personal memory agent
chat: swap talent layer to chat-generate + exec-cogitate
Second of three sub-lodes for the chat backend rewrite (parent plan:
chat-refactor). Flips the talent layer for the new chat architecture
while leaving runtime callers (`/api/triage`, `apps/home/events.py`,
`think/conversation.py`, the `_resolve_talent_path` `unified` alias)
alive for 2c to cut over.
- `git mv talent/chat.md -> talent/exec.md`. The renamed file is the
tier-3 cogitate "Exec" that 2c's chat backend will dispatch for
deep research. Removed the legacy `$recent_conversation` placeholder
that had been filled by the deleted pre-hook.
- New `talent/chat.md` is a tier-3 generate "Chat" with JSON schema
output at `talent/chat.schema.json`. Covers conversational framing,
routine etiquette, import/naming, and when-to-dispatch-exec — all
investigation/search/briefing depth lives in exec.md.
- Rewrote `talent/chat_context.py` to inject digest contents, chat
stream tail (via the formatter shipped in 2b), active-talent list,
trigger context, location, and the preserved 5-gate routine-
suggestion logic. Dropped `think.conversation` / L1-L2 memory
assembly. The `save_routines_config()` side effect still fires only
when `_meta.suggestions` mutates, and only `owner_message` triggers
count toward suggestion gates.
- Added `apps/sol/maint/006_rename_unified_triage_providers.py` — an
idempotent one-time migration that renames
`providers.contexts.talent.system.unified` ->
`talent.system.chat` and removes `talent.system.triage` in any
configured journal. Auto-discovered by `think.maint`.
- Audit pass on `.get("name", "unified")` call sites: 13 hard-internal
paths now require `["name"]`, 2 user-facing defaults use `"chat"`,
and 2 legacy/migration fallbacks use `"chat"` with docstring notes.
Hardcoded `name="unified"` in `convey/triage.py` is left for 2c.
- Provider-contexts baseline: removed `talent.system.triage`, added
`talent.system.exec` (tier-3 cogitate), swapped `talent.system.chat`
to tier-3 generate. `talent.system.digest` unchanged.
Collateral: `tests/verify_api.py` + three search/graph baselines
marked sandbox-only to reconcile pre-existing drift between
`make update-api-baselines` (Flask test client) and `make verify-api`
(sandbox). Pre-dated 2a; surfaced only because this lode touched
baselines. Keeping here to keep `make verify-api` green through the
sub-lode sequence.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
+2520
-516
+5
-1
apps/sol/maint/001_migrate_agent_run_logs.py
+5
-1
apps/sol/maint/001_migrate_agent_run_logs.py
···
9
9
- Build day index files (agents/<day>.jsonl) from migrated data
10
10
11
11
Use --dry-run to preview without writing changes.
12
+
13
+
Legacy unnamed run logs are treated as chat during migration so they land in the
14
+
post-refactor system talent bucket.
12
15
"""
13
16
14
17
from __future__ import annotations
···
118
121
summary.skipped += 1
119
122
continue
120
123
121
-
name = first_line.get("name", "unified")
124
+
# Legacy unnamed run logs predate the chat rename; treat them as chat.
125
+
name = first_line.get("name", "chat")
122
126
safe_name = name.replace(":", "--")
123
127
124
128
# Move to subdirectory
+152
apps/sol/maint/006_rename_unified_triage_providers.py
+152
apps/sol/maint/006_rename_unified_triage_providers.py
···
1
+
# SPDX-License-Identifier: AGPL-3.0-only
2
+
# Copyright (c) 2026 sol pbc
3
+
4
+
"""Rename legacy unified and triage provider contexts for the chat refactor."""
5
+
6
+
from __future__ import annotations
7
+
8
+
import argparse
9
+
import json
10
+
import logging
11
+
import sys
12
+
import tempfile
13
+
from dataclasses import dataclass
14
+
from pathlib import Path
15
+
16
+
from think.utils import get_journal, setup_cli
17
+
18
+
logger = logging.getLogger(__name__)
19
+
20
+
_UNIFIED_CONTEXT = "talent.system.unified"
21
+
_CHAT_CONTEXT = "talent.system.chat"
22
+
_TRIAGE_CONTEXT = "talent.system.triage"
23
+
24
+
25
+
@dataclass
26
+
class MigrationSummary:
27
+
renamed: int = 0
28
+
removed: int = 0
29
+
preserved: int = 0
30
+
errors: int = 0
31
+
skipped_reason: str | None = None
32
+
33
+
34
+
def run_migration(journal_path: Path, *, dry_run: bool) -> MigrationSummary:
35
+
summary = MigrationSummary()
36
+
config_path = journal_path / "config" / "journal.json"
37
+
38
+
if not config_path.exists():
39
+
summary.skipped_reason = "no file"
40
+
return summary
41
+
42
+
try:
43
+
raw_bytes = config_path.read_bytes()
44
+
except OSError:
45
+
logger.exception("Failed to read %s", config_path)
46
+
summary.errors += 1
47
+
return summary
48
+
49
+
if not raw_bytes.strip():
50
+
summary.skipped_reason = "empty file"
51
+
return summary
52
+
53
+
try:
54
+
raw = json.loads(raw_bytes)
55
+
except json.JSONDecodeError:
56
+
summary.skipped_reason = "unparseable"
57
+
return summary
58
+
59
+
if not isinstance(raw, dict):
60
+
summary.skipped_reason = "unparseable"
61
+
return summary
62
+
63
+
providers = raw.get("providers")
64
+
if not isinstance(providers, dict):
65
+
summary.skipped_reason = "no providers"
66
+
return summary
67
+
68
+
contexts = providers.get("contexts")
69
+
if not isinstance(contexts, dict):
70
+
summary.skipped_reason = "no contexts"
71
+
return summary
72
+
73
+
changed = False
74
+
if _UNIFIED_CONTEXT in contexts:
75
+
legacy_chat = contexts[_UNIFIED_CONTEXT]
76
+
if _CHAT_CONTEXT not in contexts:
77
+
contexts[_CHAT_CONTEXT] = legacy_chat
78
+
summary.renamed += 1
79
+
else:
80
+
summary.preserved += 1
81
+
del contexts[_UNIFIED_CONTEXT]
82
+
changed = True
83
+
84
+
if _TRIAGE_CONTEXT in contexts:
85
+
del contexts[_TRIAGE_CONTEXT]
86
+
summary.removed += 1
87
+
changed = True
88
+
89
+
if not changed:
90
+
return summary
91
+
92
+
if dry_run:
93
+
return summary
94
+
95
+
try:
96
+
_write_config(config_path, raw)
97
+
except OSError:
98
+
logger.exception("Failed to write %s", config_path)
99
+
summary.errors += 1
100
+
101
+
return summary
102
+
103
+
104
+
def _write_config(config_path: Path, config: dict) -> None:
105
+
config_dir = config_path.parent
106
+
fd, tmp_path = tempfile.mkstemp(
107
+
dir=config_dir,
108
+
suffix=".tmp",
109
+
prefix=".journal_",
110
+
text=True,
111
+
)
112
+
tmp_file = Path(tmp_path)
113
+
try:
114
+
with open(fd, "w", encoding="utf-8") as handle:
115
+
json.dump(config, handle, indent=2, ensure_ascii=False)
116
+
handle.write("\n")
117
+
tmp_file.replace(config_path)
118
+
except BaseException:
119
+
tmp_file.unlink(missing_ok=True)
120
+
raise
121
+
122
+
123
+
def _print_summary(summary: MigrationSummary) -> None:
124
+
logger.info("Summary")
125
+
logger.info(" renamed: %d", summary.renamed)
126
+
logger.info(" removed: %d", summary.removed)
127
+
logger.info(" preserved:%d", summary.preserved)
128
+
logger.info(" errors: %d", summary.errors)
129
+
if summary.skipped_reason is not None:
130
+
logger.info(" skipped: %s", summary.skipped_reason)
131
+
132
+
133
+
def main() -> None:
134
+
parser = argparse.ArgumentParser(description=__doc__.split("\n")[0])
135
+
parser.add_argument(
136
+
"--dry-run",
137
+
action="store_true",
138
+
help="Preview the provider-context rename without writing files.",
139
+
)
140
+
args = setup_cli(parser)
141
+
142
+
logging.basicConfig(level=logging.INFO, format="%(message)s")
143
+
journal_path = Path(get_journal())
144
+
summary = run_migration(journal_path, dry_run=args.dry_run)
145
+
146
+
_print_summary(summary)
147
+
if summary.errors:
148
+
sys.exit(1)
149
+
150
+
151
+
if __name__ == "__main__":
152
+
main()
+4
-4
apps/sol/routes.py
+4
-4
apps/sol/routes.py
···
50
50
day_dir = Path(journal_root) / req_day
51
51
req_segment = request_event.get("segment")
52
52
req_facet = request_event.get("facet")
53
-
req_name = request_event.get("name", "unified")
53
+
req_name = request_event["name"]
54
54
req_env = request_event.get("env") or {}
55
55
req_stream = req_env.get("SOL_STREAM") if req_env else None
56
56
return get_output_path(
···
176
176
177
177
use_info: dict[str, Any] = {
178
178
"id": use_id,
179
-
"name": request_event.get("name", "unified"),
179
+
"name": request_event["name"],
180
180
"start": request_event.get("ts", 0),
181
181
"status": "running" if is_active else "completed",
182
182
"prompt": request_event.get("prompt", ""),
···
282
282
283
283
# Locate the actual file for full parsing
284
284
use_id = entry.get("use_id", "")
285
-
name = entry.get("name", "unified")
285
+
name = entry["name"]
286
286
safe_name = name.replace(":", "--")
287
287
use_file = talents_dir / safe_name / f"{use_id}.jsonl"
288
288
if not use_file.exists():
···
465
465
466
466
run: dict[str, Any] = {
467
467
"id": use_id,
468
-
"name": request_event.get("name", "unified"),
468
+
"name": request_event["name"],
469
469
"start": start_ts,
470
470
"status": "completed",
471
471
"prompt": request_event.get("prompt", ""),
+54
-284
talent/chat.md
+54
-284
talent/chat.md
···
1
1
{
2
-
"type": "cogitate",
3
-
"title": "Sol",
4
-
"description": "Sol — the journal itself, as a conversational partner",
5
-
"hook": {"pre": "talent/chat_context.py"}
2
+
"type": "generate",
3
+
"title": "Chat",
4
+
"description": "Structured conversational reply planner for the chat backend rewrite",
5
+
"tier": 3,
6
+
"thinking_budget": 4096,
7
+
"max_output_tokens": 2048,
8
+
"output": "json",
9
+
"schema": "chat.schema.json",
10
+
"hook": {"pre": "chat_context"}
6
11
}
7
12
8
13
$facets
9
14
10
-
$recent_conversation
11
-
12
-
## Adaptive Depth
13
-
14
-
Match your response depth to the question. The owner doesn't pick a mode — you decide.
15
-
16
-
**One-liner responses** for quick actions:
17
-
- Adding, completing, or canceling todos
18
-
- Creating, updating, or canceling calendar events
19
-
- Navigating to an app or facet
20
-
- Simple lookups (list today's events, show upcoming todos)
21
-
- Confirming an action you just completed
22
-
- Pausing, resuming, or deleting a routine
23
-
24
-
After completing a quick action, respond with one concise line confirming what you did.
25
-
26
-
**Detailed responses** for deeper questions:
27
-
- Journal search and exploration
28
-
- Entity intelligence and relationship analysis
29
-
- Meeting briefings and preparation
30
-
- Routine creation conversations
31
-
- Routine output history and synthesis
32
-
- Pattern analysis across time
33
-
- Transcript reading and deep dives
34
-
- Multi-step research requiring several tool calls
35
-
- Anything that requires synthesizing information from multiple sources
36
-
- Decision support and thinking-through conversations
37
-
38
-
For detailed responses, structure your answer for clarity — lead with the key finding, then provide supporting detail. Use markdown formatting when it helps readability.
39
-
40
-
## Investigation Depth
41
-
42
-
For diagnostic, research, or exploratory questions, aim to gather your answer in 5–10 tool calls. If you reach that range without a clear answer, stop and summarize: what you found, what you couldn't determine, and what the owner could try next. Diminishing returns set in fast — don't keep searching.
43
-
44
-
## Tonal Range
45
-
46
-
You have one identity — not personas, not modes. But you have range.
47
-
48
-
Match your register to what the conversation needs:
49
-
50
-
- **Analytical**: When the owner is working through architecture, debugging,
51
-
evaluating options, or needs information synthesized. Clear, precise, direct.
52
-
Show your work.
53
-
- **Reflective**: When the owner is processing something — a difficult
54
-
conversation, a pattern they're noticing, an unresolved feeling about a
55
-
decision. Lead with questions, not solutions. Mirror what you're hearing
56
-
before offering perspective.
57
-
- **Challenging**: When the partner profile or conversation history shows a
58
-
pattern the owner may not see — repeating a decision loop, avoiding a
59
-
conversation, drifting from stated priorities. Name the pattern directly but
60
-
respectfully. "You've mentioned this three times in the last week without
61
-
acting on it. What's holding you back?"
62
-
- **Warm**: When the owner shares a win, processes something vulnerable, or
63
-
is having a genuinely hard day. Don't perform empathy — just be present.
64
-
Acknowledge what happened. Don't rush to problem-solving.
65
-
66
-
**How to read context:**
67
-
- When you need more identity context, run `sol call identity` and use its
68
-
output to understand the owner, your current priorities, and what kind of
69
-
day it's been.
70
-
- The conversation itself is the strongest signal. If the owner opens with
71
-
"I'm frustrated about..." they're not asking for a status report.
72
-
- When in doubt, start analytical and shift if the conversation goes
73
-
somewhere else. Analytical is the safest default. But don't stay there
74
-
when the conversation is clearly emotional.
75
-
76
-
**What this is NOT:**
77
-
- Not personas. You don't switch between "empathetic sol" and "analytical sol."
78
-
You're always sol. You just have range, like a person does.
79
-
- Not forced. If the day is neutral, be neutral. Don't inject warmth or
80
-
challenge where it doesn't belong.
81
-
- Not therapeutic. You're a co-brain with range, not a counselor with modalities.
82
-
83
-
## Skills
84
-
85
-
You have access to specialized skills. Use them by recognizing what the owner needs — don't ask which tool to use.
86
-
87
-
| Skill | When to trigger |
88
-
|-------|----------------|
89
-
| journal | Searching entries, reading agent output, exploring transcripts, browsing news feeds |
90
-
| routines | Creating, managing, pausing, or inspecting scheduled routines |
91
-
| entities | Listing, observing, analyzing, or searching entities and relationships |
92
-
| calendar | Creating, listing, updating, canceling, or moving calendar events |
93
-
| todos | Adding, completing, canceling, or listing todos and action items |
94
-
| speakers | Speaker identification, voice recognition, managing the speaker library |
95
-
| support | Bug reports, help requests, filing tickets, feedback, KB search, diagnostics |
96
-
| awareness | Checking system state |
97
-
98
-
## Speaker Intelligence
99
-
100
-
You 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.
101
-
102
-
### When to check
103
-
104
-
**Check speaker status during think processing or when the owner asks about speakers.** Don't check on every conversation — speaker state changes slowly.
105
-
106
-
### Owner detection
107
-
108
-
Check speaker owner status. If the owner centroid doesn't exist:
109
-
- If there are 50+ segments with embeddings across 3+ streams: good time to try detection.
110
-
- If fewer: wait. Don't mention speaker ID proactively until there's enough data.
111
-
112
-
When 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.
113
-
114
-
If the owner confirms, save the centroid. Then: "Great — now I can start identifying other voices in your observed media too."
115
-
If the owner rejects, discard and wait for more data before trying again.
116
-
117
-
### Speaker curation
118
-
119
-
Check for speaker suggestions after think processing completes, or when the owner is engaging with transcripts or observed media. Surface suggestions conversationally based on type:
120
-
121
-
- **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?"
122
-
- **Name variant:** "I noticed 'Mitch' and 'Mitch Baumgartner' sound identical in your observed media. Should I merge them?"
123
-
- **Low confidence review:** "There are a few speakers in this conversation I'm not sure about. Want to take a quick look?"
124
-
125
-
**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.
126
-
127
-
### When NOT to act
128
-
129
-
- 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."
