+16

apps/activities/call.py

reviewed

··· 131 131 *, 132 132 activity: str | None, 133 133 entity: str | None, 134 134 + source: str | None, 134 135 include_hidden: bool, 135 136 ) -> list[dict[str, Any]]: 136 137 matches: list[dict[str, Any]] = [] ··· 141 142 facet_name, day, include_hidden=include_hidden 142 143 ): 143 144 if activity and record.get("activity") != activity: 145 145 + continue 146 146 + if source and record.get("source") != source: 144 147 continue 145 148 if entity_query: 146 149 active_entities = record.get("active_entities", []) ··· 200 203 "--entity", 201 204 help="Filter by active entity.", 202 205 ), 206 206 + source: str | None = typer.Option( 207 207 + None, 208 208 + "--source", 209 209 + help="Filter by record source: anticipated, user, or cogitate.", 210 210 + ), 203 211 include_all: bool = typer.Option( 204 212 False, 205 213 "--all", ··· 221 229 else: 222 230 resolved_days = [resolve_sol_day(None)] 223 231 232 232 + if source and source not in {"anticipated", "cogitate", "user"}: 233 233 + typer.echo( 234 234 + "Error: --source must be 'anticipated', 'cogitate', or 'user'.", 235 235 + err=True, 236 236 + ) 237 237 + raise typer.Exit(1) 238 238 + 224 239 facets = _resolve_list_facets(facet) 225 240 records = _list_records_for_days( 226 241 facets, 227 242 resolved_days, 228 243 activity=activity, 229 244 entity=entity, 245 245 + source=source, 230 246 include_hidden=include_all, 231 247 ) 232 248

+53

apps/activities/tests/test_call.py

reviewed

··· 109 109 assert [item["id"] for item in payload] == ["coding_090000_300"] 110 110 111 111 112 112 + def test_list_filters_by_source(activities_env): 113 113 + activities_env( 114 114 + [ 115 115 + { 116 116 + "id": "anticipated_call_103000_0421", 117 117 + "activity": "call", 118 118 + "title": "Mari intro", 119 119 + "description": "Planned", 120 120 + "target_date": "2026-04-21", 121 121 + "source": "anticipated", 122 122 + "created_at": 1, 123 123 + }, 124 124 + { 125 125 + "id": "coding_090000_300", 126 126 + "activity": "coding", 127 127 + "title": "Focused coding", 128 128 + "description": "User created", 129 129 + "source": "user", 130 130 + "created_at": 2, 131 131 + }, 132 132 + { 133 133 + "id": "meeting_100000_300", 134 134 + "activity": "meeting", 135 135 + "title": "Synthesized meeting", 136 136 + "description": "Cogitate created", 137 137 + "source": "cogitate", 138 138 + "created_at": 3, 139 139 + }, 140 140 + ] 141 141 + ) 142 142 + 143 143 + result = runner.invoke( 144 144 + call_app, 145 145 + ["activities", "list", "--facet", "work", "--source", "anticipated", "--json"], 146 146 + ) 147 147 + 148 148 + assert result.exit_code == 0 149 149 + payload = json.loads(result.output) 150 150 + assert [item["id"] for item in payload] == ["anticipated_call_103000_0421"] 151 151 + 152 152 + 153 153 + def test_list_rejects_unknown_source(activities_env): 154 154 + activities_env([]) 155 155 + 156 156 + result = runner.invoke( 157 157 + call_app, 158 158 + ["activities", "list", "--facet", "work", "--source", "calendar"], 159 159 + ) 160 160 + 161 161 + assert result.exit_code == 1 162 162 + assert "--source must be 'anticipated', 'cogitate', or 'user'" in result.output 163 163 + 164 164 + 112 165 def test_get_returns_hidden_record_with_json_output(activities_env): 113 166 activities_env( 114 167 [

+27

apps/home/routes.py

reviewed

··· 303 303 304 304 def _collect_events(today: str) -> list[dict[str, Any]]: 305 305 """Collect calendar events across all facets.""" 306 306 + from think.activities import load_activity_records 306 307 from think.indexer.journal import get_events 307 308 308 309 try: ··· 312 313 event["start"] = "" 313 314 if event.get("end") is None: 314 315 event["end"] = "" 316 316 + 317 317 + for facet_name in get_facets(): 318 318 + for record in load_activity_records(facet_name, today): 319 319 + if record.get("source") != "anticipated": 320 320 + continue 321 321 + 322 322 + participants = [] 323 323 + for entry in record.get("participation", []): 324 324 + if not isinstance(entry, dict) or entry.get("role") != "attendee": 325 325 + continue 326 326 + name = str(entry.get("name") or "").strip() 327 327 + if name: 328 328 + participants.append(name) 329 329 + 330 330 + events.append( 331 331 + { 332 332 + "title": record.get("title", ""), 333 333 + "start": record.get("start") or "", 334 334 + "end": record.get("end") or "", 335 335 + "facet": facet_name, 336 336 + "occurred": False, 337 337 + "participants": participants, 338 338 + } 339 339 + ) 315 340 return events 316 341 except Exception: 317 342 logger.warning("home: failed to collect events", exc_info=True) ··· 335 360 for facet_name in facets: 336 361 records = load_activity_records(facet_name, today) 337 362 for record in records: 363 363 + if record.get("source") == "anticipated": 364 364 + continue 338 365 created_at = record.get("created_at", 0) 339 366 if created_at < cutoff_ts: 340 367 continue

+6 -7

apps/settings/routes.py

reviewed

··· 432 432 if "schedule" in info: 433 433 context_defaults[context_key]["schedule"] = info["schedule"] 434 434 context_defaults[context_key]["disabled"] = info.get("disabled", False) 435 435 - # Include extract for generators with occurrence/anticipation hooks 435 435 + # Include extract for generators with occurrence hooks 436 436 hook = info.get("hook") 437 437 has_extraction = ( 438 438 - isinstance(hook, dict) 439 439 - and hook.get("post") in ("occurrence", "anticipation") 440 440 - ) or hook in ("occurrence", "anticipation") 438 438 + isinstance(hook, dict) and hook.get("post") in ("occurrence",) 439 439 + ) or hook in ("occurrence",) 441 440 if has_extraction: 442 441 context_defaults[context_key]["extract"] = info.get("extract", True) 443 442 ··· 929 928 Transforms talent config metadata into the format expected by the 930 929 Settings UI Insights section. 931 930 """ 932 932 - # Determine if extraction is supported (occurrence/anticipation hooks) 931 931 + # Determine if extraction is supported (occurrence hooks) 933 932 hook = info.get("hook") 934 933 has_extraction = ( 935 935 - isinstance(hook, dict) and hook.get("post") in ("occurrence", "anticipation") 936 936 - ) or hook in ("occurrence", "anticipation") 934 934 + isinstance(hook, dict) and hook.get("post") in ("occurrence",) 935 935 + ) or hook in ("occurrence",) 937 936 938 937 return { 939 938 "key": key,

+2 -2

docs/APPS.md

reviewed

··· 294 294 **Event extraction via hooks:** To extract structured events from generator output, use the `hook` field: 295 295 296 296 - `"hook": {"post": "occurrence"}` - Extracts past events to `facets/{facet}/events/{day}.jsonl` 297 297 - - `"hook": {"post": "anticipation"}` - Extracts future scheduled events 297 297 + - `"hook": {"post": "schedule"}` - Writes future scheduled items as anticipated activity records 298 298 299 299 The `occurrences` field (optional string) provides agent-specific extraction guidance when using the occurrence hook. Example: 300 300 ··· 356 356 357 357 **Reference implementations:** 358 358 - System generator templates: `talent/*.md` (files with `schedule` field but no `tools` field) 359 359 - - Extraction hooks: `talent/occurrence.py`, `talent/anticipation.py` 359 359 + - Event/schedule hooks: `talent/occurrence.py`, `talent/schedule.py` 360 360 - Discovery logic: `think/talent.py` - `get_talent_configs(has_tools=False)`, `get_output_name()` 361 361 - Hook loading: `think/talent.py` - `load_pre_hook()`, `load_post_hook()` 362 362

+1 -1

docs/CORTEX.md

reviewed

··· 336 336 337 337 #### Daily Multi-Facet Agents 338 338 339 339 - **Active Facet Detection**: By default, daily multi-facet agents only run for facets that had activity the previous day. Activity is determined by the presence of occurrence events (not anticipations) in `facets/{facet}/events/{day}.jsonl`. This prevents unnecessary agent runs for inactive facets. 339 339 + **Active Facet Detection**: By default, daily multi-facet agents only run for facets that had activity the previous day. Activity is determined by the presence of occurrence events in `facets/{facet}/events/{day}.jsonl`. This prevents unnecessary agent runs for inactive facets. 340 340 341 341 To force an agent to run for all facets regardless of activity, set `"always": true`: 342 342

+1 -1

docs/THINK.md

reviewed

··· 183 183 - `mtime` – modification time of the `.md` file 184 184 - Additional keys from JSON frontmatter such as `title`, `description`, `hook`, or `load` 185 185 186 186 - The `hook` field enables event extraction by invoking named hooks like `"occurrence"` or `"anticipation"`. 186 186 + The `hook` field enables output processing by invoking named hooks like `"occurrence"` or `"schedule"`. 187 187 The `load` key controls transcript/percept/agent source filtering for generators. 188 188 See [APPS.md](APPS.md#prompt-context-configuration) for the full schema. 189 189

+1 -1

routines/templates/decision-review.md

reviewed

··· 15 15 1. Use `sol call journal search "" -a decisions --day-from START --day-to END -n 20` for the past 30 days of decision agent output. 16 16 2. Use `sol call journal search "" -a pulse --day-from START --day-to END -n 15` for narrative context around major decisions. 17 17 3. Use `sol call entities intelligence PERSON` for people involved in the most consequential decisions. 18 18 - 4. Use `sol call calendar list YYYYMMDD` for days with major decisions to see what else was happening. 18 18 + 4. Use `sol call activities list --source anticipated --day YYYYMMDD` for days with major decisions to see what else was happening. 19 19 5. Use `sol call identity partner` for the owner's known decision style. 20 20 21 21 ## Synthesize

+1 -1

routines/templates/energy-audit.md

reviewed

··· 10 10 11 11 ## Gather 12 12 13 13 - 1. Use `sol call calendar list YYYYMMDD` for each of the past 7 days to map meeting load. 13 13 + 1. Use `sol call activities list --source anticipated --day YYYYMMDD` for each of the past 7 days to map scheduled load. 14 14 2. Use `sol call journal search "" --day-from START --day-to END -n 30` to survey activity patterns. 15 15 3. Use `sol call todos list` to compare intended work against actual activity. 16 16 4. Use `sol call identity pulse` for the current state narrative.

+1 -1

routines/templates/meeting-prep.md

reviewed

··· 13 13 ## Gather 14 14 15 15 1. Read the upcoming event details in the prompt carefully. 16 16 - 2. If you need broader context, call `sol call calendar list $day_YYYYMMDD` to see the surrounding schedule. 16 16 + 2. If you need broader context, call `sol call activities list --source anticipated --day $day_YYYYMMDD` to see the surrounding schedule. 17 17 3. For each listed participant, call `sol call entities intelligence PERSON --brief`. 18 18 4. Use `sol call journal search QUERY -n 10` to look for recent mentions of the meeting topic, project, or participants. 19 19 5. If a configured facet seems especially relevant, use `sol call journal news FACET --day $day_YYYYMMDD`.

+1 -1

routines/templates/monthly-patterns.md

reviewed

··· 16 16 2. Use `sol call journal search "" --day-from START --day-to END -n 40` to survey the month across the configured facets. 17 17 3. Use `sol call journal news FACET --day YYYYMMDD` for representative weekly or recent snapshots when they help summarize a facet. 18 18 4. Use `sol call entities intelligence PERSON` for people who appear central to the month. 19 19 - 5. Use `sol call calendar list YYYYMMDD` on representative days if calendar load seems important. 19 19 + 5. Use `sol call activities list --source anticipated --day YYYYMMDD` on representative days if scheduled load seems important. 20 20 6. Use `sol call identity pulse` to compare month-long patterns against the current state narrative. 21 21 22 22 ## Synthesize

+1 -1

routines/templates/morning-briefing.md

reviewed

··· 13 13 ## Gather 14 14 15 15 1. Call `sol call journal facets` to see the active facets if you need broader context. 16 16 - 2. Call `sol call calendar list $day_YYYYMMDD` to review today's events and participants. 16 16 + 2. Call `sol call activities list --source anticipated --day $day_YYYYMMDD` to review today's scheduled items and participants. 17 17 3. Call `sol call todos list` to see pending action items across facets. 18 18 4. Call `sol call identity pulse` to capture current narrative, priorities, and needs-you items. 19 19 5. Call `sol call journal search "" -a followups -n 10` to find recent follow-up items.

+1 -1

routines/templates/weekly-review.md

reviewed

··· 15 15 1. Use `sol call journal facets` to identify the facets in scope. 16 16 2. Use `sol call journal search "" --day-from $day_minus_7_YYYYMMDD --day-to $day_YYYYMMDD -n 25` to find notable entries and themes. 17 17 3. Use `sol call todos list` to review outstanding work and infer what likely got completed or deferred. 18 18 - 4. Use `sol call calendar list YYYYMMDD` across the last 7 days to understand meeting load and major time commitments. 18 18 + 4. Use `sol call activities list --source anticipated --day YYYYMMDD` across the last 7 days to understand scheduled load and major time commitments. 19 19 5. Use `sol call identity pulse` for the current state narrative. 20 20 6. Use `sol call journal news FACET --day YYYYMMDD` for any facet that needs a richer summary. 21 21

+2 -2

skills/solstone/SKILL.md

reviewed

··· 69 69 sol call todos upcoming 70 70 71 71 # Calendar events for today 72 72 - sol call calendar list 72 72 + sol call activities list --source anticipated 73 73 74 74 # Latest facet news 75 75 sol call journal news "<facet>" ··· 144 144 ```bash 145 145 sol call journal events 146 146 sol call todos upcoming 147 147 - sol call calendar list 147 147 + sol call activities list --source anticipated 148 148 sol call entities strength --since $(date +%Y%m%d) 149 149 ``` 150 150

