1,2,3]", {"day": "20260306", "segment": "120000_300"}) - assert result == "[1,2,3]" # Returns result unchanged - - def test_returns_result_unchanged(self): - from talent.observation import post_process - - findings = json.dumps({"summary": "test", "has_meeting": False}) - result = post_process(findings, {"day": "20260306", "segment": "120000_300"}) - assert result == findings - - -class TestNudgeLogic: - def test_first_meeting_triggers_nudge(self): - from talent.observation import _check_nudge - - findings = { - "has_meeting": True, - "speaker_count": 3, - "meeting_topic": "sprint planning", - } - nudge = _check_nudge(findings, 1, 0, {}) - assert nudge is not None - assert "Meeting detected" in nudge["title"] - assert "3 people" in nudge["message"] - - def test_no_meeting_no_first_nudge(self): - from talent.observation import _check_nudge - - findings = {"has_meeting": False} - nudge = _check_nudge(findings, 1, 0, {}) - assert nudge is None - - def test_entity_cluster_triggers_nudge(self): - from talent.observation import _check_nudge - - findings = { - "has_meeting": False, - "people": ["Alice", "Bob", "Charlie"], - } - nudge = _check_nudge(findings, 2, 1, {}) - assert nudge is not None - assert "network" in nudge["title"].lower() - - def test_progress_update_at_5_segments(self): - from talent.observation import _check_nudge - - findings = {"has_meeting": False, "people": []} - nudge = _check_nudge(findings, 5, 2, {}) - assert nudge is not None - assert "Still learning" in nudge["title"] - - def test_no_nudge_when_max_reached(self): - from talent.observation import MAX_NUDGES, _check_nudge - - findings = {"has_meeting": True, "speaker_count": 5} - # nudges_sent == MAX_NUDGES means all nudges used - nudge = _check_nudge(findings, 1, MAX_NUDGES, {}) - # MAX_NUDGES is checked in post_process, not _check_nudge - # But _check_nudge with nudges_sent=4 won't match any trigger - assert nudge is None - - -class TestThreshold: - def test_not_met_with_few_segments(self): - from talent.observation import _threshold_met - - onboarding = {"started": "20260306T08:00:00"} - assert _threshold_met(onboarding, 5) is False - - def test_not_met_with_short_time(self): - # Just started — not enough time elapsed - from datetime import datetime - - from talent.observation import MIN_SEGMENTS, _threshold_met - - now = datetime.now().strftime("%Y%m%dT%H:%M:%S") - onboarding = {"started": now} - assert _threshold_met(onboarding, MIN_SEGMENTS) is False - - def test_met_with_enough_segments_and_time(self): - from talent.observation import MIN_SEGMENTS, _threshold_met - - # Started 5 hours ago - onboarding = {"started": "20260101T03:00:00"} - assert _threshold_met(onboarding, MIN_SEGMENTS) is True - - def test_not_met_with_no_started(self): - from talent.observation import MIN_SEGMENTS, _threshold_met - - onboarding = {} - assert _threshold_met(onboarding, MIN_SEGMENTS) is False - - -class TestElapsedHours: - def test_valid_iso(self): - from talent.observation import _elapsed_hours - - # A date far in the past should give many hours - hours = _elapsed_hours("20200101T00:00:00") - assert hours > 24 - - def test_empty_string(self): - from talent.observation import _elapsed_hours - - assert _elapsed_hours("") == 0.0 - - def test_invalid_format(self): - from talent.observation import _elapsed_hours - - assert _elapsed_hours("not-a-date") == 0.0 - - -class TestAwarenessLogReadCLI: - def test_log_read_empty(self): - from typer.testing import CliRunner - - from apps.awareness.call import app - - result = CliRunner().invoke(app, ["log-read"]) - assert result.exit_code == 0 - assert "No entries found" in result.output - - def test_log_read_with_entries(self): - from typer.testing import CliRunner - - from apps.awareness.call import app - from think.awareness import append_log - - append_log("observation", message="test finding") - append_log("state", key="test.key") - - result = CliRunner().invoke(app, ["log-read"]) - assert result.exit_code == 0 - data = json.loads(result.output) - assert len(data) == 2 - - def test_log_read_filter_by_kind(self): - from typer.testing import CliRunner - - from apps.awareness.call import app - from think.awareness import append_log - - append_log("observation", message="finding 1") - append_log("state", key="transition") - append_log("observation", message="finding 