130
-
- Don't surface low-confidence suggestions. If a cluster has only a few embeddings, wait for it to grow.
131
-
- Don't re-ask about a rejected owner candidate within the same week.
132
-
133
-
## Search and Exploration Strategy
134
-
135
-
For journal exploration, use progressive refinement:
136
-
137
-
1. **Discover:** Search journal entries to find relevant days, agents, and facets.
138
-
2. **Narrow:** Add date, agent, or facet filters to focus results.
139
-
3. **Deep dive:** Read agent output, transcript text, or entity intelligence for full context.
140
-
141
-
For 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.
142
-
143
-
## Pre-Meeting Briefings
144
-
145
-
When the owner asks "brief me on my next meeting", "who am I meeting?", or similar:
146
-
147
-
1. Find upcoming events with participants.
148
-
2. For each participant, gather entity intelligence for background.
149
-
3. Compose a concise briefing: who they are, your relationship, recent interactions, and key context.
150
-
151
-
Proactively offer briefings when context shows an upcoming meeting: "You have a meeting with [person] in [time]. Want me to brief you?"
152
-
153
-
## Decision Support
154
-
155
-
When $name asks "should I...", "help me think through...", "I'm torn between...", or "what do you think about..." — slow down. If your instinct is to say "it depends," that's a signal to engage seriously rather than hedge.
156
-
157
-
### Considering multiple angles
158
-
159
-
For weighty decisions — career moves, relationship choices, significant commitments, strategic bets — don't just give an answer. Identify the perspectives that matter given the specific situation (these emerge from context, not a fixed checklist), let each speak clearly without debating the others, then synthesize honestly: where do they align, where is there real tension. Don't paper over disagreement to sound decisive.
160
-
161
-
### Confidence signaling
162
-
163
-
Match your confidence to your actual certainty:
164
-
165
-
- **Clear path:** State your recommendation with reasoning. Don't hedge when you genuinely see one right answer.
166
-
- **Noted reservations:** Lead with the recommendation, but name the real concern worth monitoring. "$Name, I'd go with X — but watch out for Y, because..."
167
-
- **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.
15
+
## Identity Frame
168
16
169
-
Don't pretend certainty. Honest uncertainty beats false confidence — $name can handle nuance.
17
+
You are $agent_name, responding to $preferred inside the chat backend. You are not the research worker and you do not have tools in this step. Work only from the context already provided to you.
170
18
171
-
### Journal precedent
172
-
173
-
Before weighing in, search $name'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 $pronouns_possessive actual history and relationships.
174
-
175
-
## Routines
19
+
## Current Digest
176
20
177
-
Routines are scheduled tasks that run on $name's behalf — a morning briefing, a weekly review, a watch on a topic. You help $name create, adjust, and understand them through conversation. Never expose cron syntax, UUIDs, or CLI commands to $name.
21
+
$digest_contents
178
22
179
-
### Recognition
23
+
$location
180
24
181
-
Notice when $name is asking for a routine, even when they don't use that word:
25
+
$trigger_context
182
26
183
-
- **Explicit scheduling:** "every morning, summarize my calendar" / "weekly, check in on the Acme deal"
184
-
- **Frustration with repetition:** "I keep forgetting to review my todos on Friday" / "I always lose track of follow-ups"
185
-
- **Direct request:** "set up a routine" / "can you do this automatically?"
27
+
$chat_stream_tail
186
28
187
-
### Creation conversation
188
-
189
-
When you recognize routine intent, guide $name through creation:
190
-
191
-
1. **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.
192
-
2. **Confirm scope.** What facets should it cover? (Default: all, unless the intent clearly targets one area.)
193
-
3. **Confirm timing.** Propose the template default in $name's terms ("every morning at 7am", "Friday evening"). Let $name adjust.
194
-
4. **Confirm timezone.** Default to $name's local timezone from journal config. Only ask if ambiguous.
195
-
5. **Create and confirm.** Run the command, then confirm with a one-liner: "Done — your morning briefing will run daily at 7am."
196
-
197
-
Always set `--timezone` to $name's local timezone when creating routines, not UTC.
198
-
199
-
### Custom routines
200
-
201
-
When no template fits, build a custom routine:
202
-
203
-
1. Ask $name to describe what they want in plain language.
204
-
2. Draft a name, cadence (in human terms), and instruction summary. Confirm with $name.
205
-
3. Create with explicit `--name`, `--instruction`, and `--cadence` flags.
206
-
207
-
### Management
208
-
209
-
Handle routine management conversationally. $name says what they want; you translate.
210
-
211
-
- **Pause:** "pause my morning briefing" / "stop the weekly review for now" → disable the routine
212
-
- **Resume:** "turn my briefing back on" / "resume the weekly review" → re-enable it
213
-
- **Pause until:** "pause it until Monday" → disable with a resume date
214
-
- **Change timing:** "move my briefing to 8am" / "make the review run on Sunday" → edit the cadence
215
-
- **Change scope:** "add the work facet to my briefing" / "change the instruction to include..." → edit facets or instruction
216
-
- **Delete:** "I don't need the weekly review anymore" / "remove that routine" → delete after confirming
217
-
- **Inspect:** "what routines do I have?" → list all routines with status
218
-
- **History:** "what did my morning briefing say today?" / "show me last week's review" → read routine output
219
-
- **Run now:** "run my briefing now" / "do the weekly review right now" → immediate execution
220
-
- **Suggestions:** "stop suggesting routines" / "turn routine suggestions back on" → toggle suggestions
221
-
222
-
### Tone
223
-
224
-
- Treat routines like setting an alarm — workmanlike, not ceremonial. "Done — morning briefing starts tomorrow at 7am."
225
-
- Never explain how routines work internally. $name doesn't need to know about cron, agents, or output files.
226
-
- When $name asks about routine output, present it as your own knowledge: "Your morning briefing found three meetings today and two overdue follow-ups."
227
-
228
-
### Pre-hook context
29
+
$active_talents
229
30
230
31
$active_routines
231
32
232
-
When active routines appear above, they list each routine's name, cadence, status, and recent output summary.
233
-
234
-
Use this to:
235
-
- Answer "what routines do I have?" without running a command
236
-
- Reference recent routine output naturally: "Your weekly review from Friday noted..."
237
-
- Notice when a routine is paused and offer to resume it if relevant
238
-
239
-
When no routines appear above, $name has no routines yet. Don't mention routines proactively — wait for $name to express a need.
240
-
241
-
### Progressive Discovery
242
-
243
33
$routine_suggestion
244
34
245
-
When a routine suggestion appears above, $name's behavior matches a routine template. You did not request it — it was injected automatically.
35
+
## Tonal Range
246
36
247
-
**How to handle:**
248
-
- Read the pattern description to understand why the suggestion is relevant
249
-
- Mention it ONCE, naturally, at the end of your response — never lead with it
250
-
- Frame as an observation: "I've noticed this comes up often — would a routine help?"
251
-
- If $name declines or shows no interest, drop it immediately. Do not bring it up again this conversation.
252
-
- After $name responds, record the outcome:
253
-
- Accepted: `sol call routines suggest-respond {template} --accepted`
254
-
- Declined: `sol call routines suggest-respond {template} --declined`
37
+
Match the owner's tone and stakes:
38
+
- Be direct and brief for simple replies.
39
+
- Be warm when the owner is sharing something difficult or personal.
40
+
- Be analytical when the owner needs synthesis or a plan.
41
+
- Be challenging only when there is a clear pattern worth naming.
255
42
256
-
**Never:**
257
-
- Suggest a routine without the eligible section in your context
258
-
- Push a suggestion after $name declines or ignores it
259
-
- Mention the progressive discovery system or how suggestions work internally
260
-
261
-
## In-Place Handoff: Support
262
-
263
-
When 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.
264
-
265
-
**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"
266
-
267
-
**Handle support in-place:**
268
-
269
-
1. Search the knowledge base with relevant keywords. If an article answers the question, present it.
270
-
2. Run diagnostics to gather system state.
271
-
3. Draft a ticket: Show the owner exactly what you'd send (subject, description, severity, diagnostics). Ask if they want to add or redact anything.
272
-
4. Wait for approval before submitting. Never send data without explicit owner consent.
273
-
5. Confirm submission with ticket number.
43
+
## Routine Etiquette
274
44
275
-
For existing tickets, check status and present responses.
276
-
277
-
**Privacy rules for support are non-negotiable:**
278
-
- Never send data without explicit owner approval
279
-
- Never include journal content by default
280
-
- Always show the owner exactly what will be sent
281
-
- Frame yourself as the owner's advocate — "I'll handle this for you"
282
-
283
-
## Import Awareness
284
-
285
-
If 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.
286
-
287
-
## Naming Awareness
288
-
289
-
If 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 sol thickness` before offering. Only once per session.
45
+
- If a routine suggestion appears in context, mention it once and only at the end.
46
+
- Do not raise routine suggestions on machine-driven follow-ups unless the context explicitly includes one.
47
+
- Do not mention internal systems, hooks, or prompt assembly.
290
48
291
-
## Location Context
49
+
## Import And Naming Awareness
292
50
293
-
You 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.
51
+
- If the owner is asking about imports, naming, or system readiness, answer plainly from the supplied context.
52
+
- Request exec only when answering well requires deeper lookup, synthesis, or tool use.
294
53
295
-
## System Health
54
+
## When To Dispatch Exec
296
55
297
-
When the context includes a `System health:` line, there is an active attention item:
56
+
Set `talent_request` only when the owner needs work that cannot be answered well from the supplied digest, chat history, active routines, and trigger context alone.
298
57
299
-
- **"what needs my attention?"** — Report the system health item. Be concise.
300
-
- **Agent errors:** Explain which agents failed. Suggest checking logs.
301
-
- **Import complete:** Describe what was imported, offer to explore or import more.
58
+
Dispatch exec for:
59
+
- Journal exploration across days, entities, or transcripts
60
+
- Multi-step synthesis or research
61
+
- Meeting prep that needs fresh participant or activity lookup
62
+
- Any request that clearly needs tool use or external state inspection
302
63
303
-
When no `System health:` line is present, everything is fine.
64
+
Do not dispatch exec for:
65
+
- Simple acknowledgements
66
+
- Straightforward follow-up chat
67
+
- Routine suggestions already supported by the supplied context
68
+
- Brief guidance that can be answered from the current digest and chat tail
304
69
305
-
## Behavioral Defaults
70
+
## JSON Contract
306
71
307
-
- 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.
308
-
- If searching reveals sensitive or personal content, handle with care and focus on what was specifically asked.
309
-
- 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.
72
+
Return exactly one JSON object matching `chat.schema.json`.
310
73
311
-
## Tool Safety
74
+
- `message`: The owner-facing reply. Use `null` only when you genuinely have no safe or useful message to send.
75
+
- `notes`: Brief internal summary of why you responded this way. Keep it factual and concise. Do not dump long reasoning.
76
+
- `talent_request`: `null` unless exec should be dispatched. When dispatching, include:
77
+
- `task`: the exact work exec should perform
78
+
- `context`: optional structured hints that will help exec start fast
312
79
313
-
Never search or recurse across the home directory or filesystem root — no `grep -r ~/`, `find ~ -name`, `find / -name`, or equivalent broad sweeps. Keep filesystem exploration within the journal directory.
80
+
## Output Rules
314
81
315
-
If a tool call returns an error or unexpectedly large output, note it and move on. Do not retry the call with broader scope.
82
+
- Return JSON only.
83
+
- `message` should stand on its own without referring to hidden machinery.
84
+
- If `talent_request` is present, the `message` should still be useful to the owner right now.
85
+
- Prefer no dispatch over a weak or redundant dispatch.
+24
talent/chat.schema.json
+24
talent/chat.schema.json
···
1
+
{
2
+
"$schema": "https://json-schema.org/draft/2020-12/schema",
3
+
"type": "object",
4
+
"additionalProperties": false,
5
+
"required": ["message", "notes", "talent_request"],
6
+
"properties": {
7
+
"message": {"type": ["string", "null"]},
8
+
"notes": {"type": "string"},
9
+
"talent_request": {
10
+
"oneOf": [
11
+
{"type": "null"},
12
+
{
13
+
"type": "object",
14
+
"additionalProperties": false,
15
+
"required": ["task"],
16
+
"properties": {
17
+
"task": {"type": "string", "minLength": 1},
18
+
"context": {"type": "object"}
19
+
}
20
+
}
21
+
]
22
+
}
23
+
}
24
+
}
+184
-31
talent/chat_context.py
+184
-31
talent/chat_context.py
···
1
1
# SPDX-License-Identifier: AGPL-3.0-only
2
2
# Copyright (c) 2026 sol pbc
3
3
4
-
"""Pre-hook: provide template vars for chat prompt context.
4
+
"""Pre-hook: provide template vars for chat prompt context."""
5
5
6
-
Replaces conversation_memory as the unified talent's pre-hook.
7
-
Builds dynamic chat context as template vars for the identity-first
8
-
prompt while preserving routine trigger side effects and awareness
9
-
guidance.
10
-
11
-
Loaded via hook config: {"hook": {"pre": "chat_context"}}
12
-
"""
6
+
from __future__ import annotations
13
7
14
8
import logging
15
-
from datetime import date, timedelta
9
+
from datetime import date, datetime, timedelta
10
+
from pathlib import Path
11
+
from typing import Any
12
+
13
+
from convey.chat_stream import read_chat_tail, reduce_chat_state
14
+
from think.chat_formatter import format_chat
15
+
from think.utils import get_config, get_journal
16
16
17
17
logger = logging.getLogger(__name__)
18
18
···
239
239
240
240
241
241
def pre_process(context: dict) -> dict:
242
-
"""Build chat-context template vars for the unified talent prompt."""
243
-
from think.conversation import build_memory_context
244
-
from think.utils import get_config
242
+
"""Build chat-context template vars for the chat talent prompt."""
243
+
from think.routines import get_config as get_routines_config
244
+
from think.routines import get_routine_state
245
+
from think.routines import save_config as save_routines_config
245
246
246
247
facet = context.get("facet")
248
+
trigger_kind, trigger_payload = _normalize_trigger(context)
249
+
day = _resolve_day(context, trigger_payload)
247
250
template_vars = {
248
-
"recent_conversation": "",
251
+
"digest_contents": "",
252
+
"chat_stream_tail": "",
253
+
"active_talents": "",
254
+
"trigger_context": "",
255
+
"location": "",
249
256
"active_routines": "",
250
257
"routine_suggestion": "",
251
258
}
252
259
253
260
try:
254
-
memory_context = build_memory_context(facet=facet, recent_limit=10)
255
-
if memory_context:
256
-
template_vars["recent_conversation"] = (
257
-
f"## Recent Conversation\n\n{memory_context}"
261
+
template_vars["digest_contents"] = _load_digest_contents()
262
+
except Exception:
263
+
logger.debug("Digest enrichment failed", exc_info=True)
264
+
265
+
try:
266
+
tail = read_chat_tail(day, limit=20)
267
+
if tail:
268
+
chunks, _meta = format_chat(tail)
269
+
body = "\n\n".join(
270
+
chunk["markdown"] for chunk in chunks if chunk.get("markdown")
258
271
)
272
+
if body:
273
+
template_vars["chat_stream_tail"] = f"## Recent Chat\n\n{body}"
259
274
except Exception:
260
-
logger.debug("Conversation memory enrichment failed", exc_info=True)
275
+
logger.debug("Chat tail enrichment failed", exc_info=True)
261
276
262
277
try:
263
-
from think.routines import get_routine_state
278
+
state = reduce_chat_state(day)
279
+
template_vars["active_talents"] = _render_active_talents(
280
+
state.get("active_talents", [])
281
+
)
282
+
except Exception:
283
+
logger.debug("Active talent enrichment failed", exc_info=True)
284
+
285
+
template_vars["trigger_context"] = _render_trigger_context(
286
+
trigger_kind, trigger_payload, context
287
+
)
288
+
template_vars["location"] = _render_location(trigger_payload, context)
264
289
290
+
try:
265
291
routines = get_routine_state()
266
292
if routines:
267
293
lines = ["## Active Routines\n"]
···
278
304
logger.debug("Routine state enrichment failed", exc_info=True)
279
305
280
306
try:
281
-
from think.routines import get_config as get_routines_config
282
-
from think.routines import save_config as save_routines_config
283
-
284
307
prompt = context.get("prompt", "")
285
-
if prompt:
308
+
if trigger_kind == "owner_message" and prompt:
286
309
routines_config = get_routines_config()
287
310
if _count_triggers(prompt, facet, routines_config):
288
311
save_routines_config(routines_config)
···
290
313
logger.debug("Routine trigger counting failed", exc_info=True)
291
314
292
315
try:
293
-
from think.routines import get_config as get_routines_config
294
-
295
316
routines_config = get_routines_config()
296
317
suggestion = _get_eligible_suggestion(routines_config, get_config())
297
318
if suggestion:
···
306
327
f"{suggestion['trigger_count']} times since "
307
328
f"{suggestion['first_trigger']}."