-97

talent/anticipation.md

reviewed

··· 1 1 - { 2 2 - 3 3 - "title": "Anticipation Extraction", 4 4 - "description": "Extracts structured anticipation events (future scheduled items) from insight summaries.", 5 5 - "color": "#4527a0" 6 6 - 7 7 - } 8 8 - 9 9 - # Anticipation JSON Conversion 10 10 - 11 11 - ## Objective 12 12 - 13 13 - Extract future scheduled events from a Markdown summary and convert them into structured JSON anticipations. These are events that have not yet occurred but are planned or scheduled for future dates. 14 14 - 15 15 - ## Instructions 16 16 - 1. **Extract every distinct future event** mentioned in the summary - meetings, deadlines, appointments, etc. 17 17 - 2. **Be comprehensive** - capture calendar events, scheduled meetings, deadlines, personal appointments, recurring events, travel, etc. 18 18 - 3. **Preserve date and timing information** - always extract the scheduled date, and time if known 19 19 - 4. **Handle uncertainty gracefully** - use `null` for start/end times when not specified 20 20 - 5. **Assign facets** - for every anticipation, choose the best matching facet from the Available Facets context. This field is required. 21 21 - 6. **Return only valid JSON** - no commentary, explanations, or wrapper objects 22 22 - 7. **Handle empty sources** - if the source indicates no future events, return an empty array: `[]` 23 23 - 24 24 - ## Anticipation Fields 25 25 - - **type** – the kind of event such as `meeting`, `deadline`, `appointment`, `event`, `travel`, `reminder`, etc. 26 26 - - **date** – ISO date (YYYY-MM-DD) when the event is scheduled to occur. Required. 27 27 - - **start** and **end** – HH:MM:SS timestamps for the event time, or `null` if time is unknown/TBD 28 28 - - **title** – short descriptive title for display 29 29 - - **summary** – concise one-sentence description of what is planned 30 30 - - **work** – boolean classification: `true` for work-related, `false` for personal 31 31 - - **participants** – optional list of people or entities involved (empty array if none) 32 32 - - **facet** – required facet identifier; use the facet name/ID from Available Facets context 33 33 - - **details** – free-form string capturing location, agenda, preparation notes, or other context 34 34 - 35 35 - ## Handling Time Uncertainty 36 36 - - If exact time is known (e.g., "1:00 PM"): use `"start": "13:00:00"` 37 37 - - If time is vague (e.g., "Morning", "Afternoon"): use `null` and mention in details 38 38 - - If time is TBD or not specified: use `null` 39 39 - - If it's an all-day event: use `null` for both start and end 40 40 - 41 41 - ## Handling Recurring Events 42 42 - For recurring events (e.g., "every Wednesday"), extract the next upcoming instance with its specific date. Mention the recurrence pattern in details. 43 43 - 44 44 - ## Output Format 45 45 - Return a JSON array of anticipations only. Each anticipation must include all required fields. 46 46 - 47 47 - ## Example 48 48 - [ 49 49 - { 50 50 - "type": "meeting", 51 51 - "date": "2025-11-05", 52 52 - "start": "13:00:00", 53 53 - "end": "14:30:00", 54 54 - "title": "Meeting with Center for the Blind", 55 55 - "summary": "Introductory meeting to discuss potential collaboration on AI-powered tools.", 56 56 - "work": true, 57 57 - "participants": ["Jack Anderson", "Center for the Blind Representatives"], 58 58 - "facet": "blind_center", 59 59 - "details": "Virtual meeting. Topics include grant writing and building an AI brain from their documents." 60 60 - }, 61 61 - { 62 62 - "type": "deadline", 63 63 - "date": "2025-11-10", 64 64 - "start": null, 65 65 - "end": null, 66 66 - "title": "Airport System Deployment Target", 67 67 - "summary": "Target date for deploying the cleaned-up UI and new restart scripts.", 68 68 - "work": true, 69 69 - "participants": ["Mitch Baumgartner"], 70 70 - "facet": "aviation_networks", 71 71 - "details": "Software deployment. No specific time set." 72 72 - }, 73 73 - { 74 74 - "type": "event", 75 75 - "date": "2025-10-27", 76 76 - "start": null, 77 77 - "end": null, 78 78 - "title": "FMDS Partner Workshop", 79 79 - "summary": "Multi-day in-person workshop with partners running through October 30.", 80 80 - "work": true, 81 81 - "participants": ["L3Harris", "GDIT", "Frequentis", "uAvionix"], 82 82 - "facet": "fmds", 83 83 - "details": "In-person, security clearance required. Day 1: Win strategy and demo dry run. Day 2: Solution definition. Day 3: Prototype planning. Runs Oct 27-30." 84 84 - }, 85 85 - { 86 86 - "type": "appointment", 87 87 - "date": "2025-11-15", 88 88 - "start": null, 89 89 - "end": null, 90 90 - "title": "Gymnastics Meet", 91 91 - "summary": "First gymnastics meet of the season.", 92 92 - "work": false, 93 93 - "participants": ["Blade"], 94 94 - "facet": "family", 95 95 - "details": "Location: Marshaltown Community Center." 96 96 - } 97 97 - ]

-101

talent/anticipation.py

reviewed

··· 1 1 - # SPDX-License-Identifier: AGPL-3.0-only 2 2 - # Copyright (c) 2026 sol pbc 3 3 - 4 4 - """Hook for extracting anticipation events from generator output results. 5 5 - 6 6 - This hook is invoked via "hook": {"post": "anticipation"} in generator frontmatter. 7 7 - It extracts structured JSON events for future scheduled items and writes 8 8 - them to facet-based JSONL files. 9 9 - """ 10 10 - 11 11 - import json 12 12 - import logging 13 13 - from pathlib import Path 14 14 - 15 15 - from think.facets import facet_summaries 16 16 - from think.hooks import ( 17 17 - compute_output_source, 18 18 - log_extraction_failure, 19 19 - should_skip_extraction, 20 20 - write_events_jsonl, 21 21 - ) 22 22 - from think.models import generate 23 23 - from think.prompts import load_prompt 24 24 - from think.talent import get_output_name 25 25 - 26 26 - 27 27 - def post_process(result: str, context: dict) -> str | None: 28 28 - """Extract anticipation events from generator output result. 29 29 - 30 30 - This hook extracts structured JSON events for future scheduled items 31 31 - from markdown output summaries and writes them to facet-based JSONL files. 32 32 - 33 33 - Args: 34 34 - result: The generated output markdown content. 35 35 - context: Config dict with keys including day, segment, name, 36 36 - output_path, meta, transcript, span, span_mode. 37 37 - 38 38 - Returns: 39 39 - None - this hook does not modify the output result. 40 40 - """ 41 41 - # Check skip conditions 42 42 - skip_reason = should_skip_extraction(result, context) 43 43 - if skip_reason: 44 44 - logging.info("Skipping anticipation extraction: %s", skip_reason) 45 45 - return None 46 46 - 47 47 - # Load extraction prompt 48 48 - prompt_content = load_prompt("anticipation", base_dir=Path(__file__).parent) 49 49 - 50 50 - # Build context with facets (anticipations don't have agent-specific instructions) 51 51 - facets_context = facet_summaries(detailed=True) 52 52 - 53 53 - # Extract events 54 54 - name = context.get("name", "unknown") 55 55 - contents = [facets_context, result] 56 56 - 57 57 - try: 58 58 - response_text = generate( 59 59 - contents=contents, 60 60 - context=f"talent.system.{name}", 61 61 - temperature=0.3, 62 62 - max_output_tokens=24576, 63 63 - thinking_budget=0, 64 64 - system_instruction=prompt_content.text, 65 65 - json_output=True, 66 66 - ) 67 67 - except Exception as e: 68 68 - log_extraction_failure(e, name) 69 69 - return None 70 70 - 71 71 - try: 72 72 - events = json.loads(response_text) 73 73 - except json.JSONDecodeError as e: 74 74 - logging.error("Invalid JSON from anticipation extraction: %s", e) 75 75 - return None 76 76 - 77 77 - if not isinstance(events, list): 78 78 - logging.error("Extraction did not return array") 79 79 - return None 80 80 - 81 81 - # Write to facet JSONL files (occurred=False for anticipations) 82 82 - source_output = compute_output_source(context) 83 83 - output_name = get_output_name(name) 84 84 - day = context.get("day", "") 85 85 - 86 86 - written_paths = write_events_jsonl( 87 87 - events=events, 88 88 - agent=output_name, 89 89 - occurred=False, 90 90 - source_output=source_output, 91 91 - capture_day=day, 92 92 - ) 93 93 - 94 94 - if written_paths: 95 95 - print(f"Events written to {len(written_paths)} JSONL file(s):") 96 96 - for p in written_paths: 97 97 - print(f" {p}") 98 98 - else: 99 99 - print("No events with valid facets to write") 100 100 - 101 101 - return None # Don't modify insight result

+1 -1

talent/awareness_tender.md

reviewed

··· 21 21 22 22 1. `sol call awareness status` — processing, import, and journal state 23 23 2. `sol call identity self` — identity summary (skim for key changes) 24 24 - 3. `sol call calendar list` — today's events 24 24 + 3. `sol call activities list --source anticipated` — today's scheduled activity records 25 25 4. `sol call routines list` — active routines and recent outputs 26 26 5. `sol call entities search --since --limit 5` — recent entity activity 27 27 ## Write awareness.md

+5 -10

talent/journal/references/captures.md

reviewed

··· 229 229 230 230 ### Event extracts 231 231 232 232 - Generator output processing extracts time-based events from the day's transcripts—meetings, messages, follow-ups, file activity and more. Events are stored per-facet in JSONL files at `facets/{facet}/events/{day}.jsonl`. 233 233 - 234 234 - There are two types of events: 235 235 - - **Occurrences** – events that happened on the capture day (`occurred: true`) 236 236 - - **Anticipations** – future scheduled events extracted from calendar views (`occurred: false`) 232 232 + Generator output processing extracts time-based events from the day's transcripts—meetings, messages, follow-ups, file activity and more. Occurrence events are stored per-facet in JSONL files at `facets/{facet}/events/{day}.jsonl`. Future scheduled items from the schedule talent are stored as anticipated activity records under `facets/{facet}/activities/{target_day}.jsonl` with `source: "anticipated"`. 237 233 238 234 ```jsonl 239 235 {"type": "meeting", "start": "09:00:00", "end": "09:30:00", "title": "Team stand-up", "summary": "Status update with the engineering team", "work": true, "participants": ["Jeremie Miller", "Alice", "Bob"], "facet": "work", "agent": "meetings", "occurred": true, "source": "20250101/talents/meetings.md", "details": "Sprint planning discussion"} 240 240 - {"type": "deadline", "date": "2025-01-15", "start": null, "end": null, "title": "Project milestone", "summary": "Q1 deliverable due", "work": true, "participants": [], "facet": "work", "agent": "schedule", "occurred": false, "source": "20250101/talents/schedule.md", "details": "Final review before release"} 236 236 + {"id": "anticipated_deadline_000000_0115", "activity": "deadline", "target_date": "2025-01-15", "start": null, "end": null, "title": "Project milestone", "description": "Q1 deliverable due.", "details": "Final review before release", "facet": "work", "source": "anticipated", "active_entities": [], "participation": [], "participation_confidence": 0.5, "cancelled": false} 241 237 ``` 242 238 243 239 **Common fields:** 244 240 - **type** – event kind: `meeting`, `message`, `file`, `followup`, `documentation`, `research`, `media`, `deadline`, `appointment`, etc. 245 245 - - **start** and **end** – HH:MM:SS timestamps (or `null` for anticipations without specific times) 246 246 - - **date** – ISO date YYYY-MM-DD (anticipations only, indicates scheduled date) 241 241 + - **start** and **end** – HH:MM:SS timestamps (or `null` when a time is not known) 247 242 - **title** and **summary** – short text for display and search 248 243 - **facet** – facet name the event belongs to (required) 249 249 - - **agent** – source generator type (e.g., "meetings", "schedule", "flow") 250 250 - - **occurred** – `true` for occurrences, `false` for anticipations 244 244 + - **agent** – source generator type for occurrence events (e.g., "meetings", "flow") 245 245 + - **occurred** – `true` for occurrence event rows in `facets/*/events/*.jsonl` 251 246 - **source** – path to the output file that generated this event 252 247 - **work** – boolean, work vs. personal classification 253 248 - **participants** – optional list of people or entities involved

+1 -1

talent/journal/references/config.md

reviewed

··· 298 298 - `tier` (integer) – Tier number (optional). 299 299 - `model` (string) – Explicit model name (optional, overrides tier). 300 300 - `disabled` (boolean) – Disable this talent config (optional, talent contexts only). 301 301 - - `extract` (boolean) – Enable/disable event extraction for generators with occurrence/anticipation hooks (optional). 301 301 + - `extract` (boolean) – Enable/disable event extraction for generators with occurrence hooks (optional). 302 302 303 303 **models** – Per-provider tier overrides. Maps provider name to tier-model mappings: 304 304 ```json

+7 -7

talent/morning_briefing.md

reviewed

··· 21 21 22 22 1. `sol call journal facets` — list active facets 23 23 2. For each facet: `sol call journal news FACET --day $day_YYYYMMDD` — facet newsletter 24 24 - 3. `sol call calendar list $day_YYYYMMDD` — today's events with participants 24 24 + 3. `sol call activities list --source anticipated --day $day_YYYYMMDD` — today's scheduled items with participants 25 25 4. `sol call todos list` — pending action items across all facets 26 26 5. `sol call identity pulse` — current pulse narrative and needs-you items 27 27 6. `sol call identity partner` — owner behavioral profile (informs tone and emphasis) 28 28 7. `sol call journal search "" -d $day_YYYYMMDD -a followups -n 10` — follow-up items from today 29 29 - 8. `sol call journal search "" --day-from $day_YYYYMMDD -a anticipation -n 5` — forward-looking anticipations 29 29 + 8. `sol call activities list --source anticipated --from $day_YYYYMMDD --to <+7>` — forward-looking scheduled items 30 30 9. `sol call journal search "" -d $day_YYYYMMDD -a decisions -n 10` — yesterday's consequential decisions 31 31 - 10. For each of the next 7 days after today: `sol call calendar list YYYYMMDD` — upcoming events for forward look 31 31 + 10. For each of the next 7 days after today: `sol call activities list --source anticipated --day YYYYMMDD` — upcoming scheduled items for forward look 32 32 33 33 For each person appearing in today's calendar events, also run: 34 34 11. `sol call entities intelligence PERSON --brief` — relationship context, recent interactions, observations (brief mode: last 20 signals + top 20 network, ~95% smaller payload) ··· 97 97 Attribute commitments and follow-ups to the originating segment: `(committed [date](sol://...))`, `(flagged [date](sol://...))`. For relationship items: `(last interaction [date])`. For inferred items: `(inferred from [source](sol://...))`. 98 98 Grade action items by evidence strength. **High** (explicit commitment with date, or overdue todo): state assertively — "Follow up on Series A term sheet — committed March 20, now overdue." **Medium** (flagged by followups agent with moderate confidence, or clear single-source item): present with attribution — "Review CI pipeline logs (flagged yesterday)." **Low** (inferred obligation from ambiguous mention, or low-confidence followup): hedge — "Possible commitment to send deck to investors" or "May need to follow up on the API discussion." When upstream followup output includes a `Confidence:` score, use it: 0.85+ high, 0.50–0.84 medium, below 0.50 low. Never hedge explicit commitments with clear dates; never present inferred obligations as definite action items. 99 99 100 100 - **Forward Look** — What's coming. Draw from anticipation agent output and upcoming calendar events (next 7 days). Note preparation needed for upcoming meetings or deadlines. 101 101 - Attribute anticipation items: `(from [anticipation](sol://...))`. Data source: anticipation search result `id` path. 102 102 - Grade forward items by evidence strength. **High** (confirmed calendar event or explicit deadline): state assertively — "Board meeting Thursday — slides due Wednesday." **Medium** (anticipation agent item with clear basis): attribute and present — "Anticipation agent flagged quarterly review prep based on last quarter's timing." **Low** (speculative anticipation, inferred deadline, or pattern-based prediction): hedge — "Possible need to prepare for investor update" or "May want to schedule design review based on sprint cadence." Never hedge confirmed calendar events or explicit deadlines; never state pattern-based predictions as confirmed plans. 100 100 + **Forward Look** — What's coming. Draw from anticipated activity records and upcoming scheduled items (next 7 days). Note preparation needed for upcoming meetings or deadlines. 101 101 + Attribute schedule-derived items: `(from [schedule](sol://...))`. Data source: `sol call activities list --source anticipated` or the schedule talent output path. 102 102 + Grade forward items by evidence strength. **High** (confirmed scheduled item or explicit deadline): state assertively — "Board meeting Thursday — slides due Wednesday." **Medium** (schedule-derived activity record with clear basis): attribute and present — "Schedule extraction flagged quarterly review prep based on last quarter's timing." **Low** (speculative schedule inference or pattern-based prediction): hedge — "Possible need to prepare for investor update" or "May want to schedule design review based on sprint cadence." Never hedge confirmed scheduled items or explicit deadlines; never state pattern-based predictions as confirmed plans. 103 103 104 104 **Reading** — Links to full facet newsletters for deep dives. List each active facet that has a newsletter for the analysis day, with a brief one-line description of what it covers. This is the "detailed edition" for owners who want the full picture. Only include if facet newsletters exist. 105 105 ··· 141 141 142 142 ## Forward Look 143 143 - Board meeting Thursday — slides need review (confirmed on [calendar](sol://20260327/calendar)) 144 144 - - May want to prepare quarterly metrics based on last quarter's timing (from [anticipation](sol://20260327/talents/anticipation)) 144 144 + - May want to prepare quarterly metrics based on last quarter's timing (from [schedule](sol://20260327/talents/schedule)) 145 145 [more items...] 146 146 147 147 ## Reading