2") - - result = CliRunner().invoke(app, ["log-read", "--kind", "observation"]) - assert result.exit_code == 0 - data = json.loads(result.output) - assert len(data) == 2 - assert all(e["kind"] == "observation" for e in data) - - def test_log_read_with_limit(self): - from typer.testing import CliRunner - - from apps.awareness.call import app - from think.awareness import append_log - - for i in range(5): - append_log("observation", message=f"finding {i}") - - result = CliRunner().invoke(app, ["log-read", "--limit", "2"]) - assert result.exit_code == 0 - data = json.loads(result.output) - assert len(data) == 2 - # Should return the LAST 2 entries - assert data[0]["message"] == "finding 3" - assert data[1]["message"] == "finding 4" - - -class TestChatBarPlaceholder: - def _get_placeholder(self): - """Extract chat bar placeholder from the context processor.""" - - from flask import Flask - - app = Flask(__name__) - app.config["TESTING"] = True - - from apps import AppRegistry - from convey.apps import register_app_context - - registry = AppRegistry() - register_app_context(app, registry) - - with app.test_request_context("/"): - # Get context from context processors - ctx = {} - for func in app.template_context_processors[None]: - ctx.update(func()) - return ctx.get("chat_bar_placeholder", "") - - def test_default_placeholder(self): - assert "Bring in past conversations" in self._get_placeholder() - - def test_observing_placeholder(self): - from think.awareness import start_onboarding - - start_onboarding("a") - placeholder = self._get_placeholder() - assert "Bring in past conversations" in placeholder - - def test_ready_placeholder(self): - from think.awareness import start_onboarding, update_state - - start_onboarding("a") - update_state("onboarding", {"status": "ready"}) - placeholder = self._get_placeholder() - assert "Bring in past conversations" in placeholder - - def test_interviewing_placeholder(self): - from think.awareness import start_onboarding - - start_onboarding("b") - placeholder = self._get_placeholder() - assert "Bring in past conversations" in placeholder - - def test_complete_placeholder(self): - from think.awareness import start_onboarding, update_state - - start_onboarding("a") - update_state("onboarding", {"status": "complete"}) - update_state("imports", {"has_imported": True}) - placeholder = self._get_placeholder() - assert "Capture is running" in placeholder - - def test_skipped_placeholder(self): - from think.awareness import skip_onboarding, update_state - - skip_onboarding() - update_state("imports", {"has_imported": True}) - placeholder = self._get_placeholder() - assert "Capture is running" in placeholder diff --git a/tests/test_talent_cli.py b/tests/test_talent_cli.py index 4148ae33f..8f0777000 100644 --- a/tests/test_talent_cli.py +++ b/tests/test_talent_cli.py @@ -36,9 +36,8 @@ def test_collect_configs_excludes_disabled_by_default(): with_disabled = _collect_configs(include_disabled=True) # include_disabled should return at least as many configs assert len(with_disabled) >= len(without) - for name in ("onboarding", "observation", "observation_review", "firstday_checkin"): - assert name not in without - assert name in with_disabled + assert "flow" in without + assert "flow" in with_disabled def test_collect_configs_filter_schedule(): diff --git a/think/awareness.py b/think/awareness.py index 25e0e6998..68c0ca8ed 100644 --- a/think/awareness.py +++ b/think/awareness.py @@ -3,13 +3,13 @@ """Awareness system — solstone's self-awareness about the user. -Tracks the system's evolving understanding: onboarding state, observations, -nudges, and interactions. Two-layer storage: +Tracks the system's evolving understanding: capture state, identity +persistence, imports, and awareness signals. Two-layer storage: - ``awareness/current.json`` — materialized current state for fast reads - ``awareness/YYYYMMDD.jsonl`` — append-only daily log of everything noticed -Designed to extend beyond onboarding to cogitate (proactive agents), +Designed to extend to cogitate (proactive agents), learned preferences, and cross-session agent memory. """ @@ -519,67 +519,6 @@ def read_log(day: str | None = None) -> list[dict[str, Any]]: return entries -# --- Onboarding convenience functions --- - - -def