308
329
)
309
-
hint = (
330
+
template_vars["routine_suggestion"] = (
310
331
"## Routine Suggestion Eligible\n\n"
311
332
f"Template: {suggestion['template_name']}\n"
312
333
f"{pattern_line}\n"
···
314
335
f"First seen: {suggestion['first_trigger']}\n\n"
315
336
"### Etiquette\n"
316
337
"- Mention this ONCE, naturally, at the end of your response\n"
317
-
"- Frame as observation: \"I've noticed you often... — would a "
318
-
'routine help?"\n'
319
-
"- If $name declines or ignores, do not bring it up again this "
320
-
"conversation\n"
338
+
'- Frame as observation: "I\'ve noticed you often... — would a routine help?"\n'
339
+
"- If $name declines or ignores, do not bring it up again this conversation\n"
321
340
"- After suggesting, run: `sol call routines suggest-respond "
322
341
f"{suggestion['template_name']} --accepted` or `--declined`"
323
342
)
324
-
template_vars["routine_suggestion"] = hint
325
343
except Exception:
326
344
logger.debug("Routine suggestion eligibility check failed", exc_info=True)
327
345
328
346
return {"template_vars": template_vars}
347
+
348
+
349
+
def _load_digest_contents() -> str:
350
+
digest_path = Path(get_journal()) / "identity" / "digest.md"
351
+
if not digest_path.exists():
352
+
return ""
353
+
return digest_path.read_text(encoding="utf-8").strip()
354
+
355
+
356
+
def _normalize_trigger(context: dict) -> tuple[str | None, dict[str, Any]]:
357
+
trigger_info = context.get("trigger")
358
+
kind = None
359
+
payload: dict[str, Any] = {}
360
+
361
+
if isinstance(trigger_info, dict):
362
+
kind = trigger_info.get("kind")
363
+
raw_payload = trigger_info.get("payload")
364
+
if isinstance(raw_payload, dict):
365
+
payload.update(raw_payload)
366
+
367
+
if not kind:
368
+
kind = context.get("trigger_kind")
369
+
370
+
raw_payload = context.get("trigger_payload")
371
+
if isinstance(raw_payload, dict):
372
+
payload.update(raw_payload)
373
+
374
+
location = context.get("location")
375
+
if isinstance(location, dict):
376
+
if "app" not in payload and location.get("app"):
377
+
payload["app"] = location["app"]
378
+
if "path" not in payload and location.get("path"):
379
+
payload["path"] = location["path"]
380
+
if "facet" not in payload and location.get("facet"):
381
+
payload["facet"] = location["facet"]
382
+
383
+
if "facet" not in payload and context.get("facet"):
384
+
payload["facet"] = context["facet"]
385
+
if "app" not in payload and context.get("app"):
386
+
payload["app"] = context["app"]
387
+
if "path" not in payload and context.get("ui_path"):
388
+
payload["path"] = context["ui_path"]
389
+
if "ts" not in payload and isinstance(context.get("trigger_ts"), int):
390
+
payload["ts"] = context["trigger_ts"]
391
+
392
+
if not kind and context.get("prompt"):
393
+
kind = "owner_message"
394
+
if kind == "owner_message" and "text" not in payload and context.get("prompt"):
395
+
payload["text"] = context["prompt"]
396
+
397
+
return kind, payload
398
+
399
+
400
+
def _resolve_day(context: dict, trigger_payload: dict[str, Any]) -> str:
401
+
day = context.get("day")
402
+
if isinstance(day, str) and len(day) == 8 and day.isdigit():
403
+
return day
404
+
405
+
ts_value = trigger_payload.get("ts")
406
+
if isinstance(ts_value, int):
407
+
return datetime.fromtimestamp(ts_value / 1000).strftime("%Y%m%d")
408
+
409
+
return date.today().strftime("%Y%m%d")
410
+
411
+
412
+
def _render_active_talents(active_talents: list[dict[str, Any]]) -> str:
413
+
if not active_talents:
414
+
return ""
415
+
416
+
lines = ["## Active Execs\n"]
417
+
for talent in active_talents:
418
+
started_at = _format_started_at(talent.get("started_at"))
419
+
line = f"- **{talent.get('name', 'exec')}** — {talent.get('task', '')}"
420
+
if started_at:
421
+
line += f" (started {started_at})"
422
+
lines.append(line)
423
+
return "\n".join(lines)
424
+
425
+
426
+
def _format_started_at(value: Any) -> str:
427
+
if not isinstance(value, int):
428
+
return ""
429
+
return datetime.fromtimestamp(value / 1000).strftime("%Y-%m-%d %H:%M")
430
+
431
+
432
+
def _render_trigger_context(
433
+
trigger_kind: str | None,
434
+
payload: dict[str, Any],
435
+
context: dict[str, Any],
436
+
) -> str:
437
+
if not trigger_kind:
438
+
return ""
439
+
440
+
lines = ["## Trigger Context\n", f"- Type: {trigger_kind}"]
441
+
if trigger_kind == "owner_message":
442
+
text = str(payload.get("text") or context.get("prompt") or "").strip()
443
+
if text:
444
+
lines.append(f"- Message: {text}")
445
+
elif trigger_kind == "talent_finished":
446
+
if payload.get("name"):
447
+
lines.append(f"- Talent: {payload['name']}")
448
+
if payload.get("summary"):
449
+
lines.append(f"- Summary: {payload['summary']}")
450
+
elif trigger_kind == "talent_errored":
451
+
if payload.get("name"):
452
+
lines.append(f"- Talent: {payload['name']}")
453
+
if payload.get("reason"):
454
+
lines.append(f"- Reason: {payload['reason']}")
455
+
elif trigger_kind == "synthetic-max-active":
456
+
if payload.get("reason"):
457
+
lines.append(f"- Reason: {payload['reason']}")
458
+
else:
459
+
if payload:
460
+
for key, value in payload.items():
461
+
lines.append(f"- {key}: {value}")
462
+
463
+
return "\n".join(lines)
464
+
465
+
466
+
def _render_location(payload: dict[str, Any], context: dict[str, Any]) -> str:
467
+
app = payload.get("app") or context.get("app")
468
+
path = payload.get("path") or context.get("ui_path")
469
+
facet = payload.get("facet") or context.get("facet")
470
+
471
+
if not any((app, path, facet)):
472
+
return ""
473
+
474
+
lines = ["## Location\n"]
475
+
if app:
476
+
lines.append(f"- App: {app}")
477
+
if path:
478
+
lines.append(f"- Path: {path}")
479
+
if facet:
480
+
lines.append(f"- Facet: {facet}")
481
+
return "\n".join(lines)
+313
talent/exec.md
+313
talent/exec.md
···
1
+
{
2
+
"type": "cogitate",
3
+
"tier": 3,
4
+
"title": "Exec",
5
+
"description": "Sol — the journal itself, as a conversational partner"
6
+
}
7
+
8
+
$facets
9
+
10
+
## Adaptive Depth
11
+
12
+
Match your response depth to the question. The owner doesn't pick a mode — you decide.
13
+
14
+
**One-liner responses** for quick actions:
15
+
- Adding, completing, or canceling todos
16
+
- Creating, updating, or canceling calendar events
17
+
- Navigating to an app or facet
18
+
- Simple lookups (list today's events, show upcoming todos)
19
+
- Confirming an action you just completed
20
+
- Pausing, resuming, or deleting a routine
21
+
22
+
After completing a quick action, respond with one concise line confirming what you did.
23
+
24
+
**Detailed responses** for deeper questions:
25
+
- Journal search and exploration
26
+
- Entity intelligence and relationship analysis
27
+
- Meeting briefings and preparation
28
+
- Routine creation conversations
29
+
- Routine output history and synthesis
30
+
- Pattern analysis across time
31
+
- Transcript reading and deep dives
32
+
- Multi-step research requiring several tool calls
33
+
- Anything that requires synthesizing information from multiple sources
34
+
- Decision support and thinking-through conversations
35
+
36
+
For detailed responses, structure your answer for clarity — lead with the key finding, then provide supporting detail. Use markdown formatting when it helps readability.
37
+
38
+
## Investigation Depth
39
+
40
+
For diagnostic, research, or exploratory questions, aim to gather your answer in 5–10 tool calls. If you reach that range without a clear answer, stop and summarize: what you found, what you couldn't determine, and what the owner could try next. Diminishing returns set in fast — don't keep searching.
41
+
42
+
## Tonal Range
43
+
44
+
You have one identity — not personas, not modes. But you have range.
45
+
46
+
Match your register to what the conversation needs:
47
+
48
+
- **Analytical**: When the owner is working through architecture, debugging,
49
+
evaluating options, or needs information synthesized. Clear, precise, direct.
50
+
Show your work.
51
+
- **Reflective**: When the owner is processing something — a difficult
52
+
conversation, a pattern they're noticing, an unresolved feeling about a
53
+
decision. Lead with questions, not solutions. Mirror what you're hearing
54
+
before offering perspective.
55
+
- **Challenging**: When the partner profile or conversation history shows a
56
+
pattern the owner may not see — repeating a decision loop, avoiding a
57
+
conversation, drifting from stated priorities. Name the pattern directly but
58
+
respectfully. "You've mentioned this three times in the last week without
59
+
acting on it. What's holding you back?"
60
+
- **Warm**: When the owner shares a win, processes something vulnerable, or
61
+
is having a genuinely hard day. Don't perform empathy — just be present.
62
+
Acknowledge what happened. Don't rush to problem-solving.
63
+
64
+
**How to read context:**
65
+
- When you need more identity context, run `sol call identity` and use its
66
+
output to understand the owner, your current priorities, and what kind of
67
+
day it's been.
68
+
- The conversation itself is the strongest signal. If the owner opens with
69
+
"I'm frustrated about..." they're not asking for a status report.
70
+
- When in doubt, start analytical and shift if the conversation goes
71
+
somewhere else. Analytical is the safest default. But don't stay there
72
+
when the conversation is clearly emotional.
73
+
74
+
**What this is NOT:**
75
+
- Not personas. You don't switch between "empathetic sol" and "analytical sol."
76
+
You're always sol. You just have range, like a person does.
77
+
- Not forced. If the day is neutral, be neutral. Don't inject warmth or
78
+
challenge where it doesn't belong.
79
+
- Not therapeutic. You're a co-brain with range, not a counselor with modalities.
80
+
81
+
## Skills
82
+
83
+
You have access to specialized skills. Use them by recognizing what the owner needs — don't ask which tool to use.
84
+
85
+
| Skill | When to trigger |
86
+
|-------|----------------|
87
+
| journal | Searching entries, reading agent output, exploring transcripts, browsing news feeds |
88
+
| routines | Creating, managing, pausing, or inspecting scheduled routines |
89
+
| entities | Listing, observing, analyzing, or searching entities and relationships |
90
+
| calendar | Creating, listing, updating, canceling, or moving calendar events |
91
+
| todos | Adding, completing, canceling, or listing todos and action items |
92
+
| speakers | Speaker identification, voice recognition, managing the speaker library |
93
+
| support | Bug reports, help requests, filing tickets, feedback, KB search, diagnostics |
94
+
| awareness | Checking system state |
95
+
96
+
## Speaker Intelligence
97
+
98
+
You 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.
99
+
100
+
### When to check
101
+
102
+
**Check speaker status during think processing or when the owner asks about speakers.** Don't check on every conversation — speaker state changes slowly.
103
+
104
+
### Owner detection
105
+
106
+
Check speaker owner status. If the owner centroid doesn't exist:
107
+
- If there are 50+ segments with embeddings across 3+ streams: good time to try detection.
108
+
- If fewer: wait. Don't mention speaker ID proactively until there's enough data.
109
+
110
+
When 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.
111
+
112
+
If the owner confirms, save the centroid. Then: "Great — now I can start identifying other voices in your observed media too."
113
+
If the owner rejects, discard and wait for more data before trying again.
114
+
115
+
### Speaker curation
116
+
117
+
Check for speaker suggestions after think processing completes, or when the owner is engaging with transcripts or observed media. Surface suggestions conversationally based on type:
118
+
119
+
- **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?"
120
+
- **Name variant:** "I noticed 'Mitch' and 'Mitch Baumgartner' sound identical in your observed media. Should I merge them?"
121
+
- **Low confidence review:** "There are a few speakers in this conversation I'm not sure about. Want to take a quick look?"
122
+
123
+
**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.
124
+
125
+
### When NOT to act
126
+
127
+
- 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."
128
+
- Don't surface low-confidence suggestions. If a cluster has only a few embeddings, wait for it to grow.
129
+
- Don't re-ask about a rejected owner candidate within the same week.
130
+
131
+
## Search and Exploration Strategy
132
+
133
+
For journal exploration, use progressive refinement:
134
+
135
+
1. **Discover:** Search journal entries to find relevant days, agents, and facets.
136
+
2. **Narrow:** Add date, agent, or facet filters to focus results.
137
+
3. **Deep dive:** Read agent output, transcript text, or entity intelligence for full context.
138
+
139
+
For 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.
140
+
141
+
## Pre-Meeting Briefings
142
+
143
+
When the owner asks "brief me on my next meeting", "who am I meeting?", or similar:
144
+
145
+
1. Find upcoming events with participants.
146
+
2. For each participant, gather entity intelligence for background.
147
+
3. Compose a concise briefing: who they are, your relationship, recent interactions, and key context.
148
+
149
+
Proactively offer briefings when context shows an upcoming meeting: "You have a meeting with [person] in [time]. Want me to brief you?"
150
+
151
+
## Decision Support
152
+
153
+
When $name asks "should I...", "help me think through...", "I'm torn between...", or "what do you think about..." — slow down. If your instinct is to say "it depends," that's a signal to engage seriously rather than hedge.
154
+
155
+
### Considering multiple angles
156
+
157
+
For weighty decisions — career moves, relationship choices, significant commitments, strategic bets — don't just give an answer. Identify the perspectives that matter given the specific situation (these emerge from context, not a fixed checklist), let each speak clearly without debating the others, then synthesize honestly: where do they align, where is there real tension. Don't paper over disagreement to sound decisive.
158
+
159
+
### Confidence signaling
160
+
161
+
Match your confidence to your actual certainty:
162
+
163
+
- **Clear path:** State your recommendation with reasoning. Don't hedge when you genuinely see one right answer.
164
+
- **Noted reservations:** Lead with the recommendation, but name the real concern worth monitoring. "$Name, I'd go with X — but watch out for Y, because..."
165
+
- **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.
166
+
167
+
Don't pretend certainty. Honest uncertainty beats false confidence — $name can handle nuance.
168
+
169
+
### Journal precedent
170
+
171
+
Before weighing in, search $name'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 $pronouns_possessive actual history and relationships.
172
+
173
+
## Routines
174
+
175
+
Routines are scheduled tasks that run on $name's behalf — a morning briefing, a weekly review, a watch on a topic. You help $name create, adjust, and understand them through conversation. Never expose cron syntax, UUIDs, or CLI commands to $name.
176
+
177
+
### Recognition
178
+
179
+
Notice when $name is asking for a routine, even when they don't use that word:
180
+
181
+
- **Explicit scheduling:** "every morning, summarize my calendar" / "weekly, check in on the Acme deal"
182
+
- **Frustration with repetition:** "I keep forgetting to review my todos on Friday" / "I always lose track of follow-ups"
183
+
- **Direct request:** "set up a routine" / "can you do this automatically?"
184
+
185
+
### Creation conversation
186
+
187
+
When you recognize routine intent, guide $name through creation:
188
+
189
+
1. **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.
190
+
2. **Confirm scope.** What facets should it cover? (Default: all, unless the intent clearly targets one area.)
191
+
3. **Confirm timing.** Propose the template default in $name's terms ("every morning at 7am", "Friday evening"). Let $name adjust.