+1 -1

talent/partner.md

reviewed

··· 36 36 37 37 1. `sol call entities strength --since YYYYMMDD` (7 days back) — relationship activity 38 38 2. For each of the past 7 days: 39 39 - - `sol call calendar list YYYYMMDD` — schedule patterns 39 39 + - `sol call activities list --source anticipated --day YYYYMMDD` — scheduled activity patterns 40 40 - `sol call todos list -d YYYYMMDD` — task patterns 41 41 3. For each active facet (from `sol call journal facets`): 42 42 - `sol call journal news FACET --day YYYYMMDD` (most recent day available) — work themes

+138 -48

talent/schedule.md

reviewed

··· 2 2 "type": "generate", 3 3 4 4 "title": "Upcoming Schedule", 5 5 - "description": "Identifies all future calendar events and scheduled activities noted in transcripts. Extracts dates, times, participants, and event details for anything scheduled beyond today.", 6 6 - "hook": {"post": "anticipation"}, 5 5 + "description": "Extracts future scheduled events and calendar activities into structured anticipation records. Captures dates, times, participants, and cancellation state.", 6 6 + "hook": {"post": "schedule"}, 7 7 "color": "#5e35b1", 8 8 "schedule": "daily", 9 9 "priority": 10, 10 10 - "output": "md", 10 10 + "output": "json", 11 11 "load": {"transcripts": true, "percepts": false, "talents": {"screen": true}} 12 12 - 13 12 } 14 13 15 14 $daily_preamble 16 15 17 16 # Future Schedule Extraction 18 17 19 19 - **Input:** A markdown file containing chronologically ordered transcripts of a workday. The transcript combines audio recordings and screen activity organized by recording segments. 18 18 + **Input:** A markdown file containing chronologically ordered transcripts of a workday plus the screen agent's output for the same day. Calendar views, meeting invitations, scheduling UIs, and project-management interfaces are captured in the screen content; verbal mentions of future plans appear in transcripts. 20 19 21 21 - **Objective:** Identify and extract all future scheduled events and calendar entries visible or mentioned throughout the day. Focus exclusively on events scheduled for dates beyond today - not current day or historical events. 20 20 + **Your task:** Identify every future scheduled item (dated after today) visible in the day's screen or transcript content and emit a JSON array of anticipation objects. 22 21 23 23 - **Instructions:** 22 22 + ## What to capture 24 23 25 25 - 1. **Scan for Calendar Views:** Review all screen activity descriptions for: 26 26 - - Calendar applications (Google Calendar, Outlook, Apple Calendar, etc.) 27 27 - - Scheduling interfaces (Calendly, meeting schedulers, etc.) 28 28 - - Email invitations showing future dates 29 29 - - Project management tools with scheduled deadlines 30 30 - - Any interface displaying future dates and times 24 24 + Look for: 25 25 + - Calendar applications (Google Calendar, Outlook, Apple Calendar, Fantastical, etc.) 26 26 + - Scheduling interfaces (Calendly, meeting schedulers, SavvyCal, meet.solpbc.org) 27 27 + - Email invitations or confirmations showing future dates 28 28 + - Project management tools (Linear, Jira, Asana, Trello) with scheduled deadlines or milestones 29 29 + - Travel bookings (flights, reservations, itineraries) 30 30 + - Any UI element displaying a future date, time, or deadline 31 31 + - Verbal mentions of firm future commitments ("I'm meeting Ramon on Tuesday at 3", "flight leaves Friday morning") 31 32 32 32 - 2. **Extract Event Details:** For each future scheduled item identified, capture: 33 33 - - **Date & Time:** Full date and time information if available 34 34 - - **Event Title:** The name or subject of the scheduled event 35 35 - - **Participants:** Meeting attendees or people involved if visible 36 36 - - **Location:** Physical location or meeting link/platform 37 37 - - **Duration:** Expected length of the event 38 38 - - **Description:** Any additional context or agenda items visible 33 33 + **Include cancelled items too.** Calendar views often show cancelled events with a strikethrough, a "Cancelled" label, a declined-invite indicator, or a greyed-out style. Emit these with `"cancelled": true` — the downstream pipeline needs to know a previously-scheduled item dropped off. 39 34 40 40 - 3. **Organize Chronologically:** Sort all identified events by their scheduled date and time, nearest future events first. 35 35 + Do NOT capture: 36 36 + - Past events (anything on today or earlier — future only) 37 37 + - Vague intent without a date ("we should catch up sometime") 38 38 + - Recurring-series headers with no specific upcoming instance visible (capture the next specific instance if visible; otherwise skip) 39 39 + - Tentative suggestions that haven't been confirmed 41 40 42 42 - 4. **Focus on the Future:** 43 43 - - Include only events scheduled for tomorrow and beyond 44 44 - - Exclude today's events (already happened or happening) 45 45 - - Exclude past events visible in calendar history 46 46 - - Include recurring events' future instances if visible 41 41 + ## Output schema 47 42 48 48 - ## Output Format 43 43 + Return **only** a JSON array. Each element is an anticipation object with these fields: 49 44 50 50 - Produce a clean Markdown document with: 45 45 + ```json 46 46 + [ 47 47 + { 48 48 + "activity": "meeting", 49 49 + "target_date": "2026-04-20", 50 50 + "start": "16:30:00", 51 51 + "end": "17:30:00", 52 52 + "title": "Yuri Namikawa intro call", 53 53 + "description": "Intro call with Yuri from Offline Ventures about solstone.", 54 54 + "details": "Google Meet; prep one-pager + demo backup", 55 55 + "participation": [ 56 56 + { 57 57 + "name": "Yuri Namikawa", 58 58 + "role": "attendee", 59 59 + "source": "screen", 60 60 + "confidence": 0.9, 61 61 + "context": "visible on calendar invite; Offline Ventures" 62 62 + } 63 63 + ], 64 64 + "participation_confidence": 0.9, 65 65 + "facet": "solstone", 66 66 + "cancelled": false 67 67 + } 68 68 + ] 69 69 + ``` 51 70 52 52 - ### Header Section 53 53 - A brief overview stating the date range of scheduled events found and total count. 71 71 + ### Field-by-field 54 72 55 55 - ### Event Listings 56 56 - For each future event, create a formatted entry with: 57 57 - - **Date:** [Day, Full Date] 58 58 - - **Time:** [Start - End time with timezone if available] 59 59 - - **Event:** [Title/Subject] 60 60 - - **Participants:** [List of attendees if visible] 61 61 - - **Location:** [Physical/Virtual location] 62 62 - - **Notes:** [Any additional context, agenda items, or preparation needed] 73 73 + - **`activity`** — Short descriptive string for the kind of scheduled item. Pick the best fit for what you're seeing. Common examples: `meeting`, `call`, `deadline`, `appointment`, `event`, `travel`, `reminder`, `errand`, `celebration`. **Not a restricted enum** — use whatever label best describes the item. Lowercase, underscore-separated if multi-word (e.g., `doctor_appointment`). 63 74 64 64 - ### Summary 65 65 - Conclude with a brief summary highlighting: 66 66 - - The next upcoming event 67 67 - - Any particularly important or unusual scheduled items 68 68 - - General schedule density for the upcoming segment 75 75 + - **`target_date`** — ISO date `YYYY-MM-DD`. The day the item is scheduled for. Must be strictly after today. 69 76 70 70 - ## Important Notes 71 71 - - Only extract what is clearly visible on screen or captured in a transcript 72 72 - - Don't infer or guess event details 73 73 - - Focus on definite scheduled items, not tentative plans mentioned in conversation 74 74 - - Include both personal and professional scheduled events if visible 77 77 + - **`start`** — `HH:MM:SS` (24-hour). If the time is vague ("morning", "afternoon") or unknown, use `null` and mention the vagueness in `details`. For all-day items, use `null`. 78 78 + 79 79 + - **`end`** — `HH:MM:SS`. Use `null` if not known. 80 80 + 81 81 + - **`title`** — Short descriptive title for the anticipation (one phrase — what a human would call this item at a glance). 82 82 + 83 83 + - **`description`** — One-sentence description: what is planned and any context that's evident. Written to read naturally. 84 84 + 85 85 + - **`details`** — Free-form string. Location, meeting platform, agenda hints, prep notes, recurrence pattern, anything else relevant. May be empty string `""`. 86 86 + 87 87 + - **`participation`** — Array of participant objects. Each entry: 88 88 + - `name` — Full name if visible, otherwise the best form available. 89 89 + - `role` — `"attendee"` for people expected to be live in the meeting/call; `"mentioned"` otherwise. 90 90 + - `source` — Where the evidence came from: `"voice"`, `"speaker_label"`, `"transcript"`, `"screen"`, or `"other"`. 91 91 + - `confidence` — `0.0`–`1.0` — your confidence the person will actually be there. 92 92 + - `context` — Short string explaining why this person belongs here. 93 93 + - For deadlines, reminders, or solo items with no one else involved, `participation` is `[]`. 94 94 + 95 95 + - **`participation_confidence`** — `0.0`–`1.0` — overall confidence in the participation list for this item. Lower when many attendees are inferred rather than confirmed. 96 96 + 97 97 + - **`facet`** — Facet ID from the configured facets context. Required. If no facet fits cleanly, skip the item rather than miscategorizing. 98 98 + 99 99 + - **`cancelled`** — Boolean. `true` when the screen shows this item as cancelled (strikethrough, "Cancelled" label, declined, greyed out). `false` otherwise. 100 100 + 101 101 + ## Rules 102 102 + 103 103 + 1. **Return only valid JSON.** An array, possibly empty (`[]`). No commentary, no prose. 104 104 + 2. **ISO dates.** `YYYY-MM-DD` for `target_date`; `HH:MM:SS` or `null` for `start`/`end`. 105 105 + 3. **Be specific.** Don't invent details. If information isn't visible, use `null` or omit the field per the schema. 106 106 + 4. **Future only.** Items with `target_date <= today` get dropped. 107 107 + 5. **Cancelled events included.** Emit them with `"cancelled": true`. 108 108 + 6. **Dedupe within the run.** If the same item appears on multiple screens throughout the day (e.g., seen at 9am in calendar and again at 3pm in email), emit it once with the strongest evidence. 109 109 + 7. **Skip uncertain items.** If you can't tell whether an item is future-dated or has an identifiable date, skip it rather than guessing. 110 110 + 8. **One facet per item.** If an item spans facets, pick the dominant one. 111 111 + 112 112 + ## Examples 113 113 + 114 114 + Valid output with three future items (one cancelled): 115 115 + 116 116 + ```json 117 117 + [ 118 118 + { 119 119 + "activity": "call", 120 120 + "target_date": "2026-04-21", 121 121 + "start": "10:30:00", 122 122 + "end": "11:00:00", 123 123 + "title": "Mari Zumbro intro", 124 124 + "description": "First call with Mari Zumbro per mutual intro from Ramon.", 125 125 + "details": "Google Meet; prep one-liner on solstone", 126 126 + "participation": [ 127 127 + {"name": "Mari Zumbro", "role": "attendee", "source": "screen", "confidence": 0.95, "context": "calendar invite"} 128 128 + ], 129 129 + "participation_confidence": 0.9, 130 130 + "facet": "solstone", 131 131 + "cancelled": false 132 132 + }, 133 133 + { 134 134 + "activity": "deadline", 135 135 + "target_date": "2026-05-05", 136 136 + "start": null, 137 137 + "end": null, 138 138 + "title": "Demo Day", 139 139 + "description": "Betaworks Camp Demo Day.", 140 140 + "details": "Live demo presentation to cohort investors", 141 141 + "participation": [], 142 142 + "participation_confidence": 0.5, 143 143 + "facet": "solstone", 144 144 + "cancelled": false 145 145 + }, 146 146 + { 147 147 + "activity": "meeting", 148 148 + "target_date": "2026-04-24", 149 149 + "start": "09:00:00", 150 150 + "end": "10:00:00", 151 151 + "title": "Scott Ward standup", 152 152 + "description": "Weekly standup with Scott Ward.", 153 153 + "details": "Recurring; previously showing strikethrough on calendar", 154 154 + "participation": [ 155 155 + {"name": "Scott Ward", "role": "attendee", "source": "screen", "confidence": 0.85, "context": "recurring invite, now declined"} 156 156 + ], 157 157 + "participation_confidence": 0.85, 158 158 + "facet": "solstone", 159 159 + "cancelled": true 160 160 + } 161 161 + ] 162 162 + ``` 163 163 + 164 164 + If no future items are found, return `[]`.