get_onboarding() -> dict[str, Any]: - """Return the current onboarding state, or empty dict if none.""" - return get_current().get("onboarding", {}) - - -def start_onboarding(path: str) -> dict[str, Any]: - """Record onboarding path selection. - - Parameters - ---------- - path : str - "a" for passive observation, "b" for conversational interview - - Returns - ------- - dict - The updated onboarding state - """ - status = "observing" if path == "a" else "interviewing" - state = update_state( - "onboarding", - { - "path": path, - "status": status, - "started": _now_iso(), - "observation_count": 0, - "nudges_sent": 0, - }, - ) - append_log("state", key="onboarding.started", data={"path": path, "status": status}) - return state - - -def skip_onboarding() -> dict[str, Any]: - """Record onboarding skip.""" - state = update_state( - "onboarding", - { - "status": "skipped", - "started": _now_iso(), - }, - ) - append_log("state", key="onboarding.skipped") - return state - - -def complete_onboarding() -> dict[str, Any]: - """Record onboarding completion.""" - state = update_state( - "onboarding", - { - "status": "complete", - }, - ) - append_log("state", key="onboarding.complete") - return state - - # --- Import tracking convenience functions --- @@ -619,7 +558,7 @@ def compute_thickness() -> dict[str, Any]: Returns a dict with five signals and a composite ``ready`` boolean: - ``entity_depth``: count of entities with observation_depth >= 2 - - ``conversation_count``: non-onboarding conversation exchanges + - ``conversation_count``: conversation exchanges excluding legacy onboarding - ``recall_success``: exchanges where an entity name appears in agent_response - ``facet_count``: number of enabled (non-muted) facets - ``journal_days``: number of day directories with at least one segment diff --git a/think/dream.py b/think/dream.py index 1c8300c3b..55b0d06e4 100644 --- a/think/dream.py +++ b/think/dream.py @@ -366,24 +366,6 @@ def _should_skip_preflight( if not segment: return (False, None) - if prompt_name == "firstday_checkin": - from think.awareness import get_onboarding - - onboarding = get_onboarding() - if onboarding.get("status") != "complete": - return (True, "preflight:not_complete") - if onboarding.get("firstday_checkin_sent"): - return (True, "preflight:already_sent") - return (False, None) - - if prompt_name == "observation": - from think.awareness import get_onboarding - - onboarding = get_onboarding() - if onboarding.get("status") != "observing": - return (True, "preflight:not_observing") - return (False, None) - return (False, None) @@ -596,18 +578,6 @@ def run_segment_sense( if speaker_config: agents_to_run.append(("speaker_attribution", speaker_config)) - for onboarding_name in ("observation", "firstday_checkin"): - onboarding_config = _cfg(onboarding_name) - if onboarding_config: - skip, _skip_reason = _should_skip_preflight( - onboarding_name, - day=day, - segment=segment, - stream=stream, - ) - if not skip: - agents_to_run.append((onboarding_name, onboarding_config)) - total_expected = 1 + len(agents_to_run) if recommend.get("pulse_update") and pulse_config: total_expected += 1 @@ -1914,8 +1884,6 @@ def dry_run( "speaker_attribution", "if recommend.speaker_attribution + audio embeddings", ), - ("observation", "if onboarding=observing"), - ("firstday_checkin", "if onboarding=complete"), ("pulse", "if recommend.pulse_update"), ]: cfg = prompts.get(name) @@ -2544,23 +2512,21 @@ def main() -> None: except Exception: pass - # Set first_daily_ready awareness flag after first post-onboarding daily + # Set first_daily_ready awareness flag after first daily analysis try: - from think.awareness import get_current, get_onboarding, update_state - - ob = get_onboarding() - if ob.get("status") == "complete": - cur = get_current() - if not cur.get("journal", {}).get("first_daily_ready"): - update_state( - "journal", - { - "first_daily_ready": True, - "first_daily_ready_at": datetime.now().strftime( - "%Y%m%dT%H:%M:%S" - ), - }, - ) + from think.awareness import get_current, update_state + + cur = get_current() + if not cur.get("journal", {}).get("first_daily_ready"): + update_state( + "journal", + { + "first_daily_ready": True, + "first_daily_ready_at": datetime.now().strftime( + "%Y%m%dT%H:%M:%S" + ), + }, + ) except Exception: pass -- 2.51.2