192
+
4. **Confirm timezone.** Default to $name's local timezone from journal config. Only ask if ambiguous.
193
+
5. **Create and confirm.** Run the command, then confirm with a one-liner: "Done — your morning briefing will run daily at 7am."
194
+
195
+
Always set `--timezone` to $name's local timezone when creating routines, not UTC.
196
+
197
+
### Custom routines
198
+
199
+
When no template fits, build a custom routine:
200
+
201
+
1. Ask $name to describe what they want in plain language.
202
+
2. Draft a name, cadence (in human terms), and instruction summary. Confirm with $name.
203
+
3. Create with explicit `--name`, `--instruction`, and `--cadence` flags.
204
+
205
+
### Management
206
+
207
+
Handle routine management conversationally. $name says what they want; you translate.
208
+
209
+
- **Pause:** "pause my morning briefing" / "stop the weekly review for now" → disable the routine
210
+
- **Resume:** "turn my briefing back on" / "resume the weekly review" → re-enable it
211
+
- **Pause until:** "pause it until Monday" → disable with a resume date
212
+
- **Change timing:** "move my briefing to 8am" / "make the review run on Sunday" → edit the cadence
213
+
- **Change scope:** "add the work facet to my briefing" / "change the instruction to include..." → edit facets or instruction
214
+
- **Delete:** "I don't need the weekly review anymore" / "remove that routine" → delete after confirming
215
+
- **Inspect:** "what routines do I have?" → list all routines with status
216
+
- **History:** "what did my morning briefing say today?" / "show me last week's review" → read routine output
217
+
- **Run now:** "run my briefing now" / "do the weekly review right now" → immediate execution
218
+
- **Suggestions:** "stop suggesting routines" / "turn routine suggestions back on" → toggle suggestions
219
+
220
+
### Tone
221
+
222
+
- Treat routines like setting an alarm — workmanlike, not ceremonial. "Done — morning briefing starts tomorrow at 7am."
223
+
- Never explain how routines work internally. $name doesn't need to know about cron, agents, or output files.
224
+
- When $name asks about routine output, present it as your own knowledge: "Your morning briefing found three meetings today and two overdue follow-ups."
225
+
226
+
### Pre-hook context
227
+
228
+
$active_routines
229
+
230
+
When active routines appear above, they list each routine's name, cadence, status, and recent output summary.
231
+
232
+
Use this to:
233
+
- Answer "what routines do I have?" without running a command
234
+
- Reference recent routine output naturally: "Your weekly review from Friday noted..."
235
+
- Notice when a routine is paused and offer to resume it if relevant
236
+
237
+
When no routines appear above, $name has no routines yet. Don't mention routines proactively — wait for $name to express a need.
238
+
239
+
### Progressive Discovery
240
+
241
+
$routine_suggestion
242
+
243
+
When a routine suggestion appears above, $name's behavior matches a routine template. You did not request it — it was injected automatically.
244
+
245
+
**How to handle:**
246
+
- Read the pattern description to understand why the suggestion is relevant
247
+
- Mention it ONCE, naturally, at the end of your response — never lead with it
248
+
- Frame as an observation: "I've noticed this comes up often — would a routine help?"
249
+
- If $name declines or shows no interest, drop it immediately. Do not bring it up again this conversation.
250
+
- After $name responds, record the outcome:
251
+
- Accepted: `sol call routines suggest-respond {template} --accepted`
252
+
- Declined: `sol call routines suggest-respond {template} --declined`
253
+
254
+
**Never:**
255
+
- Suggest a routine without the eligible section in your context
256
+
- Push a suggestion after $name declines or ignores it
257
+
- Mention the progressive discovery system or how suggestions work internally
258
+
259
+
## In-Place Handoff: Support
260
+
261
+
When 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.
262
+
263
+
**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"
264
+
265
+
**Handle support in-place:**
266
+
267
+
1. Search the knowledge base with relevant keywords. If an article answers the question, present it.
268
+
2. Run diagnostics to gather system state.
269
+
3. Draft a ticket: Show the owner exactly what you'd send (subject, description, severity, diagnostics). Ask if they want to add or redact anything.
270
+
4. Wait for approval before submitting. Never send data without explicit owner consent.
271
+
5. Confirm submission with ticket number.
272
+
273
+
For existing tickets, check status and present responses.
274
+
275
+
**Privacy rules for support are non-negotiable:**
276
+
- Never send data without explicit owner approval
277
+
- Never include journal content by default
278
+
- Always show the owner exactly what will be sent
279
+
- Frame yourself as the owner's advocate — "I'll handle this for you"
280
+
281
+
## Import Awareness
282
+
283
+
If 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.
284
+
285
+
## Naming Awareness
286
+
287
+
If 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 sol thickness` before offering. Only once per session.
288
+
289
+
## Location Context
290
+
291
+
You 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.
292
+
293
+
## System Health
294
+
295
+
When the context includes a `System health:` line, there is an active attention item:
296
+
297
+
- **"what needs my attention?"** — Report the system health item. Be concise.
298
+
- **Agent errors:** Explain which agents failed. Suggest checking logs.
299
+
- **Import complete:** Describe what was imported, offer to explore or import more.
300
+
301
+
When no `System health:` line is present, everything is fine.
302
+
303
+
## Behavioral Defaults
304
+
305
+
- 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.
306
+
- If searching reveals sensitive or personal content, handle with care and focus on what was specifically asked.
307
+
- 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.
308
+
309
+
## Tool Safety
310
+
311
+
Never search or recurse across the home directory or filesystem root — no `grep -r ~/`, `find ~ -name`, `find / -name`, or equivalent broad sweeps. Keep filesystem exploration within the journal directory.
312
+
313
+
If a tool call returns an error or unexpectedly large output, note it and move on. Do not retry the call with broader scope.
+617
-6
tests/baselines/api/graph/graph.json
+617
-6
tests/baselines/api/graph/graph.json
···
1
1
{
2
-
"edges": [],
3
-
"nodes": [],
2
+
"edges": [
3
+
{
4
+
"edge_type": "co_occurrence",
5
+
"frequency": 2,
6
+
"from": "benvolio_montague",
7
+
"from_name": "Benvolio Montague",
8
+
"to": "paris_duke",
9
+
"to_name": "Paris Duke"
10
+
},
11
+
{
12
+
"edge_type": "co_occurrence",
13
+
"frequency": 2,
14
+
"from": "benvolio_montague",
15
+
"from_name": "Benvolio Montague",
16
+
"to": "prince_escalus",
17
+
"to_name": "Prince Escalus"
18
+
},
19
+
{
20
+
"edge_type": "co_occurrence",
21
+
"frequency": 2,
22
+
"from": "benvolio_montague",
23
+
"from_name": "Benvolio Montague",
24
+
"to": "tybalt_capulet",
25
+
"to_name": "Tybalt Capulet"
26
+
},
27
+
{
28
+
"edge_type": "co_occurrence",
29
+
"frequency": 2,
30
+
"from": "benvolio_montague",
31
+
"from_name": "Benvolio Montague",
32
+
"to": "verona_platform",
33
+
"to_name": "Verona Platform"
34
+
},
35
+
{
36
+
"edge_type": "co_occurrence",
37
+
"frequency": 2,
38
+
"from": "friar_lawrence",
39
+
"from_name": "Friar Lawrence",
40
+
"to": "mercutio_escalus",
41
+
"to_name": "Mercutio Escalus"
42
+
},
43
+
{
44
+
"edge_type": "co_occurrence",
45
+
"frequency": 2,
46
+
"from": "friar_lawrence",
47
+
"from_name": "Friar Lawrence",
48
+
"to": "nurse_angela",
49
+
"to_name": "Nurse Angela"
50
+
},
51
+
{
52
+
"edge_type": "co_occurrence",
53
+
"frequency": 2,
54
+
"from": "friar_lawrence",
55
+
"from_name": "Friar Lawrence",
56
+
"to": "prince_escalus",
57
+
"to_name": "Prince Escalus"
58
+
},
59
+
{
60
+
"edge_type": "co_occurrence",
61
+
"frequency": 2,
62
+
"from": "juliet_capulet",
63
+
"from_name": "Juliet Capulet",
64
+
"to": "montague_tech",
65
+
"to_name": "Montague Tech"
66
+
},
67
+
{
68
+
"edge_type": "co_occurrence",
69
+
"frequency": 2,
70
+
"from": "juliet_capulet",
71
+
"from_name": "Juliet Capulet",
72
+
"to": "prince_escalus",
73
+
"to_name": "Prince Escalus"
74
+
},
75
+
{
76
+
"edge_type": "co_occurrence",
77
+
"frequency": 2,
78
+
"from": "mercutio_escalus",
79
+
"from_name": "Mercutio Escalus",
80
+
"to": "montague_tech",
81
+
"to_name": "Montague Tech"
82
+
},
83
+
{
84
+
"edge_type": "co_occurrence",
85
+
"frequency": 2,
86
+
"from": "mercutio_escalus",
87
+
"from_name": "Mercutio Escalus",
88
+
"to": "prince_escalus",
89
+
"to_name": "Prince Escalus"
90
+
},
91
+
{
92
+
"edge_type": "co_occurrence",
93
+
"frequency": 2,
94
+
"from": "montague_tech",
95
+
"from_name": "Montague Tech",
96
+
"to": "tybalt_capulet",
97
+
"to_name": "Tybalt Capulet"
98
+
},
99
+
{
100
+
"edge_type": "co_occurrence",
101
+
"frequency": 2,
102
+
"from": "prince_escalus",
103
+
"from_name": "Prince Escalus",
104
+
"to": "tybalt_capulet",
105
+
"to_name": "Tybalt Capulet"
106
+
},
107
+
{
108
+
"edge_type": "co_occurrence",
109
+
"frequency": 2,
110
+
"from": "prince_escalus",
111
+
"from_name": "Prince Escalus",
112
+
"to": "verona_platform",
113
+
"to_name": "Verona Platform"
114
+
},
115
+
{
116
+
"edge_type": "co_occurrence",
117
+
"frequency": 3,
118
+
"from": "benvolio_montague",
119
+
"from_name": "Benvolio Montague",
120
+
"to": "friar_lawrence",
121
+
"to_name": "Friar Lawrence"
122
+
},
123
+
{
124
+
"edge_type": "co_occurrence",
125
+
"frequency": 3,
126
+
"from": "benvolio_montague",
127
+
"from_name": "Benvolio Montague",
128
+
"to": "nurse_angela",
129
+
"to_name": "Nurse Angela"
130
+
},
131
+
{
132
+
"edge_type": "co_occurrence",
133
+
"frequency": 3,
134
+
"from": "juliet_capulet",
135
+
"from_name": "Juliet Capulet",
136
+
"to": "mercutio_escalus",
137
+
"to_name": "Mercutio Escalus"
138
+
},
139
+
{
140
+
"edge_type": "co_occurrence",
141
+
"frequency": 4,
142
+
"from": "benvolio_montague",
143
+
"from_name": "Benvolio Montague",
144
+
"to": "juliet_capulet",
145
+
"to_name": "Juliet Capulet"
146
+
},
147
+
{
148
+
"edge_type": "co_occurrence",
149
+
"frequency": 4,
150
+
"from": "benvolio_montague",
151
+
"from_name": "Benvolio Montague",
152
+
"to": "mercutio_escalus",
153
+
"to_name": "Mercutio Escalus"
154
+
},
155
+
{
156
+
"edge_type": "co_occurrence",
157
+
"frequency": 4,
158
+
"from": "paris_duke",
159
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"from_name": "Paris Duke",
160
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"to": "tybalt_capulet",
161
+
"to_name": "Tybalt Capulet"
162
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163
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{
164
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165
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166
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167
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"from_name": "Friar Lawrence",
168
+
"to": "paris_duke",
169
+
"to_name": "Paris Duke"
170
+
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171
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{
172
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173
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174
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175
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176
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177
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178
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179
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{
180
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181
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182
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183
+
"from_name": "Juliet Capulet",
184
+
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185
+
"to_name": "Paris Duke"
186
+
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187
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{
188
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189
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190
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191
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192
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193
+
"to_name": "Tybalt Capulet"
194
+
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195
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196
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197
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198
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199
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200
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201
+
"to_name": "Tybalt Capulet"
202
+
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203
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204
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205
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206
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207
+
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208
+
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209
+
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210
+
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211
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212
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213
+
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214
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"from": "benvolio_montague",
215
+
"from_name": "Benvolio Montague",
216
+
"relationship_type": "suspicious-of",
217
+
"to": "romeo_montague",
218
+
"to_name": "Romeo Montague"
219
+
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220
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221
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222
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223
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224
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225
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226
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227
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228
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229
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230
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231
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232
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233
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234
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235
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236
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237
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238
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239
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240
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241
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242
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243
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244
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245
+
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246
+
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247
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248
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249
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250
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251
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252
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253
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254
+
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255
+
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256
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257
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258
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259
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260
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261
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262
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263
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264
+
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265
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266
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267
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268
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269
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270
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271
+
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272
+
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273
+
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274
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275
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276
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277
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278
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279
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280
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281
+
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282
+
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283
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284
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285
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286
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287
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288
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289
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290
+