+203

talent/schedule.py

reviewed

··· 1 1 + # SPDX-License-Identifier: AGPL-3.0-only 2 2 + # Copyright (c) 2026 sol pbc 3 3 + 4 4 + """Hook for writing schedule-derived planned items as activity records.""" 5 5 + 6 6 + from __future__ import annotations 7 7 + 8 8 + import json 9 9 + import logging 10 10 + import re 11 11 + from datetime import datetime 12 12 + from typing import Any 13 13 + 14 14 + from think.activities import ( 15 15 + append_activity_record, 16 16 + append_edit, 17 17 + dedup_anticipation, 18 18 + make_anticipation_id, 19 19 + mute_activity_record, 20 20 + ) 21 21 + from think.entities.loading import load_entities 22 22 + from think.entities.matching import find_matching_entity 23 23 + from think.facets import get_facets 24 24 + 25 25 + logger = logging.getLogger(__name__) 26 26 + 27 27 + _TIME_RE = re.compile(r"^\d{2}:\d{2}:\d{2}$") 28 28 + 29 29 + 30 30 + def _require_text(item: dict[str, Any], key: str) -> str: 31 31 + value = item.get(key) 32 32 + if not isinstance(value, str) or not value.strip(): 33 33 + raise ValueError(f"missing required field '{key}'") 34 34 + return value.strip() 35 35 + 36 36 + 37 37 + def _optional_time(item: dict[str, Any], key: str) -> str | None: 38 38 + value = item.get(key) 39 39 + if value is None: 40 40 + return None 41 41 + if not isinstance(value, str) or not _TIME_RE.fullmatch(value): 42 42 + raise ValueError(f"invalid {key!r}: expected HH:MM:SS or null") 43 43 + return value 44 44 + 45 45 + 46 46 + def post_process(result: str, context: dict) -> None: 47 47 + """Persist schedule-derived planned items as activity records.""" 48 48 + try: 49 49 + events = json.loads(result.strip()) 50 50 + except json.JSONDecodeError as exc: 51 51 + snippet = result.strip()[:200] 52 52 + logger.error("schedule hook: failed to parse JSON: %s snippet=%r", exc, snippet) 53 53 + return None 54 54 + 55 55 + if not isinstance(events, list): 56 56 + logger.error("schedule hook: expected top-level array") 57 57 + return None 58 58 + 59 59 + day = str(context.get("day") or "") 60 60 + try: 61 61 + current_day = datetime.strptime(day, "%Y%m%d").date() 62 62 + except ValueError: 63 63 + logger.error("schedule hook: invalid context day %r", day) 64 64 + return None 65 65 + 66 66 + known_facets = set(get_facets().keys()) 67 67 + entity_cache: dict[tuple[str, str], list[dict[str, Any]]] = {} 68 68 + 69 69 + for raw_event in events: 70 70 + try: 71 71 + if not isinstance(raw_event, dict): 72 72 + raise ValueError("expected object") 73 73 + 74 74 + activity = _require_text(raw_event, "activity") 75 75 + target_date = _require_text(raw_event, "target_date") 76 76 + title = _require_text(raw_event, "title") 77 77 + description = _require_text(raw_event, "description") 78 78 + facet = _require_text(raw_event, "facet") 79 79 + if facet not in known_facets: 80 80 + raise ValueError(f"unknown facet {facet!r}") 81 81 + 82 82 + target_day = datetime.strptime(target_date, "%Y-%m-%d").date() 83 83 + if target_day <= current_day: 84 84 + raise ValueError( 85 85 + f"target_date must be after context day ({target_date} <= {day})" 86 86 + ) 87 87 + 88 88 + start = _optional_time(raw_event, "start") 89 89 + end = _optional_time(raw_event, "end") 90 90 + cancelled = bool(raw_event.get("cancelled", False)) 91 91 + details = str(raw_event.get("details") or "") 92 92 + participation_confidence = raw_event.get("participation_confidence") 93 93 + participation = raw_event.get("participation", []) 94 94 + if not isinstance(participation, list): 95 95 + raise ValueError("participation must be a list") 96 96 + 97 97 + cache_key = (facet, target_day.strftime("%Y%m%d")) 98 98 + entities_list = entity_cache.get(cache_key) 99 99 + if entities_list is None: 100 100 + entities_list = load_entities(facet=facet, day=cache_key[1]) 101 101 + entity_cache[cache_key] = entities_list 102 102 + 103 103 + resolved_participation: list[dict[str, Any]] = [] 104 104 + active_entities: list[str] = [] 105 105 + seen_active_entities: set[str] = set() 106 106 + for entry in participation: 107 107 + if not isinstance(entry, dict): 108 108 + continue 109 109 + 110 110 + resolved_entry = dict(entry) 111 111 + match = find_matching_entity( 112 112 + resolved_entry.get("name", ""), entities_list 113 113 + ) 114 114 + entity_id = match.get("id") if match else None 115 115 + resolved_entry["entity_id"] = entity_id 116 116 + resolved_participation.append(resolved_entry) 117 117 + 118 118 + if resolved_entry.get("role") != "attendee" or not entity_id: 119 119 + continue 120 120 + if entity_id in seen_active_entities: 121 121 + continue 122 122 + seen_active_entities.add(entity_id) 123 123 + active_entities.append(entity_id) 124 124 + 125 125 + new_id = make_anticipation_id(activity, start, target_date) 126 126 + record = { 127 127 + "id": new_id, 128 128 + "activity": activity, 129 129 + "target_date": target_date, 130 130 + "start": start, 131 131 + "end": end, 132 132 + "title": title, 133 133 + "description": description, 134 134 + "details": details, 135 135 + "facet": facet, 136 136 + "source": "anticipated", 137 137 + "active_entities": active_entities, 138 138 + "participation": resolved_participation, 139 139 + "participation_confidence": participation_confidence, 140 140 + "cancelled": cancelled, 141 141 + "hidden": cancelled, 142 142 + } 143 143 + record = append_edit( 144 144 + record, 145 145 + actor="schedule", 146 146 + fields=[ 147 147 + "activity", 148 148 + "target_date", 149 149 + "start", 150 150 + "end", 151 151 + "title", 152 152 + "description", 153 153 + "details", 154 154 + "source", 155 155 + "active_entities", 156 156 + "participation", 157 157 + "participation_confidence", 158 158 + "cancelled", 159 159 + "hidden", 160 160 + ], 161 161 + note=( 162 162 + "created by schedule (cancelled on calendar)" 163 163 + if cancelled 164 164 + else "created by schedule" 165 165 + ), 166 166 + ) 167 167 + 168 168 + should_write, superseded_ids = dedup_anticipation( 169 169 + facet, 170 170 + target_day.strftime("%Y%m%d"), 171 171 + record, 172 172 + ) 173 173 + if not should_write: 174 174 + logger.info( 175 175 + "schedule hook: duplicate anticipated activity id=%s", new_id 176 176 + ) 177 177 + continue 178 178 + 179 179 + written = append_activity_record( 180 180 + facet, 181 181 + target_day.strftime("%Y%m%d"), 182 182 + record, 183 183 + ) 184 184 + if not written: 185 185 + logger.info("schedule hook: append lost race for id=%s", new_id) 186 186 + continue 187 187 + 188 188 + for superseded_id in superseded_ids: 189 189 + mute_activity_record( 190 190 + facet, 191 191 + target_day.strftime("%Y%m%d"), 192 192 + superseded_id, 193 193 + actor="schedule", 194 194 + reason=f"superseded by {new_id}", 195 195 + ) 196 196 + except Exception as exc: 197 197 + logger.warning( 198 198 + "schedule hook: skipping invalid item %r: %s", 199 199 + raw_event, 200 200 + exc, 201 201 + ) 202 202 + 203 203 + return None

-6

talent/triage.md

reviewed

··· 22 22 - `sol call todos cancel LINE --day DAY --facet FACET` — Cancel a todo. 23 23 - `sol call todos upcoming --facet FACET [--limit N]` — Show upcoming todos. 24 24 25 25 - ### Calendar 26 26 - - `sol call calendar list [DAY] --facet FACET` — List events for a day. 27 27 - - `sol call calendar create TITLE --start HH:MM --day DAY --facet FACET [--end HH:MM] [--summary TEXT] [--participants NAMES]` — Create a calendar event. 28 28 - - `sol call calendar update LINE --day DAY --facet FACET [--title TEXT] [--start HH:MM] [--end HH:MM] [--summary TEXT] [--participants NAMES]` — Update an event. 29 29 - - `sol call calendar cancel LINE --day DAY --facet FACET` — Cancel an event. 30 30 - 31 25 ### Entities 32 26 - `sol call entities list [FACET]` — List entities for a facet. 33 27 - `sol call entities observations ENTITY --facet FACET` — List observations for an entity.

+1 -1

tests/baselines/api/search/search.json

reviewed

··· 1 1 { 2 2 - "talents": [], 3 2 "days": [], 4 3 "facets": [ 5 4 { ··· 60 59 } 61 60 ], 62 61 "showing_days": 0, 62 62 + "talents": [], 63 63 "total": 0, 64 64 "total_days": 0 65 65 }

+8 -8

tests/baselines/api/settings/generators.json

reviewed

··· 32 32 }, 33 33 { 34 34 "app": null, 35 35 - "description": "Extracts people, projects, tools and other entities from the transcript and maps how they relate. Produces a Markdown report plus narrative describing network hubs and bridges discovered during the day.", 35 35 + "description": "Extracts future scheduled events and calendar activities into structured anticipation records. Captures dates, times, participants, and cancellation state.", 36 36 "disabled": false, 37 37 - "extract": true, 38 38 - "has_extraction": true, 39 39 - "key": "knowledge_graph", 37 37 + "extract": null, 38 38 + "has_extraction": false, 39 39 + "key": "schedule", 40 40 "source": "system", 41 41 - "title": "Knowledge Graph" 41 41 + "title": "Upcoming Schedule" 42 42 }, 43 43 { 44 44 "app": null, 45 45 - "description": "Identifies all future calendar events and scheduled activities noted in transcripts. Extracts dates, times, participants, and event details for anything scheduled beyond today.", 45 45 + "description": "Extracts people, projects, tools and other entities from the transcript and maps how they relate. Produces a Markdown report plus narrative describing network hubs and bridges discovered during the day.", 46 46 "disabled": false, 47 47 "extract": true, 48 48 "has_extraction": true, 49 49 - "key": "schedule", 49 49 + "key": "knowledge_graph", 50 50 "source": "system", 51 51 - "title": "Upcoming Schedule" 51 51 + "title": "Knowledge Graph" 52 52 }, 53 53 { 54 54 "app": null,

-8

tests/baselines/api/settings/providers.json

reviewed

··· 183 183 "tier": 2, 184 184 "type": "cogitate" 185 185 }, 186 186 - "talent.system.anticipation": { 187 187 - "disabled": false, 188 188 - "group": "Think", 189 189 - "label": "Anticipation Extraction", 190 190 - "tier": 2, 191 191 - "type": null 192 192 - }, 193 186 "talent.system.awareness_tender": { 194 187 "disabled": false, 195 188 "group": "Think", ··· 377 370 }, 378 371 "talent.system.schedule": { 379 372 "disabled": false, 380 380 - "extract": true, 381 373 "group": "Think", 382 374 "label": "Upcoming Schedule", 383 375 "schedule": "daily",

+13 -13

tests/baselines/api/sol/run-detail.json

reviewed

··· 4 4 "error_message": null, 5 5 "events": [ 6 6 { 7 7 - "use_id": "1700000000001", 8 7 "args": null, 9 8 "call_id": "call_001", 10 9 "event": "tool_end", 11 10 "result": "{\"total\": 2, \"results\": [{\"title\": \"Project Update Meeting\", \"day\": \"20231114\"}, {\"title\": \"Weekly Status\", \"day\": \"20231115\"}]}", 12 11 "tool": "tool", 13 13 - "ts": 1700000000500 12 12 + "ts": 1700000000500, 13 13 + "use_id": "1700000000001" 14 14 }, 15 15 { 16 16 - "use_id": "1700000000001", 17 16 "args": { 18 17 "limit": 5, 19 18 "query": "project updates" ··· 21 20 "call_id": "call_001", 22 21 "event": "tool_start", 23 22 "tool": "search_events", 24 24 - "ts": 1700000000400 23 23 + "ts": 1700000000400, 24 24 + "use_id": "1700000000001" 25 25 }, 26 26 { 27 27 - "use_id": "1700000000001", 28 27 "content": "The user wants to search for meetings about project updates.\nI should use the search_events tool to find relevant meetings.", 29 28 "event": "thinking", 30 30 - "ts": 1700000000300 29 29 + "ts": 1700000000300, 30 30 + "use_id": "1700000000001" 31 31 }, 32 32 { 33 33 - "use_id": "1700000000001", 34 33 "event": "finish", 35 34 "result": "I found 2 meetings about project updates:\n\n1. **Project Update Meeting** on 2023-11-14\n2. **Weekly Status** on 2023-11-15", 36 35 "ts": 1700000000600, 37 36 "usage": { 38 37 "input_tokens": 150, 39 38 "output_tokens": 80 40 40 - } 39 39 + }, 40 40 + "use_id": "1700000000001" 41 41 }, 42 42 { 43 43 - "use_id": "1700000000001", 44 43 "event": "start", 45 44 "model": "gpt-4o", 46 45 "name": "default", 47 46 "prompt": "Search for meetings about project updates", 48 47 "provider": "openai", 49 49 - "ts": 1700000000100 48 48 + "ts": 1700000000100, 49 49 + "use_id": "1700000000001" 50 50 }, 51 51 { 52 52 - "talent": "solstone", 53 53 - "use_id": "1700000000001", 54 52 "event": "talent_updated", 55 55 - "ts": 1700000000200 53 53 + "talent": "solstone", 54 54 + "ts": 1700000000200, 55 55 + "use_id": "1700000000001" 56 56 } 57 57 ], 58 58 "facet": null,

+40 -51

tests/baselines/api/sol/talents-day.json

reviewed

··· 1 1 { 2 2 + "facets": { 3 3 + "capulet": { 4 4 + "color": "#dc143c", 5 5 + "title": "Capulet Industries" 6 6 + }, 7 7 + "empty-entities": { 8 8 + "color": "", 9 9 + "title": "Empty Entities Test" 10 10 + }, 11 11 + "full-featured": { 12 12 + "color": "#28a745", 13 13 + "title": "Full Featured Facet" 14 14 + }, 15 15 + "minimal-facet": { 16 16 + "color": "", 17 17 + "title": "Minimal Facet" 18 18 + }, 19 19 + "montague": { 20 20 + "color": "#1e90ff", 21 21 + "title": "Montague Tech" 22 22 + }, 23 23 + "muted-test": { 24 24 + "color": "", 25 25 + "title": "Muted Test" 26 26 + }, 27 27 + "priority-test": { 28 28 + "color": "", 29 29 + "title": "Priority Test" 30 30 + }, 31 31 + "test-facet": { 32 32 + "color": "#007bff", 33 33 + "title": "Test Facet" 34 34 + }, 35 35 + "verona": { 36 36 + "color": "#9370db", 37 37 + "title": "Verona" 38 38 + } 39 39 + }, 2 40 "talents": { 3 41 "activities:activities_review": { 4 42 "app": "activities", ··· 10 48 "source": "app", 11 49 "title": "Activities Review", 12 50 "type": "cogitate" 13 13 - }, 14 14 - "anticipation": { 15 15 - "app": null, 16 16 - "color": "#4527a0", 17 17 - "description": "Extracts structured anticipation events (future scheduled items) from insight summaries.", 18 18 - "multi_facet": false, 19 19 - "output_format": null, 20 20 - "schedule": null, 21 21 - "source": "system", 22 22 - "title": "Anticipation Extraction", 23 23 - "type": null 24 51 }, 25 52 "awareness_tender": { 26 53 "app": null, ··· 377 404 "schedule": { 378 405 "app": null, 379 406 "color": "#5e35b1", 380 380 - "description": "Identifies all future calendar events and scheduled activities noted in transcripts. Extracts dates, times, participants, and event details for anything scheduled beyond today.", 407 407 + "description": "Extracts future scheduled events and calendar activities into structured anticipation records. Captures dates, times, participants, and cancellation state.", 381 408 "multi_facet": false, 382 382 - "output_format": "md", 409 409 + "output_format": "json", 383 410 "schedule": "daily", 384 411 "source": "system", 385 412 "title": "Upcoming Schedule", ··· 505 532 "source": "system", 506 533 "title": "Triage", 507 534 "type": "cogitate" 508 508 - } 509 509 - }, 510 510 - "facets": { 511 511 - "capulet": { 512 512 - "color": "#dc143c", 513 513 - "title": "Capulet Industries" 514 514 - }, 515 515 - "empty-entities": { 516 516 - "color": "", 517 517 - "title": "Empty Entities Test" 518 518 - }, 519 519 - "full-featured": { 520 520 - "color": "#28a745", 521 521 - "title": "Full Featured Facet" 522 522 - }, 523 523 - "minimal-facet": { 524 524 - "color": "", 525 525 - "title": "Minimal Facet" 526 526 - }, 527 527 - "montague": { 528 528 - "color": "#1e90ff", 529 529 - "title": "Montague Tech" 530 530 - }, 531 531 - "muted-test": { 532 532 - "color": "", 533 533 - "title": "Muted Test" 534 534 - }, 535 535 - "priority-test": { 536 536 - "color": "", 537 537 - "title": "Priority Test" 538 538 - }, 539 539 - "test-facet": { 540 540 - "color": "#007bff", 541 541 - "title": "Test Facet" 542 542 - }, 543 543 - "verona": { 544 544 - "color": "#9370db", 545 545 - "title": "Verona" 546 535 } 547 536 }, 548 537 "uses": []