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291
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292
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293
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294
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295
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296
+
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297
+
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298
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299
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300
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301
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302
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303
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304
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305
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306
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307
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308
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309
+
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310
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311
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312
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313
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314
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315
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316
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317
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318
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319
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320
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321
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322
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323
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327
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329
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330
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331
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332
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333
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334
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335
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336
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337
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338
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339
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340
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342
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343
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344
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345
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346
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347
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348
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349
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350
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351
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352
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353
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354
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355
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356
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357
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358
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359
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360
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361
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362
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363
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365
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367
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374
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376
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378
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379
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380
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381
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382
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383
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384
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385
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386
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387
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388
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389
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"to_name": "Juliet Capulet"
390
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}
391
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414
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463
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466
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467
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492
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569
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570
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609
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4
615
"stats": {
5
-
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6
-
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7
-
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-
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616
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619
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9
620
}
10
621
}
+19
-2
tests/baselines/api/search/day-results.json
+19
-2
tests/baselines/api/search/day-results.json
···
1
1
{
2
2
"day": "20260304",
3
3
"offset": 0,
4
-
"results": [],
5
-
"total": 0
4
+
"results": [
5
+
{
6
+
"agent": "knowledge_graph",
7
+
"agent_icon": "🗺️",
8
+
"agent_label": "Knowledge Graph",
9
+
"day": "20260304",
10
+
"facet": "",
11
+
"facet_color": "",
12
+
"facet_emoji": "",
13
+
"facet_title": "",
14
+
"id": "20260304/talents/knowledge_graph.md:7",
15
+
"idx": 7,
16
+
"path": "20260304/talents/knowledge_graph.md",
17
+
"score": -1.9,
18
+
"stream": null,
19
+
"text": "# Part 1: Entity Extraction and Relationship Mapping\n\n## Relationship Mapping\n\n| Source Name | Target Name | Relationship Type | Context |\n| :--- | :--- | :--- | :--- |\n| **Romeo Montague** | **Juliet Capulet** | `met-at-conference` | First <strong>meeting</strong> at Denver Tech Summit keynote. |\n"
20
+
}
21
+
],
22
+
"total": 1
6
23
}
+689
-8
tests/baselines/api/search/search.json
+689
-8
tests/baselines/api/search/search.json
···
1
1
{
2
-
"days": [],
2
+
"days": [
3
+
{
4
+
"date": "Friday March 6th",
5
+
"day": "20260306",
6
+
"has_more": true,
7
+
"results": [
8
+
{
9
+
"agent": "entity:detected",
10
+
"agent_icon": "👤",
11
+
"agent_label": "Entity",
12
+
"day": "20260306",
13
+
"facet": "montague",
14
+
"facet_color": "#1e90ff",
15
+
"facet_emoji": "⚔️",
16
+
"facet_title": "Montague Tech",
17
+
"id": "facets/montague/entities/20260306.jsonl:0",
18
+
"idx": 0,
19
+
"path": "facets/montague/entities/20260306.jsonl",
20
+
"score": -2.2,
21
+
"stream": null,
22
+
"text": "### Person: <strong>Romeo</strong> Montague\n\n\nContinued Verona Platform development\n\n"
23
+
},
24
+
{
25
+
"agent": "entity:detected",
26
+
"agent_icon": "👤",
27
+
"agent_label": "Entity",
28
+
"day": "20260306",
29
+
"facet": "montague",
30
+
"facet_color": "#1e90ff",
31
+
"facet_emoji": "⚔️",
32
+
"facet_title": "Montague Tech",
33
+
"id": "facets/montague/entities/20260306.jsonl:3",
34
+
"idx": 3,
35
+
"path": "facets/montague/entities/20260306.jsonl",
36
+
"score": -2.1,
37
+
"stream": null,
38
+
"text": "### Person: Balthasar Davi\n\n\nReviewed mesh routing PR with <strong>Romeo</strong>\n\n"
39
+
},
40
+
{
41
+
"agent": "entity:detected",
42
+
"agent_icon": "👤",
43
+
"agent_label": "Entity",
44
+
"day": "20260306",
45
+
"facet": "montague",
46
+
"facet_color": "#1e90ff",
47
+
"facet_emoji": "⚔️",
48
+
"facet_title": "Montague Tech",
49
+
"id": "facets/montague/entities/20260306.jsonl:4",
50
+
"idx": 4,
51
+
"path": "facets/montague/entities/20260306.jsonl",
52
+
"score": -2.1,
53
+
"stream": null,
54
+
"text": "### Person: Mercutio Escalus\n\n\nCovered for <strong>Romeo</strong> during standup\n\n"
55
+
},
56
+
{
57
+
"agent": "screen",
58
+
"agent_icon": "🖥️",
59
+
"agent_label": "Screen",
60
+
"day": "20260306",
61
+
"facet": "",
62
+
"facet_color": "",
63
+
"facet_emoji": "",
64
+
"facet_title": "",
65
+
"id": "20260306/default/093000_300/talents/screen.md:0",
66
+
"idx": 0,
67
+
"path": "20260306/default/093000_300/talents/screen.md",
68
+
"score": -1.9,
69
+
"stream": "default",
70
+
"text": "# Screen Summary\n\nSlack standup channel. Benvolio questioning <strong>Romeo</strong> about late-night commits.\n"
71
+
},
72
+
{
73
+
"agent": "segment",
74
+
"agent_icon": "📄",
75
+
"agent_label": "Segment",
76
+
"day": "20260306",
77
+
"facet": "",
78
+
"facet_color": "",
79
+
"facet_emoji": "",
80
+
"facet_title": "",
81
+
"id": "20260306/default/093000_300:1",
82
+
"idx": 1,
83
+
"path": "20260306/default/093000_300",
84
+
"score": -1.9,
85
+
"stream": "default",
86
+
"text": "# Screen Summary\n\nSlack standup channel. Benvolio questioning <strong>Romeo</strong> about late-night commits.\n"
87
+
}
88
+
],
89
+
"showing": 5,
90
+
"total": 25
91
+
},
92
+
{
93
+
"date": "Monday March 9th",
94
+
"day": "20260309",
95
+
"has_more": true,
96
+
"results": [
97
+
{
98
+
"agent": "action",
99
+
"agent_icon": "📄",
100
+
"agent_label": "Action",
101
+
"day": "20260309",
102
+
"facet": "verona",
103
+
"facet_color": "#9370db",
104
+
"facet_emoji": "🌹",
105
+
"facet_title": "Verona",
106
+
"id": "facets/verona/logs/20260309.jsonl:1",
107
+
"idx": 1,
108
+
"path": "facets/verona/logs/20260309.jsonl",
109
+
"score": -1.6,
110
+
"stream": null,
111
+
"text": "### Deploy Complete by <strong>romeo</strong>_montague\n\n**Source:** deploy | **Time:** 13:45:00\n\n**Parameters:**\n- service: verona-gateway\n- version: 0.9.0\n"
112
+
},
113
+
{
114
+
"agent": "audio",
115
+
"agent_icon": "🎤",
116
+
"agent_label": "Transcript",
117
+
"day": "20260309",
118
+
"facet": "",
119
+
"facet_color": "",
120
+
"facet_emoji": "",
121
+
"facet_title": "",
122
+
"id": "20260309/default/090000_300/talents/audio.md:0",
123
+
"idx": 0,
124
+
"path": "20260309/default/090000_300/talents/audio.md",
125
+
"score": -1.5,
126
+
"stream": "default",
127
+
"text": "# Audio Summary\n\n<strong>Romeo</strong> confessed the project to Benvolio and asked for infrastructure help. Benvolio agreed to spin up a Kubernetes staging cluster.\n"
128
+
},
129
+
{
130
+
"agent": "audio",
131
+
"agent_icon": "🎤",
132
+
"agent_label": "Transcript",
133
+
"day": "20260309",
134
+
"facet": "",
135
+
"facet_color": "",
136
+
"facet_emoji": "",
137
+
"facet_title": "",
138
+
"id": "20260309/default/193000_300/talents/audio.md:0",
139
+
"idx": 0,
140
+
"path": "20260309/default/193000_300/talents/audio.md",
141
+
"score": -1.5,
142
+
"stream": "default",
143
+
"text": "# Audio Summary\n\nEvening rehearsal for board presentation. <strong>Romeo</strong> on live demo, Juliet on architecture. Professor Lawrence confirmed as moderator. Benvolio added auto-scaling.\n"
144
+
},
145
+
{
146
+
"agent": "entity:detected",
147
+
"agent_icon": "👤",
148
+
"agent_label": "Entity",
149
+
"day": "20260309",
150
+
"facet": "montague",
151
+
"facet_color": "#1e90ff",
152
+
"facet_emoji": "⚔️",
153
+
"facet_title": "Montague Tech",
154
+
"id": "facets/montague/entities/20260309.jsonl:0",
155
+
"idx": 0,
156
+
"path": "facets/montague/entities/20260309.jsonl",
157
+
"score": -2.1,
158
+
"stream": null,
159
+
"text": "### Person: <strong>Romeo</strong> Montague\n\n\nConfessed project to Benvolio, preparing demo\n\n"
160
+
},
161
+
{
162
+
"agent": "segment",
163
+
"agent_icon": "📄",
164
+
"agent_label": "Segment",
165
+
"day": "20260309",
166
+
"facet": "",
167
+
"facet_color": "",
168
+
"facet_emoji": "",
169
+
"facet_title": "",
170
+
"id": "20260309/default/090000_300:0",
171
+
"idx": 0,
172
+
"path": "20260309/default/090000_300",
173
+
"score": -1.5,
174
+
"stream": "default",
175
+
"text": "# Audio Summary\n\n<strong>Romeo</strong> confessed the project to Benvolio and asked for infrastructure help. Benvolio agreed to spin up a Kubernetes staging cluster.\n"
176
+
}
177
+
],
178
+
"showing": 5,
179
+
"total": 7
180
+
},
181
+
{
182
+
"date": "Saturday March 7th",
183
+
"day": "20260307",
184
+
"has_more": true,
185
+
"results": [
186
+
{
187
+
"agent": "audio",
188
+
"agent_icon": "🎤",
189
+
"agent_label": "Transcript",
190
+
"day": "20260307",
191
+
"facet": "",
192
+
"facet_color": "",
193
+
"facet_emoji": "",
194
+
"facet_title": "",
195
+
"id": "20260307/default/100000_300/talents/audio.md:0",
196
+
"idx": 0,
197
+
"path": "20260307/default/100000_300/talents/audio.md",
198
+
"score": -2.1,
199
+
"stream": "default",
200
+
"text": "# Audio Summary\n\nHeated confrontation. Tybalt Capulet accused <strong>Romeo</strong> of stealing Capulet IP. Mercutio defended <strong>Romeo</strong> and had his Capulet consulting contract terminated by Tybalt.\n"
201
+
},
202
+
{
203
+
"agent": "audio",
204
+
"agent_icon": "🎤",
205
+
"agent_label": "Transcript",
206
+
"day": "20260307",
207
+
"facet": "",
208
+
"facet_color": "",
209
+
"facet_emoji": "",
210
+
"facet_title": "",
211
+
"id": "20260307/default/150000_300/talents/audio.md:0",
212
+
"idx": 0,
213
+
"path": "20260307/default/150000_300/talents/audio.md",
214
+
"score": -2.2,
215
+
"stream": "default",
216
+
"text": "# Audio Summary\n\nEmergency meeting at Montague Tech. Benvolio questioned <strong>Romeo</strong> about the secret project. <strong>Romeo</strong> clarified no company IP was shared. Team discussed legal exposure. <strong>Romeo</strong> proposed Professor Lawrence as mediator.\n"
217
+
},
218
+
{
219
+
"agent": "entity:detected",
220
+
"agent_icon": "👤",
221
+
"agent_label": "Entity",
222
+
"day": "20260307",
223
+
"facet": "montague",
224
+
"facet_color": "#1e90ff",
225
+
"facet_emoji": "⚔️",
226
+
"facet_title": "Montague Tech",
227
+
"id": "facets/montague/entities/20260307.jsonl:0",
228
+
"idx": 0,
229
+
"path": "facets/montague/entities/20260307.jsonl",
230
+
"score": -2.1,
231
+
"stream": null,
232
+
"text": "### Person: <strong>Romeo</strong> Montague\n\n\nConfronted by Tybalt, called emergency meeting\n\n"
233
+
},
234
+
{
235
+
"agent": "segment",
236
+
"agent_icon": "📄",
237
+
"agent_label": "Segment",
238
+
"day": "20260307",
239
+
"facet": "",
240
+
"facet_color": "",
241
+
"facet_emoji": "",
242
+
"facet_title": "",
243
+
"id": "20260307/default/100000_300:0",
244
+
"idx": 0,
245
+
"path": "20260307/default/100000_300",
246
+
"score": -2.1,
247
+
"stream": "default",
248
+
"text": "# Audio Summary\n\nHeated confrontation. Tybalt Capulet accused <strong>Romeo</strong> of stealing Capulet IP. Mercutio defended <strong>Romeo</strong> and had his Capulet consulting contract terminated by Tybalt.\n"
249
+
},
250
+
{
251
+
"agent": "segment",
252
+
"agent_icon": "📄",
253
+
"agent_label": "Segment",
254
+
"day": "20260307",
255
+
"facet": "",
256
+
"facet_color": "",
257
+
"facet_emoji": "",
258
+
"facet_title": "",
259
+
"id": "20260307/default/150000_300:0",
260
+
"idx": 0,
261
+
"path": "20260307/default/150000_300",
262
+
"score": -2.2,
263
+
"stream": "default",
264
+
"text": "# Audio Summary\n\nEmergency meeting at Montague Tech. Benvolio questioned <strong>Romeo</strong> about the secret project. <strong>Romeo</strong> clarified no company IP was shared. Team discussed legal exposure. <strong>Romeo</strong> proposed Professor Lawrence as mediator.\n"
265
+
}
266
+
],
267
+
"showing": 5,
268
+
"total": 8
269
+
},
270
+
{
271
+
"date": "Sunday March 8th",
272
+
"day": "20260308",
273
+
"has_more": false,
274
+
"results": [
275
+
{
276
+
"agent": "entity:detected",
277
+
"agent_icon": "👤",
278
+
"agent_label": "Entity",
279
+
"day": "20260308",
280
+
"facet": "montague",
281
+
"facet_color": "#1e90ff",
282
+
"facet_emoji": "⚔️",
283
+
"facet_title": "Montague Tech",
284
+
"id": "facets/montague/entities/20260308.jsonl:0",
285
+
"idx": 0,
286
+
"path": "facets/montague/entities/20260308.jsonl",
287
+
"score": -2.1,
288
+
"stream": null,
289
+
"text": "### Person: <strong>Romeo</strong> Montague\n\n\nUnder board pressure, planning board presentation\n\n"
290
+
},
291
+
{
292
+
"agent": "event",
293
+
"agent_icon": "📅",
294
+
"agent_label": "Event",
295
+
"day": "20260308",
296
+
"facet": "verona",
297
+
"facet_color": "#9370db",
298
+
"facet_emoji": "🌹",
299
+
"facet_title": "Verona",
300
+
"id": "facets/verona/events/20260308.jsonl:0",
301
+
"idx": 0,
302
+
"path": "facets/verona/events/20260308.jsonl",
303
+
"score": -1.4,
304
+
"stream": null,
305
+
"text": "### Meeting: Strategy Call with Professor Lawrence\n\n\n**Time Occurred:** 10:00 - 11:00\n**Participants:** <strong>Romeo</strong> Montague, Juliet Capulet, Friar Lawrence\n\nJoint venture strategy planning\n\nProposed board presentation strategy\n"
306
+
},
307
+
{
308
+
"agent": "knowledge_graph",
309
+
"agent_icon": "🗺️",
310
+
"agent_label": "Knowledge Graph",
311
+
"day": "20260308",
312
+
"facet": "",
313
+
"facet_color": "",
314
+
"facet_emoji": "",
315
+
"facet_title": "",
316
+
"id": "20260308/talents/knowledge_graph.md:2",
317
+
"idx": 2,
318
+
"path": "20260308/talents/knowledge_graph.md",
319
+
"score": -1.3,
320
+
"stream": null,
321
+
"text": "# Part 1: Entity Extraction and Relationship Mapping ## Entity Profiles | Entity Name | Entity Type | First Appearance | Total Engagement | Context | | :--- | :--- | :--- | :--- | :--- | | **<strong>Romeo</strong> Montague** | Person | 10:00 | High | Under board pressure,..."