+18 -18

tests/baselines/api/stats/stats.json

reviewed

··· 8 8 "pre": "daily_schedule" 9 9 }, 10 10 "load": { 11 11 - "talents": false, 12 11 "percepts": false, 12 12 + "talents": false, 13 13 "transcripts": false 14 14 }, 15 15 "max_output_tokens": 512, ··· 36 36 "post": "occurrence" 37 37 }, 38 38 "load": { 39 39 + "percepts": false, 39 40 "talents": { 40 41 "screen": true 41 42 }, 42 42 - "percepts": false, 43 43 "transcripts": true 44 44 }, 45 45 "mtime": 0, ··· 59 59 "pre": "documents" 60 60 }, 61 61 "load": { 62 62 + "percepts": false, 62 63 "talents": false, 63 63 - "percepts": false, 64 64 "transcripts": true 65 65 }, 66 66 "max_output_tokens": 8192, ··· 81 81 "post": "entities" 82 82 }, 83 83 "load": { 84 84 - "talents": false, 85 84 "percepts": true, 85 85 + "talents": false, 86 86 "transcripts": true 87 87 }, 88 88 "max_output_tokens": 1024, ··· 106 106 "pre": "entities:entity_observer" 107 107 }, 108 108 "load": { 109 109 - "talents": false, 110 109 "percepts": false, 110 110 + "talents": false, 111 111 "transcripts": false 112 112 }, 113 113 "mtime": 0, ··· 129 129 "post": "occurrence" 130 130 }, 131 131 "load": { 132 132 + "percepts": false, 132 133 "talents": { 133 134 "screen": true 134 135 }, 135 135 - "percepts": false, 136 136 "transcripts": true 137 137 }, 138 138 "mtime": 0, ··· 158 158 "post": "occurrence" 159 159 }, 160 160 "load": { 161 161 + "percepts": false, 161 162 "talents": { 162 163 "screen": true 163 164 }, 164 164 - "percepts": false, 165 165 "transcripts": true 166 166 }, 167 167 "mtime": 0, ··· 181 181 "post": "occurrence" 182 182 }, 183 183 "load": { 184 184 + "percepts": false, 184 185 "talents": { 185 186 "screen": true 186 187 }, 187 187 - "percepts": false, 188 188 "transcripts": true 189 189 }, 190 190 "mtime": 0, ··· 207 207 "post": "occurrence" 208 208 }, 209 209 "load": { 210 210 + "percepts": false, 210 211 "talents": { 211 212 "screen": true 212 213 }, 213 213 - "percepts": false, 214 214 "transcripts": true 215 215 }, 216 216 "mtime": 0, ··· 234 234 "post": "occurrence" 235 235 }, 236 236 "load": { 237 237 + "percepts": false, 237 238 "talents": { 238 239 "screen": true 239 240 }, 240 240 - "percepts": false, 241 241 "transcripts": true 242 242 }, 243 243 "mtime": 0, ··· 278 278 }, 279 279 "schedule": { 280 280 "color": "#5e35b1", 281 281 - "description": "Identifies all future calendar events and scheduled activities noted in transcripts. Extracts dates, times, participants, and event details for anything scheduled beyond today.", 281 281 + "description": "Extracts future scheduled events and calendar activities into structured anticipation records. Captures dates, times, participants, and cancellation state.", 282 282 "hook": { 283 283 - "post": "anticipation" 283 283 + "post": "schedule" 284 284 }, 285 285 "load": { 286 286 + "percepts": false, 286 287 "talents": { 287 288 "screen": true 288 289 }, 289 289 - "percepts": false, 290 290 "transcripts": true 291 291 }, 292 292 "mtime": 0, 293 293 - "output": "md", 293 293 + "output": "json", 294 294 "path": "<PROJECT>/talent/schedule.md", 295 295 "priority": 10, 296 296 "schedule": "daily", ··· 302 302 "color": "#9c27b0", 303 303 "description": "Creates a detailed documentary record of screen activity. Focuses on the 'what' - chronological account with preserved details, excerpts, and entities.", 304 304 "load": { 305 305 - "talents": false, 306 305 "percepts": "required", 306 306 + "talents": false, 307 307 "transcripts": true 308 308 }, 309 309 "mtime": 0, ··· 319 319 "color": "#ff6f00", 320 320 "description": "Unified segment understanding — density, content type, entities, facets, speakers, and routing recommendations in a single pass", 321 321 "load": { 322 322 - "talents": false, 323 322 "percepts": true, 323 323 + "talents": false, 324 324 "transcripts": true 325 325 }, 326 326 "max_output_tokens": 4096, ··· 346 346 "pre": "skills" 347 347 }, 348 348 "load": { 349 349 - "talents": false, 350 349 "percepts": false, 350 350 + "talents": false, 351 351 "transcripts": false 352 352 }, 353 353 "mtime": 0, ··· 389 389 "post": "occurrence" 390 390 }, 391 391 "load": { 392 392 + "percepts": false, 392 393 "talents": { 393 394 "screen": true 394 395 }, 395 395 - "percepts": false, 396 396 "transcripts": true 397 397 }, 398 398 "mtime": 0,

-3

tests/baselines/api/talents/badge-count.json

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··· 1 1 - { 2 2 - "count": 0 3 3 - }

-6

tests/baselines/api/talents/preview.json

reviewed

··· 1 1 - { 2 2 - "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 think 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 observed media too.\"\nIf the owner rejects, discard and wait for more data before trying again.\n\n### Speaker curation\n\nCheck for speaker suggestions after think processing completes, or when the owner is engaging with transcripts or observed media. Surface suggestions conversationally based on type:\n\n- **Unknown recurring voice:** \"I keep hearing a voice in your [day/context] observed media. 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 observed media. 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.", 3 3 - "multi_facet": false, 4 4 - "name": "unified", 5 5 - "title": "Sol" 6 6 - }

-71

tests/baselines/api/talents/run-detail.json

reviewed

··· 1 1 - { 2 2 - "cost": 0.001175, 3 3 - "day": "20231114", 4 4 - "error_message": null, 5 5 - "events": [ 6 6 - { 7 7 - "use_id": "1700000000001", 8 8 - "args": null, 9 9 - "call_id": "call_001", 10 10 - "event": "tool_end", 11 11 - "result": "{\"total\": 2, \"results\": [{\"title\": \"Project Update Meeting\", \"day\": \"20231114\"}, {\"title\": \"Weekly Status\", \"day\": \"20231115\"}]}", 12 12 - "tool": "tool", 13 13 - "ts": 1700000000500 14 14 - }, 15 15 - { 16 16 - "use_id": "1700000000001", 17 17 - "args": { 18 18 - "limit": 5, 19 19 - "query": "project updates" 20 20 - }, 21 21 - "call_id": "call_001", 22 22 - "event": "tool_start", 23 23 - "tool": "search_events", 24 24 - "ts": 1700000000400 25 25 - }, 26 26 - { 27 27 - "use_id": "1700000000001", 28 28 - "content": "The user wants to search for meetings about project updates.\nI should use the search_events tool to find relevant meetings.", 29 29 - "event": "thinking", 30 30 - "ts": 1700000000300 31 31 - }, 32 32 - { 33 33 - "use_id": "1700000000001", 34 34 - "event": "finish", 35 35 - "result": "I found 2 meetings about project updates:\n\n1. **Project Update Meeting** on 2023-11-14\n2. **Weekly Status** on 2023-11-15", 36 36 - "ts": 1700000000600, 37 37 - "usage": { 38 38 - "input_tokens": 150, 39 39 - "output_tokens": 80 40 40 - } 41 41 - }, 42 42 - { 43 43 - "use_id": "1700000000001", 44 44 - "event": "start", 45 45 - "model": "gpt-4o", 46 46 - "name": "default", 47 47 - "prompt": "Search for meetings about project updates", 48 48 - "provider": "openai", 49 49 - "ts": 1700000000100 50 50 - }, 51 51 - { 52 52 - "talent": "solstone", 53 53 - "use_id": "1700000000001", 54 54 - "event": "talent_updated", 55 55 - "ts": 1700000000200 56 56 - } 57 57 - ], 58 58 - "facet": null, 59 59 - "failed": false, 60 60 - "id": "1700000000001", 61 61 - "model": "gpt-4o", 62 62 - "name": "default", 63 63 - "output_file": null, 64 64 - "prompt": "Search for meetings about project updates", 65 65 - "provider": "openai", 66 66 - "runtime_seconds": 0.599, 67 67 - "start": 1700000000001, 68 68 - "status": "completed", 69 69 - "thinking_count": 1, 70 70 - "tool_count": 1 71 71 - }

-25

tests/baselines/api/talents/stats-month.json

reviewed

··· 1 1 - { 2 2 - "20260304": { 3 3 - "_none": 3 4 4 - }, 5 5 - "20260305": { 6 6 - "_none": 2, 7 7 - "verona": 1 8 8 - }, 9 9 - "20260306": { 10 10 - "_none": 2 11 11 - }, 12 12 - "20260307": { 13 13 - "_none": 2 14 14 - }, 15 15 - "20260308": { 16 16 - "_none": 3 17 17 - }, 18 18 - "20260309": { 19 19 - "_none": 1 20 20 - }, 21 21 - "20260310": { 22 22 - "_none": 3, 23 23 - "verona": 1 24 24 - } 25 25 - }

-461

tests/baselines/api/talents/talents-day.json

reviewed

··· 1 1 - { 2 2 - "talents": { 3 3 - "anticipation": { 4 4 - "app": null, 5 5 - "color": "#4527a0", 6 6 - "description": "Extracts structured anticipation events (future scheduled items) from insight summaries.", 7 7 - "multi_facet": false, 8 8 - "output_format": null, 9 9 - "schedule": null, 10 10 - "source": "system", 11 11 - "title": "Anticipation Extraction", 12 12 - "type": null 13 13 - }, 14 14 - "awareness_tender": { 15 15 - "app": null, 16 16 - "color": "#6c757d", 17 17 - "description": "Maintains sol/awareness.md — a compact situational awareness snapshot", 18 18 - "multi_facet": false, 19 19 - "output_format": null, 20 20 - "schedule": "segment", 21 21 - "source": "system", 22 22 - "title": "Awareness Tender", 23 23 - "type": "cogitate" 24 24 - }, 25 25 - "chat": { 26 26 - "app": null, 27 27 - "color": "#6c757d", 28 28 - "description": "Sol — the journal itself, as a conversational partner", 29 29 - "multi_facet": false, 30 30 - "output_format": null, 31 31 - "schedule": null, 32 32 - "source": "system", 33 33 - "title": "Sol", 34 34 - "type": "cogitate" 35 35 - }, 36 36 - "coder": { 37 37 - "app": null, 38 38 - "color": "#6c757d", 39 39 - "description": "Developer agent with full repo read/write access", 40 40 - "multi_facet": false, 41 41 - "output_format": null, 42 42 - "schedule": null, 43 43 - "source": "system", 44 44 - "title": "Coder", 45 45 - "type": "cogitate" 46 46 - }, 47 47 - "daily_schedule": { 48 48 - "app": null, 49 49 - "color": "#455a64", 50 50 - "description": "Analyzes activity patterns to identify optimal times for scheduled maintenance tasks.", 51 51 - "multi_facet": false, 52 52 - "output_format": "json", 53 53 - "schedule": "daily", 54 54 - "source": "system", 55 55 - "title": "Maintenance Window", 56 56 - "type": "generate" 57 57 - }, 58 58 - "decisionalizer": { 59 59 - "app": null, 60 60 - "color": "#c62828", 61 61 - "description": "Analyzes the day's top decision-actions to create detailed dossiers identifying gaps and stakeholder impacts", 62 62 - "multi_facet": false, 63 63 - "output_format": "md", 64 64 - "schedule": "daily", 65 65 - "source": "system", 66 66 - "title": "Decision Dossier Generator", 67 67 - "type": "cogitate" 68 68 - }, 69 69 - "decisions": { 70 70 - "app": null, 71 71 - "color": "#dc3545", 72 72 - "description": "Tracks consequential decision-actions that change state, plans, resources, responsibilities, or timing in ways that affect other people.", 73 73 - "multi_facet": false, 74 74 - "output_format": "md", 75 75 - "schedule": "activity", 76 76 - "source": "system", 77 77 - "title": "Decision Actions", 78 78 - "type": "generate" 79 79 - }, 80 80 - "entities": { 81 81 - "app": null, 82 82 - "color": "#2e7d32", 83 83 - "description": "Extracts people, companies, projects, and tools from segment content", 84 84 - "multi_facet": false, 85 85 - "output_format": "md", 86 86 - "schedule": "segment", 87 87 - "source": "system", 88 88 - "title": "Entity Extraction", 89 89 - "type": "generate" 90 90 - }, 91 91 - "entities:entities": { 92 92 - "app": "entities", 93 93 - "color": "#00897b", 94 94 - "description": "Mines journal for entity mentions and records facet-scoped detections with day-specific context", 95 95 - "multi_facet": true, 96 96 - "output_format": null, 97 97 - "schedule": "daily", 98 98 - "source": "app", 99 99 - "title": "Entity Detector", 100 100 - "type": "cogitate" 101 101 - }, 102 102 - "entities:entities_review": { 103 103 - "app": "entities", 104 104 - "color": "#00796b", 105 105 - "description": "Reviews detected entities and promotes recurring ones to attached status", 106 106 - "multi_facet": true, 107 107 - "output_format": null, 108 108 - "schedule": "daily", 109 109 - "source": "app", 110 110 - "title": "Entity Reviewer", 111 111 - "type": "cogitate" 112 112 - }, 113 113 - "entities:entity_assist": { 114 114 - "app": "entities", 115 115 - "color": "#00695c", 116 116 - "description": "Quick entity addition with intelligent type detection and automatic description generation", 117 117 - "multi_facet": false, 118 118 - "output_format": null, 119 119 - "schedule": null, 120 120 - "source": "app", 121 121 - "title": "Entity Assistant", 122 122 - "type": "cogitate" 123 123 - }, 124 124 - "entities:entity_describe": { 125 125 - "app": "entities", 126 126 - "color": "#26a69a", 127 127 - "description": "Research and generate single-sentence descriptions for attached entities", 128 128 - "multi_facet": false, 129 129 - "output_format": null, 130 130 - "schedule": null, 131 131 - "source": "app", 132 132 - "title": "Entity Description", 133 133 - "type": "cogitate" 134 134 - }, 135 135 - "entities:entity_observer": { 136 136 - "app": "entities", 137 137 - "color": "#004d40", 138 138 - "description": "Extracts durable factoids about attached entities from journal content", 139 139 - "multi_facet": true, 140 140 - "output_format": null, 141 141 - "schedule": "daily", 142 142 - "source": "app", 143 143 - "title": "Entity Observer", 144 144 - "type": "cogitate" 145 145 - }, 146 146 - "facet_newsletter": { 147 147 - "app": null, 148 148 - "color": "#0d47a1", 149 149 - "description": "Creates comprehensive daily newsletters for each facet, capturing activities, progress, and insights", 150 150 - "multi_facet": true, 151 151 - "output_format": null, 152 152 - "schedule": "daily", 153 153 - "source": "system", 154 154 - "title": "Facet Newsletter Generator", 155 155 - "type": "cogitate" 156 156 - }, 157 157 - "flow": { 158 158 - "app": null, 159 159 - "color": "#17a2b8", 160 160 - "description": "Summarizes the overall flow of the workday. Looks for patterns in focus, energy, context switching and highlights productivity insights in a Markdown report.", 161 161 - "multi_facet": false, 162 162 - "output_format": "md", 163 163 - "schedule": "daily", 164 164 - "source": "system", 165 165 - "title": "Day Overview", 166 166 - "type": "generate" 167 167 - }, 168 168 - "followups": { 169 169 - "app": null, 170 170 - "color": "#ffc107", 171 171 - "description": "Detects promised tasks, commitments, and reminders for future action within each activity. Outputs a concise Markdown list of follow-ups with context.", 172 172 - "multi_facet": false, 173 173 - "output_format": "md", 174 174 - "schedule": "activity", 175 175 - "source": "system", 176 176 - "title": "Follow-Up Items", 177 177 - "type": "generate" 178 178 - }, 179 179 - "heartbeat": { 180 180 - "app": null, 181 181 - "color": "#6c757d", 182 182 - "description": "Sol's periodic self-awareness — journal health, agency tending, curation scan", 183 183 - "multi_facet": false, 184 184 - "output_format": null, 185 185 - "schedule": "none", 186 186 - "source": "system", 187 187 - "title": "Heartbeat", 188 188 - "type": "cogitate" 189 189 - }, 190 190 - "joke_bot": { 191 191 - "app": null, 192 192 - "color": "#f9a825", 193 193 - "description": "Mines the analysis day's journal for poignant moments and crafts a personalized joke delivered via message", 194 194 - "multi_facet": false, 195 195 - "output_format": "md", 196 196 - "schedule": "daily", 197 197 - "source": "system", 198 198 - "title": "Joke Bot", 199 199 - "type": "cogitate" 200 200 - }, 201 201 - "knowledge_graph": { 202 202 - "app": null, 203 203 - "color": "#6f42c1", 204 204 - "description": "Extracts people, projects, tools and other entities from the transcript and maps how they relate. Produces a Markdown report plus narrative describing network hubs and bridges discovered during the day.", 205 205 - "multi_facet": false, 206 206 - "output_format": "md", 207 207 - "schedule": "daily", 208 208 - "source": "system", 209 209 - "title": "Knowledge Graph", 210 210 - "type": "generate" 211 211 - }, 212 212 - "meetings": { 213 213 - "app": null, 214 214 - "color": "#e83e8c", 215 215 - "description": "Produces detailed meeting notes for each meeting activity, including participants, topics discussed, action items, and presentation details.", 216 216 - "multi_facet": false, 217 217 - "output_format": "md", 218 218 - "schedule": "activity", 219 219 - "source": "system", 220 220 - "title": "Meeting Notes", 221 221 - "type": "generate" 222 222 - }, 223 223 - "messaging": { 224 224 - "app": null, 225 225 - "color": "#78909c", 226 226 - "description": "Extracts contacts, channels, apps, and message content from completed messaging and email activities.", 227 227 - "multi_facet": false, 228 228 - "output_format": "md", 229 229 - "schedule": "activity", 230 230 - "source": "system", 231 231 - "title": "Messaging Summary", 232 232 - "type": "generate" 233 233 - }, 234 234 - "morning_briefing": { 235 235 - "app": null, 236 236 - "color": "#1565c0", 237 237 - "description": "Synthesizes all daily agent outputs into a structured five-section morning briefing with entity intelligence", 238 238 - "multi_facet": false, 239 239 - "output_format": "md", 240 240 - "schedule": "daily", 241 241 - "source": "system", 242 242 - "title": "Morning Briefing", 243 243 - "type": "cogitate" 244 244 - }, 245 245 - "naming": { 246 246 - "app": null, 247 247 - "color": "#6c757d", 248 248 - "description": "Proposes a personalized name for the owner's journal assistant", 249 249 - "multi_facet": false, 250 250 - "output_format": null, 251 251 - "schedule": null, 252 252 - "source": "system", 253 253 - "title": "Naming", 254 254 - "type": "cogitate" 255 255 - }, 256 256 - "occurrence": { 257 257 - "app": null, 258 258 - "color": "#37474f", 259 259 - "description": "Extracts structured occurrence events from insight summaries.", 260 260 - "multi_facet": false, 261 261 - "output_format": null, 262 262 - "schedule": null, 263 263 - "source": "system", 264 264 - "title": "Occurrence Extraction", 265 265 - "type": null 266 266 - }, 267 267 - "partner": { 268 268 - "app": null, 269 269 - "color": "#6c757d", 270 270 - "description": "Weekly observation of the journal owner's behavioral patterns — work style, communication, priorities, decision-making, expertise", 271 271 - "multi_facet": false, 272 272 - "output_format": null, 273 273 - "schedule": "weekly", 274 274 - "source": "system", 275 275 - "title": "Partner Profile", 276 276 - "type": "cogitate" 277 277 - }, 278 278 - "pulse": { 279 279 - "app": null, 280 280 - "color": "#6c757d", 281 281 - "description": "Living narrative of the owner's day — updated each segment", 282 282 - "multi_facet": false, 283 283 - "output_format": null, 284 284 - "schedule": "segment", 285 285 - "source": "system", 286 286 - "title": "Pulse", 287 287 - "type": "cogitate" 288 288 - }, 289 289 - "routine": { 290 290 - "app": null, 291 291 - "color": "#6c757d", 292 292 - "description": "User-defined routine execution — runs owner instructions on schedule", 293 293 - "multi_facet": false, 294 294 - "output_format": null, 295 295 - "schedule": "none", 296 296 - "source": "system", 297 297 - "title": "Routine", 298 298 - "type": "cogitate" 299 299 - }, 300 300 - "schedule": { 301 301 - "app": null, 302 302 - "color": "#5e35b1", 303 303 - "description": "Identifies all future calendar events and scheduled activities noted in transcripts. Extracts dates, times, participants, and event details for anything scheduled beyond today.", 304 304 - "multi_facet": false, 305 305 - "output_format": "md", 306 306 - "schedule": "daily", 307 307 - "source": "system", 308 308 - "title": "Upcoming Schedule", 309 309 - "type": "generate" 310 310 - }, 311 311 - "screen": { 312 312 - "app": null, 313 313 - "color": "#9c27b0", 314 314 - "description": "Creates a detailed documentary record of screen activity. Focuses on the 'what' - chronological account with preserved details, excerpts, and entities.", 315 315 - "multi_facet": false, 316 316 - "output_format": "md", 317 317 - "schedule": "segment", 318 318 - "source": "system", 319 319 - "title": "Screen Record", 320 320 - "type": "generate" 321 321 - }, 322 322 - "sense": { 323 323 - "app": null, 324 324 - "color": "#ff6f00", 325 325 - "description": "Unified segment understanding — density, content type, entities, facets, speakers, and routing recommendations in a single pass", 326 326 - "multi_facet": false, 327 327 - "output_format": "json", 328 328 - "schedule": "segment", 329 329 - "source": "system", 330 330 - "title": "Segment Sense", 331 331 - "type": "generate" 332 332 - }, 333 333 - "skills": { 334 334 - "app": null, 335 335 - "color": "#6c757d", 336 336 - "description": "Detects recurring activity patterns and generates structured skill documents describing what the owner does, how, and why.", 337 337 - "multi_facet": false, 338 338 - "output_format": "json", 339 339 - "schedule": "activity", 340 340 - "source": "system", 341 341 - "title": "Skill Observer", 342 342 - "type": "generate" 343 343 - }, 344 344 - "speaker_attribution": { 345 345 - "app": null, 346 346 - "color": "#d84315", 347 347 - "description": "Identifies who said what in each transcript segment. Layers 1-3 (owner, structural, acoustic) run computationally via hook; Layer 4 uses contextual LLM analysis for remaining unmatched sentences.", 348 348 - "multi_facet": false, 349 349 - "output_format": "json", 350 350 - "schedule": "segment", 351 351 - "source": "system", 352 352 - "title": "Speaker Attribution", 353 353 - "type": "generate" 354 354 - }, 355 355 - "support:support": { 356 356 - "app": "support", 357 357 - "color": "#0288d1", 358 358 - "description": "Files and monitors support requests with sol pbc — consent-gated, never sends data without explicit owner approval", 359 359 - "multi_facet": false, 360 360 - "output_format": null, 361 361 - "schedule": null, 362 362 - "source": "app", 363 363 - "title": "Support", 364 364 - "type": "cogitate" 365 365 - }, 366 366 - "timeline": { 367 367 - "app": null, 368 368 - "color": "#7b1fa2", 369 369 - "description": "Constructs a detailed chronological timeline documenting every activity, task shift, and event throughout the workday. Creates a comprehensive historical record with rich descriptions of what happened when.", 370 370 - "multi_facet": false, 371 371 - "output_format": "md", 372 372 - "schedule": "daily", 373 373 - "source": "system", 374 374 - "title": "Day Timeline", 375 375 - "type": "generate" 376 376 - }, 377 377 - "todos:daily": { 378 378 - "app": "todos", 379 379 - "color": "#ef6c00", 380 380 - "description": "Carries forward unfinished tasks, aggregates per-activity todo detections, validates completions against journal evidence, and prioritises the day's checklist.", 381 381 - "multi_facet": true, 382 382 - "output_format": null, 383 383 - "schedule": "daily", 384 384 - "source": "app", 385 385 - "title": "Daily TODO Curator", 386 386 - "type": "cogitate" 387 387 - }, 388 388 - "todos:todo": { 389 389 - "app": "todos", 390 390 - "color": "#e65100", 391 391 - "description": "Detects todo items from activity transcripts and validates existing todos against activity evidence via sol call commands.", 392 392 - "multi_facet": false, 393 393 - "output_format": null, 394 394 - "schedule": "activity", 395 395 - "source": "app", 396 396 - "title": "TODO Detector", 397 397 - "type": "cogitate" 398 398 - }, 399 399 - "todos:weekly": { 400 400 - "app": "todos", 401 401 - "color": "#f4511e", 402 402 - "description": "Audits the past week's journal follow-ups to confirm completions and surface the next five high-impact todos for today.", 403 403 - "multi_facet": false, 404 404 - "output_format": null, 405 405 - "schedule": null, 406 406 - "source": "app", 407 407 - "title": "TODO Weekly Scout", 408 408 - "type": "cogitate" 409 409 - }, 410 410 - "triage": { 411 411 - "app": null, 412 412 - "color": "#6c757d", 413 413 - "description": "Quick-action assistant for the chat bar — handles navigation, todos, calendar, and entity lookups", 414 414 - "multi_facet": false, 415 415 - "output_format": null, 416 416 - "schedule": null, 417 417 - "source": "system", 418 418 - "title": "Triage", 419 419 - "type": "cogitate" 420 420 - } 421 421 - }, 422 422 - "facets": { 423 423 - "capulet": { 424 424 - "color": "#dc143c", 425 425 - "title": "Capulet Industries" 426 426 - }, 427 427 - "empty-entities": { 428 428 - "color": "", 429 429 - "title": "Empty Entities Test" 430 430 - }, 431 431 - "full-featured": { 432 432 - "color": "#28a745", 433 433 - "title": "Full Featured Facet" 434 434 - }, 435 435 - "minimal-facet": { 436 436 - "color": "", 437 437 - "title": "Minimal Facet" 438 438 - }, 439 439 - "montague": { 440 440 - "color": "#1e90ff", 441 441 - "title": "Montague Tech" 442 442 - }, 443 443 - "muted-test": { 444 444 - "color": "", 445 445 - "title": "Muted Test" 446 446 - }, 447 447 - "priority-test": { 448 448 - "color": "", 449 449 - "title": "Priority Test" 450 450 - }, 451 451 - "test-facet": { 452 452 - "color": "#007bff", 453 453 - "title": "Test Facet" 454 454 - }, 455 455 - "verona": { 456 456 - "color": "#9370db", 457 457 - "title": "Verona" 458 458 - } 459 459 - }, 460 460 - "uses": [] 461 461 - }

-1

tests/baselines/api/talents/updated-days.json

reviewed

··· 1 1 - []

+1 -1

tests/fixtures/journal/facets/work/events/20240105.jsonl

reviewed

··· 1 1 - {"type": "meeting", "date": "2024-01-05", "start": "14:00:00", "end": "15:00:00", "title": "Project kickoff", "summary": "Initial project planning", "facet": "work", "agent": "schedule", "occurred": false, "source": "20240101/talents/schedule.md", "participants": ["Alice", "Bob", "Charlie"], "work": true, "details": "Virtual meeting to discuss Q1 roadmap"} 1 1 + {"type": "meeting", "start": "14:00:00", "end": "15:00:00", "title": "Project kickoff", "summary": "Initial project planning", "facet": "work", "agent": "meetings", "occurred": true, "source": "20240105/talents/meetings.md", "participants": ["Alice", "Bob", "Charlie"], "work": true, "details": "Virtual meeting to discuss Q1 roadmap"}

+2 -2

tests/fixtures/journal/sol/briefing.md

reviewed

··· 36 36 37 37 ## Forward Look 38 38 39 39 - - **Monday** — All-hands presentation on Q1 results. Slides need final review by Friday (from [anticipation](sol://20260327/talents/anticipation)). 39 39 + - **Monday** — All-hands presentation on Q1 results. Slides need final review by Friday (from [schedule](sol://20260327/talents/schedule)). 40 40 - **Wednesday** — Deadline for the compliance audit documentation. 41 41 - - Sarah mentioned wanting to discuss the API rate limiting strategy next week (from [anticipation](sol://20260327/talents/anticipation)). 41 41 + - Sarah mentioned wanting to discuss the API rate limiting strategy next week (from [schedule](sol://20260327/talents/schedule)). 42 42 43 43 ## Reading 44 44