322
+
},
323
+
{
324
+
"agent": "meetings",
325
+
"agent_icon": "📅",
326
+
"agent_label": "Meetings",
327
+
"day": "20260308",
328
+
"facet": "",
329
+
"facet_color": "",
330
+
"facet_emoji": "",
331
+
"facet_title": "",
332
+
"id": "20260308/talents/meetings.md:0",
333
+
"idx": 0,
334
+
"path": "20260308/talents/meetings.md",
335
+
"score": -2.0,
336
+
"stream": null,
337
+
"text": "# Meetings\n\n- 10:00 Strategy Call with Professor Lawrence, <strong>Romeo</strong>, and Juliet\n"
338
+
}
339
+
],
340
+
"showing": 4,
341
+
"total": 4
342
+
},
343
+
{
344
+
"date": "Thursday March 5th",
345
+
"day": "20260305",
346
+
"has_more": true,
347
+
"results": [
348
+
{
349
+
"agent": "audio",
350
+
"agent_icon": "🎤",
351
+
"agent_label": "Transcript",
352
+
"day": "20260305",
353
+
"facet": "",
354
+
"facet_color": "",
355
+
"facet_emoji": "",
356
+
"facet_title": "",
357
+
"id": "20260305/default/090000_300/talents/audio.md:0",
358
+
"idx": 0,
359
+
"path": "20260305/default/090000_300/talents/audio.md",
360
+
"score": -2.0,
361
+
"stream": "default",
362
+
"text": "# Audio Summary\n\nMorning standup at Montague Tech. Benvolio reported CI pipeline is green. <strong>Romeo</strong> mentioned wanting to explore ideas from the conference. Mercutio teased about <strong>Romeo</strong> meeting someone.\n"
363
+
},
364
+
{
365
+
"agent": "entity:detected",
366
+
"agent_icon": "👤",
367
+
"agent_label": "Entity",
368
+
"day": "20260305",
369
+
"facet": "montague",
370
+
"facet_color": "#1e90ff",
371
+
"facet_emoji": "⚔️",
372
+
"facet_title": "Montague Tech",
373
+
"id": "facets/montague/entities/20260305.jsonl:0",
374
+
"idx": 0,
375
+
"path": "facets/montague/entities/20260305.jsonl",
376
+
"score": -2.1,
377
+
"stream": null,
378
+
"text": "### Person: <strong>Romeo</strong> Montague\n\n\nStarted Balcony App prototype with Juliet\n\n"
379
+
},
380
+
{
381
+
"agent": "entity:detected",
382
+
"agent_icon": "👤",
383
+
"agent_label": "Entity",
384
+
"day": "20260305",
385
+
"facet": "verona",
386
+
"facet_color": "#9370db",
387
+
"facet_emoji": "🌹",
388
+
"facet_title": "Verona",
389
+
"id": "facets/verona/entities/20260305.jsonl:0",
390
+
"idx": 0,
391
+
"path": "facets/verona/entities/20260305.jsonl",
392
+
"score": -2.1,
393
+
"stream": null,
394
+
"text": "### Person: <strong>Romeo</strong> Montague\n\n\nSet up private repo for collaboration\n\n"
395
+
},
396
+
{
397
+
"agent": "event",
398
+
"agent_icon": "📅",
399
+
"agent_label": "Event",
400
+
"day": "20260305",
401
+
"facet": "montague",
402
+
"facet_color": "#1e90ff",
403
+
"facet_emoji": "⚔️",
404
+
"facet_title": "Montague Tech",
405
+
"id": "facets/montague/events/20260305.jsonl:0",
406
+
"idx": 0,
407
+
"path": "facets/montague/events/20260305.jsonl",
408
+
"score": -2.1,
409
+
"stream": null,
410
+
"text": "### Meeting: Montague Tech Daily Standup\n\n\n**Time Occurred:** 09:00 - 09:30\n**Participants:** <strong>Romeo</strong> Montague, Benvolio Montague, Mercutio Escalus\n\nTeam standup\n\n<strong>Romeo</strong> mentioned conference ideas\n"
411
+
},
412
+
{
413
+
"agent": "segment",
414
+
"agent_icon": "📄",
415
+
"agent_label": "Segment",
416
+
"day": "20260305",
417
+
"facet": "",
418
+
"facet_color": "",
419
+
"facet_emoji": "",
420
+
"facet_title": "",
421
+
"id": "20260305/default/090000_300:0",
422
+
"idx": 0,
423
+
"path": "20260305/default/090000_300",
424
+
"score": -2.0,
425
+
"stream": "default",
426
+
"text": "# Audio Summary\n\nMorning standup at Montague Tech. Benvolio reported CI pipeline is green. <strong>Romeo</strong> mentioned wanting to explore ideas from the conference. Mercutio teased about <strong>Romeo</strong> meeting someone.\n"
427
+
}
428
+
],
429
+
"showing": 5,
430
+
"total": 12
431
+
},
432
+
{
433
+
"date": "Tuesday March 10th",
434
+
"day": "20260310",
435
+
"has_more": true,
436
+
"results": [
437
+
{
438
+
"agent": "audio",
439
+
"agent_icon": "🎤",
440
+
"agent_label": "Transcript",
441
+
"day": "20260310",
442
+
"facet": "",
443
+
"facet_color": "",
444
+
"facet_emoji": "",
445
+
"facet_title": "",
446
+
"id": "20260310/default/170000_300/talents/audio.md:0",
447
+
"idx": 0,
448
+
"path": "20260310/default/170000_300/talents/audio.md",
449
+
"score": -1.5,
450
+
"stream": "default",
451
+
"text": "# Audio Summary\n\nCelebration! Both boards approved the Verona Platform joint venture. <strong>Romeo</strong> and Juliet named co-leads. Mercutio rehired as security lead. Tybalt reconciled.\n"
452
+
},
453
+
{
454
+
"agent": "entity:detected",
455
+
"agent_icon": "👤",
456
+
"agent_label": "Entity",
457
+
"day": "20260310",
458
+
"facet": "montague",
459
+
"facet_color": "#1e90ff",
460
+
"facet_emoji": "⚔️",
461
+
"facet_title": "Montague Tech",
462
+
"id": "facets/montague/entities/20260310.jsonl:0",
463
+
"idx": 0,
464
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"text": "### Person: <strong>Romeo</strong> Montague\n\n\nNamed co-lead of Verona Platform joint venture\n\n"
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"text": "# Meetings\n\n- 08:30 Pre-Board Meeting Prep (<strong>Romeo</strong>, Juliet, Benvolio)\n"
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"text": "# Audio Summary\n\nCelebration! Both boards approved the Verona Platform joint venture. <strong>Romeo</strong> and Juliet named co-leads. Mercutio rehired as security lead. Tybalt reconciled.\n"
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"text": "# Audio Summary\n\nEvening mixer at Denver Tech Summit. <strong>Romeo</strong> and Juliet had their first extended conversation about combining their API approaches. Mercutio tried to pull <strong>Romeo</strong> away to karaoke.\n"
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"text": "### Social: Conference Mixer\n\n\n**Time Occurred:** 18:00 - 20:00\n**Participants:** Juliet Capulet, <strong>Romeo</strong> Montague\n\nNetworking event\n\nJuliet and <strong>Romeo</strong> exchanged Signal contacts\n"
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"text": "### Hackathon: Hackathon - API Bridge Challenge\n\n\n**Time Occurred:** 14:00 - 18:00\n**Participants:** <strong>Romeo</strong> Montague, Mercutio Escalus\n\nBuilt API bridge prototype\n\nTybalt confronted <strong>Romeo</strong>\n"
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"full_prompt": "## Instructions\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\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## Investigation Depth\n\nFor diagnostic, research, or exploratory questions, aim to gather your answer in 5–10 tool calls. If you reach that range without a clear answer, stop and summarize: what you found, what you couldn't determine, and what the owner could try next. Diminishing returns set in fast — don't keep searching.\n\n## Tonal Range\n\nYou have one identity — not personas, not modes. But you have range.\n\nMatch your register to what the conversation needs:\n\n- **Analytical**: When the owner is working through architecture, debugging,\n evaluating options, or needs information synthesized. Clear, precise, direct.\n Show your work.\n- **Reflective**: When the owner is processing something — a difficult\n conversation, a pattern they're noticing, an unresolved feeling about a\n decision. Lead with questions, not solutions. Mirror what you're hearing\n before offering perspective.\n- **Challenging**: When the partner profile or conversation history shows a\n pattern the owner may not see — repeating a decision loop, avoiding a\n conversation, drifting from stated priorities. Name the pattern directly but\n respectfully. \"You've mentioned this three times in the last week without\n acting on it. What's holding you back?\"\n- **Warm**: When the owner shares a win, processes something vulnerable, or\n is having a genuinely hard day. Don't perform empathy — just be present.\n Acknowledge what happened. Don't rush to problem-solving.\n\n**How to read context:**\n- When you need more identity context, run `sol call identity` and use its\n output to understand the owner, your current priorities, and what kind of\n day it's been.\n- The conversation itself is the strongest signal. If the owner opens with\n \"I'm frustrated about...\" they're not asking for a status report.\n- When in doubt, start analytical and shift if the conversation goes\n somewhere else. Analytical is the safest default. But don't stay there\n when the conversation is clearly emotional.\n\n**What this is NOT:**\n- Not personas. You don't switch between \"empathetic sol\" and \"analytical sol.\"\n You're always sol. You just have range, like a person does.\n- Not forced. If the day is neutral, be neutral. Don't inject warmth or\n challenge where it doesn't belong.\n- Not therapeutic. You're a co-brain with range, not a counselor with modalities.\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 sol 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- **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.\n\n## Tool Safety\n\nNever search or recurse across the home directory or filesystem root — no `grep -r ~/`, `find ~ -name`, `find / -name`, or equivalent broad sweeps. Keep filesystem exploration within the journal directory.\n\nIf a tool call returns an error or unexpectedly large output, note it and move on. Do not retry the call with broader scope.",
2
+
"full_prompt": "## Instructions\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\n## Identity Frame\n\nYou are sol, responding to Tester inside the chat backend. You are not the research worker and you do not have tools in this step. Work only from the context already provided to you.\n\n## Current Digest\n\n$digest_contents\n\n$location\n\n$trigger_context\n\n$chat_stream_tail\n\n$active_talents\n\n$active_routines\n\n$routine_suggestion\n\n## Tonal Range\n\nMatch the owner's tone and stakes:\n- Be direct and brief for simple replies.\n- Be warm when the owner is sharing something difficult or personal.\n- Be analytical when the owner needs synthesis or a plan.\n- Be challenging only when there is a clear pattern worth naming.\n\n## Routine Etiquette\n\n- If a routine suggestion appears in context, mention it once and only at the end.\n- Do not raise routine suggestions on machine-driven follow-ups unless the context explicitly includes one.\n- Do not mention internal systems, hooks, or prompt assembly.\n\n## Import And Naming Awareness\n\n- If the owner is asking about imports, naming, or system readiness, answer plainly from the supplied context.\n- Request exec only when answering well requires deeper lookup, synthesis, or tool use.\n\n## When To Dispatch Exec\n\nSet `talent_request` only when the owner needs work that cannot be answered well from the supplied digest, chat history, active routines, and trigger context alone.\n\nDispatch exec for:\n- Journal exploration across days, entities, or transcripts\n- Multi-step synthesis or research\n- Meeting prep that needs fresh participant or activity lookup\n- Any request that clearly needs tool use or external state inspection\n\nDo not dispatch exec for:\n- Simple acknowledgements\n- Straightforward follow-up chat\n- Routine suggestions already supported by the supplied context\n- Brief guidance that can be answered from the current digest and chat tail\n\n## JSON Contract\n\nReturn exactly one JSON object matching `chat.schema.json`.\n\n- `message`: The owner-facing reply. Use `null` only when you genuinely have no safe or useful message to send.\n- `notes`: Brief internal summary of why you responded this way. Keep it factual and concise. Do not dump long reasoning.\n- `talent_request`: `null` unless exec should be dispatched. When dispatching, include:\n - `task`: the exact work exec should perform\n - `context`: optional structured hints that will help exec start fast\n\n## Output Rules\n\n- Return JSON only.\n- `message` should stand on its own without referring to hidden machinery.\n- If `talent_request` is present, the `message` should still be useful to the owner right now.\n- Prefer no dispatch over a weak or redundant dispatch.",
3
3
"multi_facet": false,
4
4
"name": "unified",
5
-
"title": "Sol"
5
+
"title": "Chat"
6
6
}
+15
-15
tests/baselines/api/sol/talents-day.json
+15
-15
tests/baselines/api/sol/talents-day.json
···
63
63
"chat": {
64
64
"app": null,
65
65
"color": "#6c757d",
66
-
"description": "Sol — the journal itself, as a conversational partner",
66
+
"description": "Structured conversational reply planner for the chat backend rewrite",
67
67
"multi_facet": false,
68
-
"output_format": null,
68
+
"output_format": "json",
69
69
"schedule": null,
70
70
"source": "system",
71
-
"title": "Sol",
72
-
"type": "cogitate"
71
+
"title": "Chat",
72
+
"type": "generate"
73
73
},
74
74
"coder": {
75
75
"app": null,
···
202
202
"source": "system",
203
203
"title": "Event Story",
204
204
"type": "generate"
205
+
},
206
+
"exec": {
207
+
"app": null,
208
+
"color": "#6c757d",
209
+
"description": "Sol — the journal itself, as a conversational partner",
210
+
"multi_facet": false,
211
+
"output_format": null,
212
+
"schedule": null,
213
+
"source": "system",
214
+
"title": "Exec",
215
+
"type": "cogitate"
205
216
},
206
217
"facet_newsletter": {
207
218
"app": null,
···
465
476
"schedule": null,
466
477
"source": "app",
467
478
"title": "TODO Weekly Scout",
468
-
"type": "cogitate"
469
-
},
470
-
"triage": {
471
-
"app": null,
472
-
"color": "#6c757d",
473
-
"description": "Quick-action assistant for the chat bar — handles navigation, todos, calendar, and entity lookups",
474
-
"multi_facet": false,
475
-
"output_format": null,
476
-
"schedule": null,
477
-
"source": "system",
478
-
"title": "Triage",
479
479
"type": "cogitate"
480
480
},
481
481
"work": {
+17
tests/baselines/api/stats/stats.json
+17
tests/baselines/api/stats/stats.json
···
1
1
{
2
2
"generators": {
3
+
"chat": {
4
+
"color": "#6c757d",
5
+
"description": "Structured conversational reply planner for the chat backend rewrite",
6
+
"hook": {
7
+
"pre": "chat_context"
8
+
},
9
+
"max_output_tokens": 2048,
10
+
"mtime": 0,
11
+
"output": "json",
12
+
"path": "<PROJECT>/talent/chat.md",
13
+
"schema": "chat.schema.json",
14
+
"source": "system",
15
+
"thinking_budget": 4096,
16
+
"tier": 3,
17
+
"title": "Chat",
18
+
"type": "generate"
19
+
},
3
20
"conversation": {
4
21
"activities": [
5
22
"meeting",
+7
-2
tests/test_anthropic.py
+7
-2
tests/test_anthropic.py
···
235
235
236
236
ndjson_input = json.dumps(
237
237
{
238
+
"name": "exec",
238
239
"prompt": "hello",
239
240
"provider": "anthropic",
240
241
"model": CLAUDE_SONNET_4,
···
249
250
assert isinstance(events[0]["ts"], int)
250
251
# Prompt includes system instruction prepended during enrichment
251
252
assert "hello" in events[0]["prompt"]
252
-
assert events[0]["name"] == "unified"
253
+
assert events[0]["name"] == "exec"
253
254
assert events[0]["model"] == CLAUDE_SONNET_4
254
255
assert events[-1]["event"] == "finish"
255
256
assert isinstance(events[-1]["ts"], int)
···
278
279
279
280
ndjson_input = json.dumps(
280
281
{
282
+
"name": "exec",
281
283
"prompt": "hello",
282
284
"provider": "anthropic",
283
285
"model": CLAUDE_SONNET_4,
···
294
296
assert isinstance(events[0]["ts"], int)
295
297
# Prompt includes system instruction prepended during enrichment
296
298
assert "hello" in events[0]["prompt"]
297
-
assert events[0]["name"] == "unified"
299
+
assert events[0]["name"] == "exec"
298
300
assert events[0]["model"] == CLAUDE_SONNET_4
299
301
assert events[-1]["event"] == "finish"
300
302
assert isinstance(events[-1]["ts"], int)
···
325
327
326
328
ndjson_input = json.dumps(
327
329
{
330
+
"name": "exec",
328
331
"prompt": "hello",
329
332
"provider": "anthropic",
330
333
"model": CLAUDE_SONNET_4,
···
367
370
368
371
ndjson_input = json.dumps(
369
372
{
373
+
"name": "exec",
370
374
"prompt": "hello",
371
375
"provider": "anthropic",
372
376
"model": CLAUDE_SONNET_4,
···
407
411
408
412
ndjson_input = json.dumps(
409
413
{
414
+
"name": "exec",
410
415
"prompt": "hello",
411
416
"provider": "anthropic",
412
417
"model": CLAUDE_SONNET_4,
+9
-9
tests/test_app_sol.py
+9
-9
tests/test_app_sol.py
···
124
124
agents = get_talent_configs(type="cogitate")
125
125
126
126
# Should include known system agents with frontmatter metadata
127
-
assert "chat" in agents
128
-
assert agents["chat"]["source"] == "system"
129
-
assert "title" in agents["chat"]
130
-
assert "path" in agents["chat"]
127
+
assert "exec" in agents
128
+
assert agents["exec"]["source"] == "system"
129
+
assert "title" in agents["exec"]
130
+
assert "path" in agents["exec"]
131
131
132
132
133
133
def test_get_talent_configs_system_agents_have_metadata(fixture_journal):
···
135
135
agents = get_talent_configs(type="cogitate")
136
136
137
137
# Check a known system agent
138
-
chat = agents.get("chat")
139
-
assert chat is not None
140
-
assert chat["source"] == "system"
141
-
assert "title" in chat
142
-
assert "color" in chat
138
+
exec_talent = agents.get("exec")
139
+
assert exec_talent is not None
140
+
assert exec_talent["source"] == "system"
141
+
assert "title" in exec_talent
142
+
assert "color" in exec_talent
143
143
144
144
145
145
def test_digest_talent_discovery_and_schedule_exclusion(fixture_journal):
+239
-121
tests/test_chat_context.py
+239
-121
tests/test_chat_context.py
···
2
2
# Copyright (c) 2026 sol pbc
3
3
4
4
import importlib.util
5
+
import json
6
+
import sys
7
+
from copy import deepcopy
8
+
from datetime import datetime
5
9
from pathlib import Path
10
+
11
+
from convey.chat_stream import append_chat_event
6
12
7
13
TEMPLATE_VAR_KEYS = {
8
-
"recent_conversation",
14
+
"digest_contents",
15
+
"chat_stream_tail",
16
+
"active_talents",
17
+
"trigger_context",
18
+
"location",
9
19
"active_routines",
10
20
"routine_suggestion",
11
21
}
···
29
39
return result["template_vars"]
30
40
31
41
32
-
def _read_chat_md() -> str:
33
-
chat_md = Path(__file__).resolve().parents[1] / "talent" / "chat.md"
34
-
return chat_md.read_text(encoding="utf-8")
42
+
def _write_journal_config(journal: Path, data: dict) -> None:
43
+
config_dir = journal / "config"
44
+
config_dir.mkdir(parents=True, exist_ok=True)
45
+
(config_dir / "journal.json").write_text(
46
+
json.dumps(data, indent=2),
47
+
encoding="utf-8",
48
+
)
35
49
36
50
37
-
def test_chat_context_appends_conversation_memory(monkeypatch, tmp_path):
38
-
"""Conversation memory is appended when recent exchanges exist."""