+209

tests/test_activities.py

reviewed

··· 2181 2181 assert _flush_state["day"] == "20260209" 2182 2182 assert _flush_state["segment"] == "110000_300" 2183 2183 assert _flush_state["last_segment_ts"] > 0 2184 2184 + 2185 2185 + 2186 2186 + def _seed_activity_records( 2187 2187 + tmpdir: str, facet: str, day: str, records: list[dict] 2188 2188 + ) -> None: 2189 2189 + from think.activities import append_activity_record 2190 2190 + 2191 2191 + for record in records: 2192 2192 + append_activity_record(facet, day, record) 2193 2193 + 2194 2194 + 2195 2195 + def test_make_anticipation_id_builds_stable_id(): 2196 2196 + from think.activities import make_anticipation_id 2197 2197 + 2198 2198 + assert make_anticipation_id("meeting", "16:30:00", "2026-04-20") == ( 2199 2199 + "anticipated_meeting_163000_0420" 2200 2200 + ) 2201 2201 + assert make_anticipation_id("deadline", None, "2026-05-05") == ( 2202 2202 + "anticipated_deadline_000000_0505" 2203 2203 + ) 2204 2204 + 2205 2205 + 2206 2206 + @pytest.mark.parametrize( 2207 2207 + ("activity_type", "start", "target_date"), 2208 2208 + [ 2209 2209 + ("meeting", "9:00", "2026-04-20"), 2210 2210 + ("meeting", "09:00:00", "2026/04/20"), 2211 2211 + ("", "09:00:00", "2026-04-20"), 2212 2212 + ], 2213 2213 + ) 2214 2214 + def test_make_anticipation_id_rejects_malformed_inputs( 2215 2215 + activity_type, 2216 2216 + start, 2217 2217 + target_date, 2218 2218 + ): 2219 2219 + from think.activities import make_anticipation_id 2220 2220 + 2221 2221 + with pytest.raises(ValueError): 2222 2222 + make_anticipation_id(activity_type, start, target_date) 2223 2223 + 2224 2224 + 2225 2225 + def test_dedup_anticipation_returns_empty_for_first_record(monkeypatch): 2226 2226 + from think.activities import dedup_anticipation 2227 2227 + 2228 2228 + with tempfile.TemporaryDirectory() as tmpdir: 2229 2229 + monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", tmpdir) 2230 2230 + 2231 2231 + should_write, superseded_ids = dedup_anticipation( 2232 2232 + "work", 2233 2233 + "20260420", 2234 2234 + {"id": "anticipated_meeting_163000_0420", "title": "Yuri intro"}, 2235 2235 + ) 2236 2236 + 2237 2237 + assert should_write is True 2238 2238 + assert superseded_ids == [] 2239 2239 + 2240 2240 + 2241 2241 + def test_dedup_anticipation_rejects_exact_id_collision(monkeypatch): 2242 2242 + from think.activities import dedup_anticipation 2243 2243 + 2244 2244 + with tempfile.TemporaryDirectory() as tmpdir: 2245 2245 + monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", tmpdir) 2246 2246 + _seed_activity_records( 2247 2247 + tmpdir, 2248 2248 + "work", 2249 2249 + "20260420", 2250 2250 + [ 2251 2251 + { 2252 2252 + "id": "anticipated_meeting_163000_0420", 2253 2253 + "activity": "meeting", 2254 2254 + "title": "Yuri intro", 2255 2255 + "description": "Original", 2256 2256 + "source": "anticipated", 2257 2257 + } 2258 2258 + ], 2259 2259 + ) 2260 2260 + 2261 2261 + should_write, superseded_ids = dedup_anticipation( 2262 2262 + "work", 2263 2263 + "20260420", 2264 2264 + {"id": "anticipated_meeting_163000_0420", "title": "Yuri intro"}, 2265 2265 + ) 2266 2266 + 2267 2267 + assert should_write is False 2268 2268 + assert superseded_ids == [] 2269 2269 + 2270 2270 + 2271 2271 + def test_dedup_anticipation_returns_fuzzy_supersede_matches(monkeypatch): 2272 2272 + from think.activities import dedup_anticipation 2273 2273 + 2274 2274 + with tempfile.TemporaryDirectory() as tmpdir: 2275 2275 + monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", tmpdir) 2276 2276 + _seed_activity_records( 2277 2277 + tmpdir, 2278 2278 + "work", 2279 2279 + "20260420", 2280 2280 + [ 2281 2281 + { 2282 2282 + "id": "anticipated_meeting_160000_0420", 2283 2283 + "activity": "meeting", 2284 2284 + "title": "Yuri Namikawa intro call", 2285 2285 + "description": "Original", 2286 2286 + "source": "anticipated", 2287 2287 + } 2288 2288 + ], 2289 2289 + ) 2290 2290 + 2291 2291 + should_write, superseded_ids = dedup_anticipation( 2292 2292 + "work", 2293 2293 + "20260420", 2294 2294 + { 2295 2295 + "id": "anticipated_meeting_163000_0420", 2296 2296 + "title": "Yuri Namikawa intro call", 2297 2297 + }, 2298 2298 + ) 2299 2299 + 2300 2300 + assert should_write is True 2301 2301 + assert superseded_ids == ["anticipated_meeting_160000_0420"] 2302 2302 + 2303 2303 + 2304 2304 + def test_dedup_anticipation_ignores_below_threshold_and_hidden_rows(monkeypatch): 2305 2305 + from think.activities import dedup_anticipation 2306 2306 + 2307 2307 + with tempfile.TemporaryDirectory() as tmpdir: 2308 2308 + monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", tmpdir) 2309 2309 + _seed_activity_records( 2310 2310 + tmpdir, 2311 2311 + "work", 2312 2312 + "20260420", 2313 2313 + [ 2314 2314 + { 2315 2315 + "id": "anticipated_meeting_090000_0420", 2316 2316 + "activity": "meeting", 2317 2317 + "title": "Quarterly planning summit", 2318 2318 + "description": "Visible", 2319 2319 + "source": "anticipated", 2320 2320 + }, 2321 2321 + { 2322 2322 + "id": "anticipated_meeting_100000_0420", 2323 2323 + "activity": "meeting", 2324 2324 + "title": "Yuri Namikawa intro call", 2325 2325 + "description": "Hidden", 2326 2326 + "source": "anticipated", 2327 2327 + "hidden": True, 2328 2328 + }, 2329 2329 + ], 2330 2330 + ) 2331 2331 + 2332 2332 + should_write, superseded_ids = dedup_anticipation( 2333 2333 + "work", 2334 2334 + "20260420", 2335 2335 + { 2336 2336 + "id": "anticipated_meeting_163000_0420", 2337 2337 + "title": "Scott Ward standup", 2338 2338 + }, 2339 2339 + ) 2340 2340 + 2341 2341 + assert should_write is True 2342 2342 + assert superseded_ids == [] 2343 2343 + 2344 2344 + 2345 2345 + def test_dedup_anticipation_returns_all_matching_supersedes(monkeypatch): 2346 2346 + from think.activities import dedup_anticipation 2347 2347 + 2348 2348 + with tempfile.TemporaryDirectory() as tmpdir: 2349 2349 + monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", tmpdir) 2350 2350 + _seed_activity_records( 2351 2351 + tmpdir, 2352 2352 + "work", 2353 2353 + "20260420", 2354 2354 + [ 2355 2355 + { 2356 2356 + "id": "anticipated_call_090000_0420", 2357 2357 + "activity": "call", 2358 2358 + "title": "Mari Zumbro intro", 2359 2359 + "description": "Old 1", 2360 2360 + "source": "anticipated", 2361 2361 + }, 2362 2362 + { 2363 2363 + "id": "anticipated_call_093000_0420", 2364 2364 + "activity": "call", 2365 2365 + "title": "Mari Zumbro intro", 2366 2366 + "description": "Old 2", 2367 2367 + "source": "anticipated", 2368 2368 + }, 2369 2369 + { 2370 2370 + "id": "cogitate_call_100000_300", 2371 2371 + "activity": "call", 2372 2372 + "title": "Mari Zumbro intro", 2373 2373 + "description": "Non-anticipated", 2374 2374 + "source": "cogitate", 2375 2375 + }, 2376 2376 + ], 2377 2377 + ) 2378 2378 + 2379 2379 + should_write, superseded_ids = dedup_anticipation( 2380 2380 + "work", 2381 2381 + "20260420", 2382 2382 + { 2383 2383 + "id": "anticipated_call_103000_0420", 2384 2384 + "title": "Mari Zumbro intro", 2385 2385 + }, 2386 2386 + ) 2387 2387 + 2388 2388 + assert should_write is True 2389 2389 + assert superseded_ids == [ 2390 2390 + "anticipated_call_090000_0420", 2391 2391 + "anticipated_call_093000_0420", 2392 2392 + ]

+2 -2

tests/test_formatters.py

reviewed

··· 1006 1006 assert "Daily sync" in chunks[0]["markdown"] 1007 1007 assert "Task: Code review" in chunks[1]["markdown"] 1008 1008 1009 1009 - def test_format_events_anticipation_labels(self): 1010 1010 - """Test that anticipations use 'Planned', 'Scheduled', 'Expected' labels.""" 1009 1009 + def test_format_events_planned_labels(self): 1010 1010 + """Test that planned future events use 'Planned', 'Scheduled', 'Expected' labels.""" 1011 1011 from think.events import format_events 1012 1012 1013 1013 entries = [

+85

tests/test_home_yesterdays_processing.py

reviewed

··· 16 16 from apps.home.routes import ( 17 17 _briefing_freshness, 18 18 _build_pulse_context, 19 19 + _collect_activities, 20 20 + _collect_events, 19 21 _format_activity_label, 20 22 _format_duration, 21 23 _format_entity_summary, ··· 35 37 dst = journal / rel_path 36 38 dst.parent.mkdir(parents=True, exist_ok=True) 37 39 shutil.copy2(src, dst) 40 40 + 41 41 + 42 42 + def _write_jsonl(path: Path, rows: list[dict]) -> None: 43 43 + path.parent.mkdir(parents=True, exist_ok=True) 44 44 + path.write_text( 45 45 + "".join(json.dumps(row, ensure_ascii=False) + "\n" for row in rows), 46 46 + encoding="utf-8", 47 47 + ) 38 48 39 49 40 50 def _write_facet_meta(journal: Path, facet: str, title: str) -> None: ··· 248 258 monkeypatch.setattr("apps.home.routes._today", lambda: "20260417") 249 259 250 260 assert _summarize_yesterday_processing("20260416", 9) is None 261 261 + 262 262 + 263 263 + def test_collectors_merge_anticipated_events_without_double_counting( 264 264 + tmp_path, 265 265 + monkeypatch, 266 266 + ): 267 267 + journal = tmp_path / "journal" 268 268 + journal.mkdir() 269 269 + monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", str(journal)) 270 270 + 271 271 + today = "20260418" 272 272 + now_ms = int(datetime.now().timestamp() * 1000) 273 273 + 274 274 + _write_facet_meta(journal, "work", "Work") 275 275 + _write_jsonl( 276 276 + journal / "facets" / "work" / "events" / f"{today}.jsonl", 277 277 + [ 278 278 + { 279 279 + "type": "meeting", 280 280 + "title": "Team standup", 281 281 + "start": "09:00:00", 282 282 + "end": "09:30:00", 283 283 + "participants": ["Alice"], 284 284 + "occurred": True, 285 285 + } 286 286 + ], 287 287 + ) 288 288 + _write_jsonl( 289 289 + journal / "facets" / "work" / "activities" / f"{today}.jsonl", 290 290 + [ 291 291 + { 292 292 + "id": "anticipated_call_103000_0418", 293 293 + "activity": "call", 294 294 + "title": "Mari intro", 295 295 + "description": "Planned intro call", 296 296 + "target_date": "2026-04-18", 297 297 + "start": "10:30:00", 298 298 + "end": "11:00:00", 299 299 + "source": "anticipated", 300 300 + "created_at": now_ms, 301 301 + "participation": [ 302 302 + { 303 303 + "name": "Mari Zumbro", 304 304 + "role": "attendee", 305 305 + "source": "screen", 306 306 + "confidence": 0.9, 307 307 + "context": "calendar invite", 308 308 + }, 309 309 + { 310 310 + "name": "Ramon", 311 311 + "role": "mentioned", 312 312 + "source": "screen", 313 313 + "confidence": 0.6, 314 314 + "context": "note", 315 315 + }, 316 316 + ], 317 317 + }, 318 318 + { 319 319 + "id": "coding_090000_300", 320 320 + "activity": "coding", 321 321 + "title": "Focused coding", 322 322 + "description": "Recent work", 323 323 + "created_at": now_ms, 324 324 + "source": "user", 325 325 + }, 326 326 + ], 327 327 + ) 328 328 + 329 329 + events = _collect_events(today) 330 330 + activities = _collect_activities(today) 331 331 + 332 332 + assert [event["title"] for event in events] == ["Team standup", "Mari intro"] 333 333 + assert events[1]["occurred"] is False 334 334 + assert events[1]["participants"] == ["Mari Zumbro"] 335 335 + assert [activity["id"] for activity in activities] == ["coding_090000_300"] 251 336 252 337 253 338 def test_yesterdays_card_sparse_mode_copy(tmp_path, monkeypatch):