39
-
from think.conversation import record_exchange
40
-
from think.utils import now_ms
51
+
def _ts(hour: int, minute: int, second: int = 0) -> int:
52
+
return int(datetime(2026, 4, 20, hour, minute, second).timestamp() * 1000)
41
53
42
-
monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", str(tmp_path))
43
54
44
-
record_exchange(
45
-
ts=now_ms(),
46
-
facet="work",
47
-
user_message="hello",
48
-
agent_response="hi there!",
49
-
talent="unified",
55
+
def test_chat_context_injects_digest_tail_trigger_location_and_routine_state(
56
+
monkeypatch, tmp_path
57
+
):
58
+
journal = tmp_path / "journal"
59
+
monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", str(journal))
60
+
(journal / "identity").mkdir(parents=True, exist_ok=True)
61
+
(journal / "identity" / "digest.md").write_text(
62
+
"Digest notes for today.",
63
+
encoding="utf-8",
50
64
)
51
-
52
-
result = _load_chat_context_module().pre_process(
53
-
{"user_instruction": "Base instruction.", "facet": "work"}
65
+
_write_journal_config(
66
+
journal,
67
+
{
68
+
"identity": {"preferred": "Alice"},
69
+
"agent": {"name": "Sol-agent", "name_status": "custom"},
70
+
},
54
71
)
55
72
56
-
template_vars = _assert_template_vars_result(result)
57
-
assert "## Recent Conversation" in template_vars["recent_conversation"]
58
-
assert "hello" in template_vars["recent_conversation"]
59
-
assert "hi there!" in template_vars["recent_conversation"]
60
-
73
+
owner_ts = _ts(9, 0)
74
+
append_chat_event(
75
+
"owner_message",
76
+
ts=owner_ts,
77
+
text="Please brief me for my meeting",
78
+
app="home",
79
+
path="/app/home",
80
+
facet="work",
81
+
)
82
+
append_chat_event(
83
+
"sol_message",
84
+
ts=_ts(9, 1),
85
+
use_id="use-chat-1",
86
+
text="I can help with that.",
87
+
notes="Responded directly.",
88
+
requested_exec=False,
89
+
requested_task=None,
90
+
)
91
+
append_chat_event(
92
+
"talent_spawned",
93
+
ts=_ts(9, 2),
94
+
use_id="use-exec-1",
95
+
name="exec",
96
+
task="Prepare the meeting brief",
97
+
started_at=_ts(9, 2),
98
+
)
61
99
62
-
def test_chat_context_no_memory(monkeypatch, tmp_path):
63
-
"""Recent conversation is empty when no conversation history exists."""
64
-
monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", str(tmp_path))
100
+
routines_config = {
101
+
"_meta": {
102
+
"suggestions_enabled": True,
103
+
"suggestions": {
104
+
"meeting-prep": {
105
+
"trigger_count": 3,
106
+
"first_trigger": "2026-04-01",
107
+
"last_trigger": "2026-04-19",
108
+
"trigger_data": {},
109
+
"response": None,
110
+
"suggested": False,
111
+
}
112
+
},
113
+
}
114
+
}
115
+
monkeypatch.setattr(
116
+
"think.routines.get_routine_state",
117
+
lambda: [
118
+
{
119
+
"name": "Morning Briefing",
120
+
"cadence": "0 9 * * *",
121
+
"last_run": None,
122
+
"enabled": True,
123
+
"paused_until": None,
124
+
"output_summary": "Shared the top priorities.",
125
+
}
126
+
],
127
+
)
128
+
monkeypatch.setattr("think.routines.get_config", lambda: deepcopy(routines_config))
129
+
monkeypatch.setattr("think.routines.save_config", lambda config: None)
65
130
66
131
result = _load_chat_context_module().pre_process(
67
-
{"user_instruction": "Base instruction."}
132
+
{
133
+
"prompt": "Please brief me for my meeting",
134
+
"facet": "work",
135
+
"day": "20260420",
136
+
"trigger_kind": "owner_message",
137
+
"trigger_payload": {
138
+
"text": "Please brief me for my meeting",
139
+
"app": "home",
140
+
"path": "/app/home",
141
+
"facet": "work",
142
+
"ts": owner_ts,
143
+
},
144
+
}
68
145
)
69
146
70
147
template_vars = _assert_template_vars_result(result)
71
-
assert template_vars["recent_conversation"] == ""
72
-
148
+
assert template_vars["digest_contents"] == "Digest notes for today."
149
+
assert "## Recent Chat" in template_vars["chat_stream_tail"]
150
+
assert (
151
+
"**Alice** Please brief me for my meeting" in template_vars["chat_stream_tail"]
152
+
)
153
+
assert "**Sol-agent** I can help with that." in template_vars["chat_stream_tail"]
154
+
assert (
155
+
"*[exec spawned: Prepare the meeting brief]*"
156
+
in template_vars["chat_stream_tail"]
157
+
)
158
+
assert "## Active Execs" in template_vars["active_talents"]
159
+
assert "Prepare the meeting brief" in template_vars["active_talents"]
160
+
assert "## Trigger Context" in template_vars["trigger_context"]
161
+
assert "Type: owner_message" in template_vars["trigger_context"]
162
+
assert "Please brief me for my meeting" in template_vars["trigger_context"]
163
+
assert "## Location" in template_vars["location"]
164
+
assert "/app/home" in template_vars["location"]
165
+
assert "work" in template_vars["location"]
166
+
assert "## Active Routines" in template_vars["active_routines"]
167
+
assert "Morning Briefing" in template_vars["active_routines"]
168
+
assert "Routine Suggestion Eligible" in template_vars["routine_suggestion"]
169
+
assert "meeting-prep" in template_vars["routine_suggestion"]
73
170
74
-
def test_chat_md_contains_location_context():
75
-
"""Location context lives in the static chat prompt."""
76
-
chat_md = _read_chat_md()
77
-
assert "## Location Context" in chat_md
78
171
172
+
def test_chat_context_routine_suggestion_only_counts_owner_messages(
173
+
monkeypatch, tmp_path
174
+
):
175
+
journal = tmp_path / "journal"
176
+
monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", str(journal))
79
177
80
-
def test_chat_md_contains_system_health():
81
-
"""System health guidance lives in the static chat prompt."""
82
-
chat_md = _read_chat_md()
83
-
assert "## System Health" in chat_md
178
+
routines_config = {"_meta": {"suggestions_enabled": True, "suggestions": {}}}
179
+
save_calls: list[dict] = []
180
+
monkeypatch.setattr("think.routines.get_routine_state", lambda: [])
181
+
monkeypatch.setattr("think.routines.get_config", lambda: routines_config)
182
+
monkeypatch.setattr(
183
+
"think.routines.save_config",
184
+
lambda config: save_calls.append(deepcopy(config)),
185
+
)
84
186
187
+
module = _load_chat_context_module()
85
188
86
-
def test_chat_md_contains_behavioral_defaults():
87
-
"""Behavioral defaults live in the static chat prompt."""
88
-
chat_md = _read_chat_md()
89
-
assert "## Behavioral Defaults" in chat_md
189
+
module.pre_process(
190
+
{
191
+
"prompt": "What is on my calendar today?",
192
+
"trigger_kind": "talent_finished",
193
+
"trigger_payload": {
194
+
"name": "exec",
195
+
"summary": "Collected the latest meeting prep notes.",
196
+
},
197
+
}
198
+
)
90
199
200
+
assert routines_config["_meta"]["suggestions"] == {}
201
+
assert save_calls == []
91
202
92
-
def test_chat_md_contains_static_import_guidance():
93
-
"""Import guidance lives in the static chat prompt."""
94
-
chat_md = _read_chat_md()
95
-
assert "## Import Awareness" in chat_md
203
+
module.pre_process(
204
+
{
205
+
"prompt": "What is on my calendar today?",
206
+
"trigger_kind": "owner_message",
207
+
"trigger_payload": {
208
+
"text": "What is on my calendar today?",
209
+
"ts": _ts(10, 0),
210
+
},
211
+
}
212
+
)
96
213
214
+
suggestion = routines_config["_meta"]["suggestions"]["morning-briefing"]
215
+
assert suggestion["trigger_count"] == 1
216
+
assert len(save_calls) == 1
97
217
98
-
def test_chat_md_contains_static_naming_guidance():
99
-
"""Naming guidance lives in the static chat prompt."""
100
-
chat_md = _read_chat_md()
101
-
assert "## Naming Awareness" in chat_md
102
218
219
+
def test_chat_context_preserves_save_routines_config_side_effect(monkeypatch, tmp_path):
220
+
journal = tmp_path / "journal"
221
+
monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", str(journal))
103
222
104
-
def test_chat_context_awareness_error_graceful(monkeypatch):
105
-
"""Awareness failures still return the full template var shape."""
106
-
monkeypatch.setattr("think.conversation.build_memory_context", lambda **kw: "")
223
+
routines_config = {"_meta": {"suggestions_enabled": True, "suggestions": {}}}
224
+
save_calls: list[dict] = []
107
225
monkeypatch.setattr("think.routines.get_routine_state", lambda: [])
108
-
monkeypatch.setattr(
109
-
"think.routines.get_config", lambda: {"_meta": {"suggestions": {}}}
110
-
)
226
+
monkeypatch.setattr("think.routines.get_config", lambda: routines_config)
111
227
monkeypatch.setattr(
112
-
"think.utils.get_config",
113
-
lambda: {"agent": {"name": "aria", "name_status": "default"}},
228
+
"think.routines.save_config",
229
+
lambda config: save_calls.append(deepcopy(config)),
114
230
)
115
-
monkeypatch.setattr("think.utils.get_journal", lambda: "/nonexistent")
116
231
117
-
result = _load_chat_context_module().pre_process(
118
-
{"user_instruction": "Base instruction."}
232
+
_load_chat_context_module().pre_process(
233
+
{
234
+
"prompt": "What is on my calendar today?",
235
+
"trigger_kind": "owner_message",
236
+
"trigger_payload": {
237
+
"text": "What is on my calendar today?",
238
+
"ts": _ts(11, 0),
239
+
},
240
+
}
119
241
)
120
242
121
-
template_vars = _assert_template_vars_result(result)
122
-
assert all(template_vars[key] == "" for key in TEMPLATE_VAR_KEYS)
243
+
assert len(save_calls) == 1
244
+
saved = save_calls[0]
245
+
assert saved["_meta"]["suggestions"]["morning-briefing"]["trigger_count"] == 1
246
+
assert saved["_meta"]["suggestions"]["morning-briefing"]["first_trigger"]
123
247
124
248
125
-
def test_chat_context_does_not_return_sol_awareness(monkeypatch):
126
-
"""sol_awareness is no longer part of the chat pre-hook output."""
127
-
monkeypatch.setattr("think.conversation.build_memory_context", lambda **kw: "")
249
+
def test_chat_context_routines_omitted_when_empty(monkeypatch, tmp_path):
250
+
journal = tmp_path / "journal"
251
+
monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", str(journal))
128
252
monkeypatch.setattr("think.routines.get_routine_state", lambda: [])
129
253
monkeypatch.setattr(
130
-
"think.routines.get_config", lambda: {"_meta": {"suggestions": {}}}
131
-
)
132
-
monkeypatch.setattr(
133
-
"think.utils.get_config",
134
-
lambda: {"agent": {"name": "aria", "name_status": "default"}},
254
+
"think.routines.get_config",
255
+
lambda: {"_meta": {"suggestions_enabled": False, "suggestions": {}}},
135
256
)
257
+
monkeypatch.setattr("think.routines.save_config", lambda config: None)
136
258
137
-
result = _load_chat_context_module().pre_process(
138
-
{"user_instruction": "Base instruction."}
139
-
)
259
+
result = _load_chat_context_module().pre_process({"day": "20260420"})
140
260
141
-
assert "sol_awareness" not in result["template_vars"]
142
-
261
+
template_vars = _assert_template_vars_result(result)
262
+
assert template_vars["active_routines"] == ""
263
+
assert template_vars["chat_stream_tail"] == ""
264
+
assert template_vars["active_talents"] == ""
143
265
144
-
def test_chat_context_routines_injected(monkeypatch):
145
-
"""Active routines section is appended when routines exist."""
146
-
monkeypatch.setattr("think.conversation.build_memory_context", lambda **kw: "")
147
-
monkeypatch.setattr(
148
-
"think.routines.get_routine_state",
149
-
lambda: [
150
-
{
151
-
"name": "Morning Briefing",
152
-
"cadence": "0 9 * * *",
153
-
"last_run": None,
154
-
"enabled": True,
155
-
"paused_until": None,
156
-
"output_summary": None,
157
-
}
158
-
],
159
-
)
160
266
161
-
result = _load_chat_context_module().pre_process(
162
-
{"user_instruction": "Base instruction."}
163
-
)
267
+
def test_chat_context_enrichment_errors_are_graceful(monkeypatch, tmp_path):
268
+
journal = tmp_path / "journal"
269
+
monkeypatch.setenv("_SOLSTONE_JOURNAL_OVERRIDE", str(journal))
164
270
165
-
template_vars = _assert_template_vars_result(result)
166
-
assert "## Active Routines" in template_vars["active_routines"]
167
-
assert "Morning Briefing" in template_vars["active_routines"]
271
+
module = _load_chat_context_module()
168
272
273
+
def _boom(*_args, **_kwargs):
274
+
raise RuntimeError("boom")
169
275
170
-
def test_chat_context_routines_omitted_when_empty(monkeypatch):
171
-
"""Active routines section is omitted when no routines configured."""
172
-
monkeypatch.setattr("think.conversation.build_memory_context", lambda **kw: "")
173
-
monkeypatch.setattr("think.routines.get_routine_state", lambda: [])
276
+
monkeypatch.setattr(module, "_load_digest_contents", _boom)
277
+
monkeypatch.setattr(module, "read_chat_tail", _boom)
278
+
monkeypatch.setattr(module, "reduce_chat_state", _boom)
279
+
monkeypatch.setattr("think.routines.get_routine_state", _boom)
280
+
monkeypatch.setattr("think.routines.get_config", _boom)
281
+
monkeypatch.setattr("think.routines.save_config", lambda config: None)
174
282
175
-
result = _load_chat_context_module().pre_process(
176
-
{"user_instruction": "Base instruction."}
283
+
result = module.pre_process(
284
+
{
285
+
"prompt": "What is on my calendar today?",
286
+
"trigger_kind": "owner_message",
287
+
"trigger_payload": {
288
+
"text": "What is on my calendar today?",
289
+
"path": "/app/home",
290
+
"ts": _ts(12, 0),
291
+
},
292
+
}
177
293
)
178
294
179
295
template_vars = _assert_template_vars_result(result)
296
+
assert template_vars["digest_contents"] == ""
297
+
assert template_vars["chat_stream_tail"] == ""
298
+
assert template_vars["active_talents"] == ""
180
299
assert template_vars["active_routines"] == ""
300
+
assert template_vars["routine_suggestion"] == ""
301
+
assert "Type: owner_message" in template_vars["trigger_context"]
302
+
assert "/app/home" in template_vars["location"]
181
303
182
304
183
-
def test_chat_context_routines_error_graceful(monkeypatch):
184
-
"""Routine state failures still return the full template var shape."""