+424

tests/test_schedule_hook.py

reviewed

··· 1 1 + # SPDX-License-Identifier: AGPL-3.0-only 2 2 + # Copyright (c) 2026 sol pbc 3 3 + 4 4 + from __future__ import annotations 5 5 + 6 6 + import json 7 7 + import logging 8 8 + from pathlib import Path 9 9 + 10 10 + 11 11 + def _write_facet(journal: Path, facet: str) -> None: 12 12 + facet_path = journal / "facets" / facet / "facet.json" 13 13 + facet_path.parent.mkdir(parents=True, exist_ok=True) 14 14 + facet_path.write_text( 15 15 + json.dumps({"title": facet.title(), "description": ""}), 16 16 + encoding="utf-8", 17 17 + ) 18 18 + 19 19 + 20 20 + def _write_detected_entities( 21 21 + journal: Path, 22 22 + facet: str, 23 23 + day: str, 24 24 + rows: list[dict], 25 25 + ) -> None: 26 26 + path = journal / "facets" / facet / "entities" / f"{day}.jsonl" 27 27 + path.parent.mkdir(parents=True, exist_ok=True) 28 28 + path.write_text( 29 29 + "".join(json.dumps(row, ensure_ascii=False) + "\n" for row in rows), 30 30 + encoding="utf-8", 31 31 + ) 32 32 + 33 33 + 34 34 + def test_schedule_post_process_writes_record_and_resolves_entities( 35 35 + tmp_path, 36 36 + monkeypatch, 37 37 + ): 38 38 + from talent.schedule import post_process 39 39 + from think.activities import load_activity_records 40 40 + 41 41 + monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", str(tmp_path)) 42 42 + _write_facet(tmp_path, "work") 43 43 + _write_detected_entities( 44 44 + tmp_path, 45 45 + "work", 46 46 + "20260420", 47 47 + [ 48 48 + {"id": "yuri_namikawa", "type": "Person", "name": "Yuri Namikawa"}, 49 49 + {"id": "scott_ward", "type": "Person", "name": "Scott Ward"}, 50 50 + ], 51 51 + ) 52 52 + 53 53 + payload = [ 54 54 + { 55 55 + "activity": "meeting", 56 56 + "target_date": "2026-04-20", 57 57 + "start": "16:30:00", 58 58 + "end": "17:30:00", 59 59 + "title": "Yuri Namikawa intro call", 60 60 + "description": "Intro call with Yuri from Offline Ventures.", 61 61 + "details": "Google Meet", 62 62 + "participation": [ 63 63 + { 64 64 + "name": "Yuri Namikawa", 65 65 + "role": "attendee", 66 66 + "source": "screen", 67 67 + "confidence": 0.95, 68 68 + "context": "calendar invite", 69 69 + }, 70 70 + { 71 71 + "name": "Scott Ward", 72 72 + "role": "mentioned", 73 73 + "source": "screen", 74 74 + "confidence": 0.5, 75 75 + "context": "mentioned in notes", 76 76 + }, 77 77 + { 78 78 + "name": "Unknown Guest", 79 79 + "role": "attendee", 80 80 + "source": "screen", 81 81 + "confidence": 0.4, 82 82 + "context": "guest field", 83 83 + }, 84 84 + ], 85 85 + "participation_confidence": 0.88, 86 86 + "facet": "work", 87 87 + "cancelled": False, 88 88 + } 89 89 + ] 90 90 + 91 91 + assert post_process(json.dumps(payload), {"day": "20260418"}) is None 92 92 + 93 93 + records = load_activity_records("work", "20260420", include_hidden=True) 94 94 + assert len(records) == 1 95 95 + record = records[0] 96 96 + assert record["id"] == "anticipated_meeting_163000_0420" 97 97 + assert record["source"] == "anticipated" 98 98 + assert record["active_entities"] == ["yuri_namikawa"] 99 99 + assert record["cancelled"] is False 100 100 + assert record["hidden"] is False 101 101 + assert record["participation_confidence"] == 0.88 102 102 + assert record["participation"][0]["entity_id"] == "yuri_namikawa" 103 103 + assert record["participation"][1]["entity_id"] == "scott_ward" 104 104 + assert record["participation"][2]["entity_id"] is None 105 105 + assert record["edits"][-1]["actor"] == "schedule" 106 106 + assert record["edits"][-1]["note"] == "created by schedule" 107 107 + 108 108 + 109 109 + def test_schedule_post_process_marks_cancelled_records_hidden(tmp_path, monkeypatch): 110 110 + from talent.schedule import post_process 111 111 + from think.activities import load_activity_records 112 112 + 113 113 + monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", str(tmp_path)) 114 114 + _write_facet(tmp_path, "work") 115 115 + 116 116 + payload = [ 117 117 + { 118 118 + "activity": "meeting", 119 119 + "target_date": "2026-04-22", 120 120 + "start": "09:00:00", 121 121 + "end": "10:00:00", 122 122 + "title": "Scott Ward standup", 123 123 + "description": "Weekly standup with Scott Ward.", 124 124 + "details": "Recurring invite", 125 125 + "participation": [], 126 126 + "participation_confidence": 0.85, 127 127 + "facet": "work", 128 128 + "cancelled": True, 129 129 + } 130 130 + ] 131 131 + 132 132 + post_process(json.dumps(payload), {"day": "20260418"}) 133 133 + 134 134 + records = load_activity_records("work", "20260422", include_hidden=True) 135 135 + assert len(records) == 1 136 136 + record = records[0] 137 137 + assert record["cancelled"] is True 138 138 + assert record["hidden"] is True 139 139 + assert record["edits"][-1]["note"] == "created by schedule (cancelled on calendar)" 140 140 + 141 141 + 142 142 + def test_schedule_post_process_skips_missing_required_field( 143 143 + tmp_path, 144 144 + monkeypatch, 145 145 + caplog, 146 146 + ): 147 147 + from talent.schedule import post_process 148 148 + from think.activities import load_activity_records 149 149 + 150 150 + monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", str(tmp_path)) 151 151 + _write_facet(tmp_path, "work") 152 152 + caplog.set_level(logging.WARNING, logger="talent.schedule") 153 153 + 154 154 + post_process( 155 155 + json.dumps( 156 156 + [ 157 157 + { 158 158 + "activity": "meeting", 159 159 + "target_date": "2026-04-20", 160 160 + "start": "09:00:00", 161 161 + "end": None, 162 162 + "description": "Missing title should fail.", 163 163 + "details": "", 164 164 + "participation": [], 165 165 + "participation_confidence": 0.5, 166 166 + "facet": "work", 167 167 + "cancelled": False, 168 168 + } 169 169 + ] 170 170 + ), 171 171 + {"day": "20260418"}, 172 172 + ) 173 173 + 174 174 + assert load_activity_records("work", "20260420", include_hidden=True) == [] 175 175 + assert "missing required field 'title'" in caplog.text 176 176 + 177 177 + 178 178 + def test_schedule_post_process_skips_unknown_facet(tmp_path, monkeypatch, caplog): 179 179 + from talent.schedule import post_process 180 180 + 181 181 + monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", str(tmp_path)) 182 182 + _write_facet(tmp_path, "work") 183 183 + caplog.set_level(logging.WARNING, logger="talent.schedule") 184 184 + 185 185 + post_process( 186 186 + json.dumps( 187 187 + [ 188 188 + { 189 189 + "activity": "meeting", 190 190 + "target_date": "2026-04-20", 191 191 + "start": "09:00:00", 192 192 + "end": None, 193 193 + "title": "Wrong facet", 194 194 + "description": "This facet should be rejected.", 195 195 + "details": "", 196 196 + "participation": [], 197 197 + "participation_confidence": 0.5, 198 198 + "facet": "missing", 199 199 + "cancelled": False, 200 200 + } 201 201 + ] 202 202 + ), 203 203 + {"day": "20260418"}, 204 204 + ) 205 205 + 206 206 + assert "unknown facet 'missing'" in caplog.text 207 207 + 208 208 + 209 209 + def test_schedule_post_process_skips_non_future_items(tmp_path, monkeypatch, caplog): 210 210 + from talent.schedule import post_process 211 211 + from think.activities import load_activity_records 212 212 + 213 213 + monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", str(tmp_path)) 214 214 + _write_facet(tmp_path, "work") 215 215 + caplog.set_level(logging.WARNING, logger="talent.schedule") 216 216 + 217 217 + post_process( 218 218 + json.dumps( 219 219 + [ 220 220 + { 221 221 + "activity": "meeting", 222 222 + "target_date": "2026-04-18", 223 223 + "start": "09:00:00", 224 224 + "end": None, 225 225 + "title": "Too soon", 226 226 + "description": "Should be dropped because it is not future-dated.", 227 227 + "details": "", 228 228 + "participation": [], 229 229 + "participation_confidence": 0.5, 230 230 + "facet": "work", 231 231 + "cancelled": False, 232 232 + } 233 233 + ] 234 234 + ), 235 235 + {"day": "20260418"}, 236 236 + ) 237 237 + 238 238 + assert load_activity_records("work", "20260418", include_hidden=True) == [] 239 239 + assert "target_date must be after context day" in caplog.text 240 240 + 241 241 + 242 242 + def test_schedule_post_process_logs_error_on_invalid_json( 243 243 + tmp_path, monkeypatch, caplog 244 244 + ): 245 245 + from talent.schedule import post_process 246 246 + 247 247 + monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", str(tmp_path)) 248 248 + _write_facet(tmp_path, "work") 249 249 + caplog.set_level(logging.ERROR, logger="talent.schedule") 250 250 + 251 251 + assert post_process("{not valid json", {"day": "20260418"}) is None 252 252 + assert "failed to parse JSON" in caplog.text 253 253 + 254 254 + 255 255 + def test_schedule_post_process_is_idempotent(tmp_path, monkeypatch): 256 256 + from talent.schedule import post_process 257 257 + from think.activities import load_activity_records 258 258 + 259 259 + monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", str(tmp_path)) 260 260 + _write_facet(tmp_path, "work") 261 261 + 262 262 + payload = json.dumps( 263 263 + [ 264 264 + { 265 265 + "activity": "call", 266 266 + "target_date": "2026-04-21", 267 267 + "start": "10:30:00", 268 268 + "end": "11:00:00", 269 269 + "title": "Mari Zumbro intro", 270 270 + "description": "First call with Mari Zumbro.", 271 271 + "details": "Google Meet", 272 272 + "participation": [], 273 273 + "participation_confidence": 0.9, 274 274 + "facet": "work", 275 275 + "cancelled": False, 276 276 + } 277 277 + ] 278 278 + ) 279 279 + 280 280 + post_process(payload, {"day": "20260418"}) 281 281 + post_process(payload, {"day": "20260418"}) 282 282 + 283 283 + records = load_activity_records("work", "20260421", include_hidden=True) 284 284 + assert len(records) == 1 285 285 + assert records[0]["id"] == "anticipated_call_103000_0421" 286 286 + 287 287 + 288 288 + def test_schedule_post_process_fuzzy_supersedes_previous_record(tmp_path, monkeypatch): 289 289 + from talent.schedule import post_process 290 290 + from think.activities import append_activity_record, load_activity_records 291 291 + 292 292 + monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", str(tmp_path)) 293 293 + _write_facet(tmp_path, "work") 294 294 + 295 295 + append_activity_record( 296 296 + "work", 297 297 + "20260421", 298 298 + { 299 299 + "id": "anticipated_call_100000_0421", 300 300 + "activity": "call", 301 301 + "target_date": "2026-04-21", 302 302 + "start": "10:00:00", 303 303 + "end": "10:30:00", 304 304 + "title": "Mari Zumbro intro", 305 305 + "description": "Old version", 306 306 + "details": "", 307 307 + "facet": "work", 308 308 + "source": "anticipated", 309 309 + "participation": [], 310 310 + "active_entities": [], 311 311 + "participation_confidence": 0.8, 312 312 + "cancelled": False, 313 313 + "hidden": False, 314 314 + }, 315 315 + ) 316 316 + 317 317 + post_process( 318 318 + json.dumps( 319 319 + [ 320 320 + { 321 321 + "activity": "call", 322 322 + "target_date": "2026-04-21", 323 323 + "start": "10:30:00", 324 324 + "end": "11:00:00", 325 325 + "title": "Mari Zumbro intro", 326 326 + "description": "Updated invite", 327 327 + "details": "Google Meet", 328 328 + "participation": [], 329 329 + "participation_confidence": 0.9, 330 330 + "facet": "work", 331 331 + "cancelled": False, 332 332 + } 333 333 + ] 334 334 + ), 335 335 + {"day": "20260418"}, 336 336 + ) 337 337 + 338 338 + records = { 339 339 + record["id"]: record 340 340 + for record in load_activity_records("work", "20260421", include_hidden=True) 341 341 + } 342 342 + assert set(records) == { 343 343 + "anticipated_call_100000_0421", 344 344 + "anticipated_call_103000_0421", 345 345 + } 346 346 + assert records["anticipated_call_100000_0421"]["hidden"] is True 347 347 + assert ( 348 348 + records["anticipated_call_100000_0421"]["edits"][-1]["note"] 349 349 + == "superseded by anticipated_call_103000_0421" 350 350 + ) 351 351 + assert records["anticipated_call_103000_0421"]["hidden"] is False 352 352 + 353 353 + 354 354 + def test_schedule_post_process_cancelled_record_supersedes_pending( 355 355 + tmp_path, 356 356 + monkeypatch, 357 357 + ): 358 358 + from talent.schedule import post_process 359 359 + from think.activities import append_activity_record, load_activity_records 360 360 + 361 361 + monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", str(tmp_path)) 362 362 + _write_facet(tmp_path, "work") 363 363 + 364 364 + append_activity_record( 365 365 + "work", 366 366 + "20260424", 367 367 + { 368 368 + "id": "anticipated_meeting_090000_0424", 369 369 + "activity": "meeting", 370 370 + "target_date": "2026-04-24", 371 371 + "start": "09:00:00", 372 372 + "end": "10:00:00", 373 373 + "title": "Scott Ward standup", 374 374 + "description": "Pending version", 375 375 + "details": "", 376 376 + "facet": "work", 377 377 + "source": "anticipated", 378 378 + "participation": [], 379 379 + "active_entities": [], 380 380 + "participation_confidence": 0.85, 381 381 + "cancelled": False, 382 382 + "hidden": False, 383 383 + }, 384 384 + ) 385 385 + 386 386 + post_process( 387 387 + json.dumps( 388 388 + [ 389 389 + { 390 390 + "activity": "meeting", 391 391 + "target_date": "2026-04-24", 392 392 + "start": "09:30:00", 393 393 + "end": "10:00:00", 394 394 + "title": "Scott Ward standup", 395 395 + "description": "Calendar now shows it cancelled.", 396 396 + "details": "Recurring invite", 397 397 + "participation": [], 398 398 + "participation_confidence": 0.85, 399 399 + "facet": "work", 400 400 + "cancelled": True, 401 401 + } 402 402 + ] 403 403 + ), 404 404 + {"day": "20260418"}, 405 405 + ) 406 406 + 407 407 + records = { 408 408 + record["id"]: record 409 409 + for record in load_activity_records("work", "20260424", include_hidden=True) 410 410 + } 411 411 + assert set(records) == { 412 412 + "anticipated_meeting_090000_0424", 413 413 + "anticipated_meeting_093000_0424", 414 414 + } 415 415 + assert records["anticipated_meeting_090000_0424"]["hidden"] is True 416 416 + assert records["anticipated_meeting_093000_0424"]["hidden"] is True 417 417 + assert ( 418 418 + records["anticipated_meeting_090000_0424"]["edits"][-1]["note"] 419 419 + == "superseded by anticipated_meeting_093000_0424" 420 420 + ) 421 421 + assert ( 422 422 + records["anticipated_meeting_093000_0424"]["edits"][-1]["note"] 423 423 + == "created by schedule (cancelled on calendar)" 424 424 + )

+62

think/activities.py

reviewed

··· 10 10 stored as facets/{facet}/activities/{day}.jsonl. 11 11 """ 12 12 13 13 + import difflib 13 14 import fcntl 14 15 import json 15 16 import logging ··· 25 26 from think.utils import get_journal, segment_parse 26 27 27 28 logger = logging.getLogger(__name__) 29 29 + ANTICIPATION_FUZZY_THRESHOLD = 0.85 28 30 29 31 # --------------------------------------------------------------------------- 30 32 # Default Activities ··· 871 873 if include_hidden: 872 874 return records 873 875 return [record for record in records if not record.get("hidden", False)] 876 876 + 877 877 + 878 878 + def make_anticipation_id( 879 879 + activity_type: str, 880 880 + start: str | None, 881 881 + target_date: str, 882 882 + ) -> str: 883 883 + """Build the stable ID used for schedule-generated anticipated records.""" 884 884 + activity_key = str(activity_type or "").strip() 885 885 + if not activity_key: 886 886 + raise ValueError("activity_type must be non-empty") 887 887 + 888 888 + try: 889 889 + parsed_target = datetime.strptime(target_date, "%Y-%m-%d") 890 890 + except ValueError as exc: 891 891 + raise ValueError("target_date must match YYYY-MM-DD") from exc 892 892 + 893 893 + if start is None: 894 894 + start_key = "000000" 895 895 + else: 896 896 + if not re.fullmatch(r"\d{2}:\d{2}:\d{2}", start): 897 897 + raise ValueError("start must match HH:MM:SS") 898 898 + start_key = start.replace(":", "") 899 899 + 900 900 + return f"anticipated_{activity_key}_{start_key}_{parsed_target.strftime('%m%d')}" 901 901 + 902 902 + 903 903 + def dedup_anticipation( 904 904 + facet: str, 905 905 + target_day: str, 906 906 + new_record: dict[str, Any], 907 907 + *, 908 908 + threshold: float = ANTICIPATION_FUZZY_THRESHOLD, 909 909 + ) -> tuple[bool, list[str]]: 910 910 + """Check a new anticipated record for collisions and fuzzy supersedes.""" 911 911 + 912 912 + new_id = str(new_record.get("id") or "").strip() 913 913 + if not new_id: 914 914 + raise ValueError("new_record.id is required") 915 915 + 916 916 + def _normalize_title(value: Any) -> str: 917 917 + return " ".join(str(value or "").lower().split()) 918 918 + 919 919 + new_title = _normalize_title(new_record.get("title")) 920 920 + superseded_ids: list[str] = [] 921 921 + 922 922 + for record in load_activity_records(facet, target_day, include_hidden=False): 923 923 + if record.get("source") != "anticipated": 924 924 + continue 925 925 + 926 926 + existing_id = str(record.get("id") or "").strip() 927 927 + if existing_id == new_id: 928 928 + return False, [] 929 929 + 930 930 + existing_title = _normalize_title(record.get("title")) 931 931 + ratio = difflib.SequenceMatcher(None, new_title, existing_title).ratio() 932 932 + if ratio >= threshold: 933 933 + superseded_ids.append(existing_id) 934 934 + 935 935 + return True, superseded_ids 874 936 875 937 876 938 def load_record_ids(facet: str, day: str) -> set[str]:

+2 -2

think/events.py

reviewed

··· 126 126 ) 127 127 lines.append(f"**{participants_label}:** {', '.join(participants)}") 128 128 129 129 - # For anticipations, show when it was created (from source path) 129 129 + # For future-dated event rows, show when they were created (from source path) 130 130 if not occurred: 131 131 source = event.get("source", "") 132 132 - # Extract YYYYMMDD from source path like "20240101/talents/schedule.md" 132 132 + # Extract YYYYMMDD from source path like "20240101/talents/agent.md" 133 133 source_match = re.match(r"(\d{8})/", source) 134 134 if source_match: 135 135 created_day = source_match.group(1)

+4 -8

think/hooks.py

reviewed

··· 1 1 # SPDX-License-Identifier: AGPL-3.0-only 2 2 # Copyright (c) 2026 sol pbc 3 3 4 4 - """Shared utilities for output extraction hooks. 5 5 - 6 6 - This module provides common functions used by extraction hooks like 7 7 - occurrence.py and anticipation.py in the talent/ directory. 8 8 - """ 4 4 + """Shared utilities for output-side event hooks.""" 9 5 10 6 import json 11 7 import logging ··· 113 109 114 110 Args: 115 111 events: List of event dictionaries from extraction. 116 116 - agent: Source generator agent (e.g., "meetings", "schedule"). 117 117 - occurred: True for occurrences, False for anticipations. 112 112 + agent: Source generator agent (e.g., "meetings", "flow"). 113 113 + occurred: True for occurrence rows, False for future-dated event rows. 118 114 source_output: Relative path to source output file. 119 115 capture_day: Day the output was captured (YYYYMMDD). 120 116 ··· 146 142 # Occurrences use capture day 147 143 event_day = capture_day 148 144 else: 149 149 - # Anticipations use their scheduled date 145 145 + # Future-dated event rows use their scheduled date 150 146 event_date = event.get("date", "") 151 147 # Convert YYYY-MM-DD to YYYYMMDD 152 148 event_day = event_date.replace("-", "") if event_date else capture_day