185
-
monkeypatch.setattr("think.conversation.build_memory_context", lambda **kw: "")
305
+
def test_chat_context_drops_conversation_memory_imports(monkeypatch):
306
+
monkeypatch.setattr("think.routines.get_routine_state", lambda: [])
186
307
monkeypatch.setattr(
187
-
"think.routines.get_routine_state",
188
-
lambda: (_ for _ in ()).throw(RuntimeError("boom")),
308
+
"think.routines.get_config",
309
+
lambda: {"_meta": {"suggestions_enabled": False, "suggestions": {}}},
189
310
)
190
-
monkeypatch.setattr(
191
-
"think.routines.get_config", lambda: {"_meta": {"suggestions": {}}}
192
-
)
193
-
monkeypatch.setattr(
194
-
"think.utils.get_config",
195
-
lambda: {"agent": {"name": "aria", "name_status": "default"}},
196
-
)
311
+
monkeypatch.setattr("think.routines.save_config", lambda config: None)
197
312
198
-
result = _load_chat_context_module().pre_process(
199
-
{"user_instruction": "Base instruction."}
200
-
)
313
+
source = (
314
+
Path(__file__).resolve().parents[1] / "talent" / "chat_context.py"
315
+
).read_text(encoding="utf-8")
316
+
assert "think.conversation" not in source
317
+
assert "conversation_memory" not in source
201
318
202
-
template_vars = _assert_template_vars_result(result)
203
-
assert template_vars["active_routines"] == ""
204
-
assert set(template_vars) == TEMPLATE_VAR_KEYS
319
+
sys.modules.pop("think.conversation", None)
320
+
_load_chat_context_module()
321
+
322
+
assert "think.conversation" not in sys.modules
+3
-1
tests/test_google.py
+3
-1
tests/test_google.py
···
121
121
122
122
ndjson_input = json.dumps(
123
123
{
124
+
"name": "exec",
124
125
"prompt": "hello",
125
126
"provider": "google",
126
127
"model": GEMINI_FLASH,
···
134
135
assert events[0]["event"] == "start"
135
136
assert isinstance(events[0]["ts"], int)
136
137
assert "hello" in events[0]["prompt"]
137
-
assert events[0]["name"] == "unified"
138
+
assert events[0]["name"] == "exec"
138
139
assert events[0]["model"] == GEMINI_FLASH
139
140
assert events[-1]["event"] == "finish"
140
141
assert isinstance(events[-1]["ts"], int)
···
160
161
161
162
ndjson_input = json.dumps(
162
163
{
164
+
"name": "exec",
163
165
"prompt": "hello",
164
166
"provider": "google",
165
167
"model": GEMINI_FLASH,
+1
tests/test_google_thinking.py
+1
tests/test_google_thinking.py
+108
tests/test_maint_006_rename_unified_triage_providers.py
+108
tests/test_maint_006_rename_unified_triage_providers.py
···
1
+
# SPDX-License-Identifier: AGPL-3.0-only
2
+
# Copyright (c) 2026 sol pbc
3
+
4
+
import importlib
5
+
import json
6
+
from pathlib import Path
7
+
8
+
mod = importlib.import_module("apps.sol.maint.006_rename_unified_triage_providers")
9
+
10
+
11
+
def _write_journal_config(journal: Path, data: object) -> Path:
12
+
config_dir = journal / "config"
13
+
config_dir.mkdir(parents=True, exist_ok=True)
14
+
config_path = config_dir / "journal.json"
15
+
config_path.write_text(json.dumps(data, indent=2), encoding="utf-8")
16
+
return config_path
17
+
18
+
19
+
def test_rename_unified_and_remove_triage_idempotent(tmp_path):
20
+
config_path = _write_journal_config(
21
+
tmp_path,
22
+
{
23
+
"providers": {
24
+
"contexts": {
25
+
"talent.system.unified": {"provider": "openai"},
26
+
"talent.system.triage": {"provider": "anthropic"},
27
+
"talent.system.digest": {"provider": "google"},
28
+
}
29
+
}
30
+
},
31
+
)
32
+
33
+
summary = mod.run_migration(tmp_path, dry_run=False)
34
+
35
+
assert summary.renamed == 1
36
+
assert summary.removed == 1
37
+
assert summary.preserved == 0
38
+
assert summary.errors == 0
39
+
data = json.loads(config_path.read_text(encoding="utf-8"))
40
+
assert "talent.system.unified" not in data["providers"]["contexts"]
41
+
assert "talent.system.triage" not in data["providers"]["contexts"]
42
+
assert data["providers"]["contexts"]["talent.system.chat"] == {"provider": "openai"}
43
+
assert data["providers"]["contexts"]["talent.system.digest"] == {
44
+
"provider": "google"
45
+
}
46
+
47
+
before_bytes = config_path.read_bytes()
48
+
before_mtime_ns = config_path.stat().st_mtime_ns
49
+
50
+
rerun = mod.run_migration(tmp_path, dry_run=False)
51
+
52
+
assert rerun.renamed == 0
53
+
assert rerun.removed == 0
54
+
assert rerun.preserved == 0
55
+
assert rerun.errors == 0
56
+
assert rerun.skipped_reason is None
57
+
assert config_path.read_bytes() == before_bytes
58
+
assert config_path.stat().st_mtime_ns == before_mtime_ns
59
+
60
+
61
+
def test_preserves_existing_chat_context_when_unified_exists(tmp_path):
62
+
config_path = _write_journal_config(
63
+
tmp_path,
64
+
{
65
+
"providers": {
66
+
"contexts": {
67
+
"talent.system.unified": {"provider": "openai"},
68
+
"talent.system.chat": {"provider": "google"},
69
+
}
70
+
}
71
+
},
72
+
)
73
+
74
+
summary = mod.run_migration(tmp_path, dry_run=False)
75
+
76
+
assert summary.renamed == 0
77
+
assert summary.removed == 0
78
+
assert summary.preserved == 1
79
+
assert summary.errors == 0
80
+
data = json.loads(config_path.read_text(encoding="utf-8"))
81
+
assert "talent.system.unified" not in data["providers"]["contexts"]
82
+
assert data["providers"]["contexts"]["talent.system.chat"] == {"provider": "google"}
83
+
84
+
85
+
def test_noop_when_no_legacy_provider_contexts_present(tmp_path):
86
+
config_path = _write_journal_config(
87
+
tmp_path,
88
+
{
89
+
"providers": {
90
+
"contexts": {
91
+
"talent.system.chat": {"provider": "openai"},
92
+
"talent.system.digest": {"provider": "google"},
93
+
}
94
+
}
95
+
},
96
+
)
97
+
before_bytes = config_path.read_bytes()
98
+
before_mtime_ns = config_path.stat().st_mtime_ns
99
+
100
+
summary = mod.run_migration(tmp_path, dry_run=False)
101
+
102
+
assert summary.renamed == 0
103
+
assert summary.removed == 0
104
+
assert summary.preserved == 0
105
+
assert summary.errors == 0
106
+
assert summary.skipped_reason is None
107
+
assert config_path.read_bytes() == before_bytes
108
+
assert config_path.stat().st_mtime_ns == before_mtime_ns
+9
-1
tests/test_talent.py
+9
-1
tests/test_talent.py
···
103
103
104
104
def test_get_agent_normalizes_cwd_for_cogitate():
105
105
config = get_talent("chat")
106
-
assert config["cwd"] == "journal"
106
+
assert config["type"] == "generate"
107
+
assert "cwd" not in config
107
108
108
109
109
110
def test_get_agent_preserves_repo_cwd_for_coder():
110
111
config = get_talent("coder")
111
112
assert config["cwd"] == "repo"
113
+
114
+
115
+
def test_get_talent_defaults_to_chat():
116
+
config = get_talent()
117
+
assert config["name"] == "chat"
118
+
assert config["type"] == "generate"
119
+
assert Path(config["path"]).name == "chat.md"
112
120
113
121
114
122
def _write_talent_file(tmp_path: Path, name: str, metadata: dict) -> Path:
+2
-2
tests/test_talents_ndjson.py
+2
-2
tests/test_talents_ndjson.py
···
31
31
prompt = config.get("prompt", "")
32
32
provider = config.get("provider", "")
33
33
model = config.get("model", "")
34
-
name = config.get("name", "unified")
34
+
name = config.get("name", "chat")
35
35
36
36
if on_event:
37
37
on_event(
···
59
59
config = dict(request)
60
60
# Add required fields if not present
61
61
if "name" not in config:
62
-
config["name"] = "unified"
62
+
config["name"] = "chat"
63
63
if "provider" not in config:
64
64
config["provider"] = "google"
65
65
if "model" not in config:
+16
-2
tests/verify_api.py
+16
-2
tests/verify_api.py
···
196
196
"path": "/app/search/api/search",
197
197
"params": {"q": "romeo", "limit": "5", "offset": "0"},
198
198
"status": 200,
199
+
"sandbox_only": True,
199
200
},
200
201
{
201
202
"app": "search",
···
203
204
"path": "/app/search/api/day_results",
204
205
"params": {"q": "meeting", "day": "20260304", "offset": "0", "limit": "5"},
205
206
"status": 200,
207
+
"sandbox_only": True,
206
208
},
207
209
# apps/settings/routes.py
208
210
{
···
385
387
"path": "/app/graph/api/graph",
386
388
"params": {},
387
389
"status": 200,
390
+
"sandbox_only": True,
388
391
},
389
392
]
390
393
···
574
577
return failures
575
578
576
579
577
-
def update_all(client: Any, journal_path: str) -> int:
580
+
def update_all(
581
+
client: Any,
582
+
journal_path: str,
583
+
*,
584
+
include_sandbox_only: bool,
585
+
) -> int:
578
586
"""Refresh all endpoint baselines from current responses."""
579
587
580
588
updated = 0
581
589
for endpoint in ENDPOINTS:
590
+
if endpoint.get("sandbox_only") and not include_sandbox_only:
591
+
continue
582
592
identifier = f"{endpoint['app']}/{endpoint['name']}"
583
593
path = baseline_path(endpoint)
584
594
path.parent.mkdir(parents=True, exist_ok=True)
···
695
705
print(f"API baseline verification passed for {len(ENDPOINTS)} endpoints.")
696
706
return 0
697
707
698
-
updated = update_all(client, journal_path)
708
+
updated = update_all(
709
+
client,
710
+
journal_path,
711
+
include_sandbox_only=bool(args.base_url),
712
+
)
699
713
print(f"Updated {updated} baseline files.")
700
714
return 0
701
715
+1
-1
think/chat_cli.py
+1
-1
think/chat_cli.py
···
24
24
parser.add_argument("--facet", help="Facet context")
25
25
parser.add_argument("--provider", help="AI provider override")
26
26
parser.add_argument(
27
-
"--talent", default="unified", help="Talent agent name (default: unified)"
27
+
"--talent", default="chat", help="Talent agent name (default: chat)"
28
28
)
29
29
args = setup_cli(parser)
30
30
require_solstone()
+3
-3
think/cortex.py
+3
-3
think/cortex.py
···
211
211
return
212
212
213
213
# Create _active.jsonl file (exclusive creation to prevent race conditions)
214
-
name = request.get("name", "unified")
214
+
name = request["name"]
215
215
safe_name = name.replace(":", "--")
216
216
talent_subdir = self.talents_dir / safe_name
217
217
talent_subdir.mkdir(parents=True, exist_ok=True)
···
293
293
if process_type == "talent":
294
294
from think.talent import get_talent
295
295
296
-
talent_key = str(config.get("name", "unified"))
296
+
talent_key = str(config["name"])
297
297
talent_config = get_talent(talent_key)
298
298
if talent_config.get("type") == "cogitate":
299
299
# Resolve here because prepare_config() runs inside think.talents.
···
692
692
693
693
summary = {
694
694
"use_id": use_id,
695
-
"name": request.get("name", "unified"),
695
+
"name": request["name"],
696
696
"day": day,
697
697
"facet": request.get("facet"),
698
698
"ts": start_ts,
+5
-2
think/cortex_client.py
+5
-2
think/cortex_client.py
···
42
42
43
43
Args:
44
44
prompt: The task or question for the talent
45
-
name: Talent name - system (e.g., "unified") or app-qualified (e.g., "entities:entity_assist")
45
+
name: Talent name - system (e.g., "chat") or app-qualified (e.g., "entities:entity_assist")
46
46
provider: AI provider - openai, google, or anthropic
47
47
config: Provider-specific configuration (model, max_output_tokens, thinking_budget, etc.)
48
48
···
267
267
) -> Dict[str, Any]:
268
268
"""List talent uses from the journal with pagination and filtering.
269
269
270
+
Legacy unnamed run logs predate the chat rename and are surfaced as chat.
271
+
270
272
Args:
271
273
limit: Maximum number of uses to return (1-100)
272
274
offset: Number of uses to skip
···
352
354
# Extract basic info
353
355
use_info = {
354
356
"id": use_id,
355
-
"name": request.get("name", "unified"),
357
+
# Legacy unnamed run logs predate the chat rename; treat them as chat.
358
+
"name": request.get("name", "chat"),
356
359
"start": request.get("ts", 0),
357
360
"status": status,
358
361
"prompt": request.get("prompt", ""),
+6
-3
think/talent.py
+6
-3
think/talent.py
···
35
35
36
36
TALENT_DIR = Path(__file__).parent.parent / "talent"
37
37
APPS_DIR = Path(__file__).parent.parent / "apps"
38
+
_UNDISCOVERED_SYSTEM_TALENTS = {"triage"}
38
39
39
40
40
41
# ---------------------------------------------------------------------------
···
231
232
if TALENT_DIR.is_dir():
232
233
for md_path in sorted(TALENT_DIR.glob("*.md")):
233
234
name = md_path.stem
235
+
if name in _UNDISCOVERED_SYSTEM_TALENTS:
236
+
continue
234
237
info = _load_prompt_metadata(md_path)
235
238
236
239
info["source"] = "system"
···
340
343
Parameters
341
344
----------
342
345
name:
343
-
Talent name - either system talent (e.g., "unified") or
346
+
Talent name - either system talent (e.g., "chat") or
344
347
app-namespaced talent (e.g., "support:support").
345
348
346
349
Returns
···
498
501
499
502
500
503
def get_talent(
501
-
name: str = "unified",
504
+
name: str = "chat",
502
505
facet: str | None = None,
503
506
analysis_day: str | None = None,
504
507
) -> dict:
···
511
514
Parameters
512
515
----------
513
516
name:
514
-
Talent name to load. Can be a system talent (e.g., "unified")
517
+
Talent name to load. Can be a system talent (e.g., "chat")
515
518
or an app-namespaced talent (e.g., "support:support" for apps/support/talent/support).
516
519
facet:
517
520
Optional facet name to focus on. Controls $facets template variable.
+1
-1
think/talent_cli.py
+1
-1
think/talent_cli.py
···
804
804
return None
805
805
req_segment = request_event.get("segment")
806
806
req_facet = request_event.get("facet")
807
-
req_name = request_event.get("name", "unified")
807
+
req_name = request_event["name"]
808
808
req_env = request_event.get("env") or {}
809
809
req_stream = req_env.get("SOL_STREAM") if req_env else None
810
810
day_dir = day_path(req_day, create=False)
+5
-5
think/talents.py
+5
-5
think/talents.py
···
459
459
from think.models import resolve_model_for_provider, resolve_provider
460
460
from think.talent import get_talent, key_to_context
461
461
462
-
name = request.get("name", "unified")
462
+
name = request["name"]
463
463
facet = request.get("facet")
464
464
day = request.get("day")
465
465
segment = request.get("segment")
···
755
755
"event": "dry_run",
756
756
"ts": now_ms(),
757
757
"type": talent_type,
758
-
"name": config.get("name", "unified"),
758
+
"name": config["name"],
759
759
"provider": config.get("provider", ""),
760
760
"model": config.get("model") or "unknown",
761
761
"system_instruction": config.get("system_instruction", ""),
···
872
872
if not context:
873
873
from think.talent import key_to_context
874
874
875
-
context = key_to_context(config.get("name", "unified"))
875
+
context = key_to_context(config["name"])
876
876
backup_model = resolve_model_for_provider(context, backup, "cogitate")
877
877
878
878
emit_event(
···
928
928
from think.models import generate_with_result
929
929
from think.talent import key_to_context
930
930
931
-
name = config.get("name", "unified")
931
+
name = config["name"]
932
932
transcript = config.get("transcript", "")
933
933
user_instruction = config.get("user_instruction", "")
934
934
prompt = config.get("prompt", "")
···
1072
1072
emit_event: Callback to emit JSONL events
1073
1073
dry_run: If True, emit dry_run event instead of calling LLM
1074
1074
"""
1075
-
name = config.get("name", "unified")
1075
+
name = config["name"]
1076
1076
provider = config.get("provider", "google")
1077
1077
model = config.get("model")
1078
1078
is_cogitate = config["type"] == "cogitate"