personal memory agent
Add dynamic input-level context for quiet/sparse journal days
Insights and scheduled agents now receive context about data availability
for the day being processed. This helps them handle days with no recordings
(holidays, weekends, offline) gracefully without raising false alarms.
Changes:
- Add day_input_summary() helper to think/utils.py that detects recording
segments and returns human-readable summaries like "No recordings" or
"Light activity: 2 segments, ~3 minutes"
- Modify think/insight.py to prepend input context notes to Gemini prompts
when file_count is 0 or very low
- Modify think/supervisor.py to include input summary in agent spawn prompts
- Update test_supervisor_schedule.py to mock the new function
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
+84
-8
+13
-5
tests/test_supervisor_schedule.py
+13
-5
tests/test_supervisor_schedule.py
···
9
9
from think.supervisor import spawn_scheduled_agents
10
10
11
11
12
+
@patch("think.supervisor.day_input_summary")
12
13
@patch("think.supervisor.cortex_request")
13
14
@patch("think.supervisor.get_agents")
14
15
@pytest.mark.asyncio
15
-
async def test_spawn_scheduled_agents(mock_get_agents, mock_cortex_request):
16
+
async def test_spawn_scheduled_agents(
17
+
mock_get_agents, mock_cortex_request, mock_input_summary
18
+
):
16
19
"""Test that scheduled agents are spawned correctly via Cortex."""
17
20
from think.supervisor import check_scheduled_agents
18
21
···
37
40
# Mock cortex_request to return agent IDs
38
41
mock_cortex_request.side_effect = ["123456789", "987654321"]
39
42
43
+
# Mock input summary
44
+
mock_input_summary.return_value = "No recordings"
45
+
40
46
# Call the functions (prepare then execute)
41
47
with patch.dict(os.environ, {"JOURNAL_PATH": "/test/journal"}, clear=True):
42
48
spawn_scheduled_agents()
···
45
51
# Should spawn 2 agents (todo and another_daily)
46
52
assert mock_cortex_request.call_count == 2
47
53
48
-
# Check first request call (todos:todo) - now simplified
54
+
# Check first request call (todos:todo) - includes input summary
49
55
first_call = mock_cortex_request.call_args_list[0]
50
56
assert first_call[1]["persona"] == "todos:todo"
51
-
assert "Running daily scheduled task for todos:todo" in first_call[1]["prompt"]
57
+
assert "Running daily scheduled task" in first_call[1]["prompt"]
58
+
assert "No recordings" in first_call[1]["prompt"]
52
59
53
-
# Check second request call (another_daily) - now simplified
60
+
# Check second request call (another_daily) - includes input summary
54
61
second_call = mock_cortex_request.call_args_list[1]
55
62
assert second_call[1]["persona"] == "another_daily"
56
-
assert "Running daily scheduled task for another_daily" in second_call[1]["prompt"]
63
+
assert "Running daily scheduled task" in second_call[1]["prompt"]
64
+
assert "No recordings" in second_call[1]["prompt"]
57
65
58
66
59
67
@patch("think.supervisor.check_scheduled_agents")
+15
think/insight.py
+15
think/insight.py
···
355
355
markdown, file_count = cluster(args.day)
356
356
day_dir = str(day_path(args.day))
357
357
358
+
# Prepend input context note for sparse/empty days
359
+
if file_count == 0:
360
+
input_note = (
361
+
"**Input Note:** No recordings for this day - likely a holiday, "
362
+
"weekend, or offline day. This is normal. Generate concise "
363
+
"acknowledgment rather than detailed analysis.\n\n"
364
+
)
365
+
markdown = input_note + markdown
366
+
elif file_count < 3:
367
+
input_note = (
368
+
"**Input Note:** Limited recordings for this day. "
369
+
"Scale analysis to available input.\n\n"
370
+
)
371
+
markdown = input_note + markdown
372
+
358
373
try:
359
374
360
375
load_dotenv()
+4
-3
think/supervisor.py
+4
-3
think/supervisor.py
···
18
18
from think.callosum import CallosumConnection, CallosumServer
19
19
from think.facets import get_active_facets, get_facets
20
20
from think.runner import ManagedProcess as RunnerManagedProcess
21
-
from think.utils import get_agents, setup_cli
21
+
from think.utils import day_input_summary, get_agents, setup_cli
22
22
23
23
DEFAULT_THRESHOLD = 60
24
24
CHECK_INTERVAL = 30
···
422
422
# yesterday is the same for all agents in the group (YYYY-MM-DD format)
423
423
yesterday = agents_list[0][2] if agents_list else ""
424
424
yesterday_yyyymmdd = yesterday.replace("-", "")
425
+
input_summary = day_input_summary(yesterday_yyyymmdd)
425
426
facets = get_facets()
426
427
enabled_facets = {k: v for k, v in facets.items() if not v.get("muted", False)}
427
428
active_facets = get_active_facets(yesterday_yyyymmdd)
···
454
455
455
456
logging.info(f"Spawning {persona_id} for facet: {facet_name}")
456
457
agent_id = cortex_request(
457
-
prompt=f"You are processing facet '{facet_name}' for yesterday ({yesterday}), use get_facet('{facet_name}') to load the correct context before starting.",
458
+
prompt=f"Processing facet '{facet_name}' for yesterday ({yesterday}): {input_summary}. Use get_facet('{facet_name}') to load context.",
458
459
persona=persona_id,
459
460
)
460
461
active_files.append(agents_dir / f"{agent_id}_active.jsonl")
···
464
465
else:
465
466
# Regular single-instance agent
466
467
agent_id = cortex_request(
467
-
prompt=f"Running daily scheduled task for {persona_id}, yesterday was {yesterday}.",
468
+
prompt=f"Running daily scheduled task. Yesterday ({yesterday}): {input_summary}.",
468
469
persona=persona_id,
469
470
)
470
471
active_files.append(agents_dir / f"{agent_id}_active.jsonl")
+52
think/utils.py
+52
think/utils.py
···
410
410
_append_task_log(journal, message)
411
411
412
412
413
+
def day_input_summary(day: str) -> str:
414
+
"""Return a human-readable summary of recording data available for a day.
415
+
416
+
Uses cluster_segments() to detect recording segments and computes
417
+
total duration from segment keys (HHMMSS_LEN format).
418
+
419
+
Parameters
420
+
----------
421
+
day:
422
+
Day in YYYYMMDD format.
423
+
424
+
Returns
425
+
-------
426
+
str
427
+
Human-readable summary like "No recordings", "Light activity: 2 segments,
428
+
~3 minutes", or "18 segments, ~7.5 hours".
429
+
"""
430
+
from think.cluster import cluster_segments
431
+
432
+
segments = cluster_segments(day)
433
+
434
+
if not segments:
435
+
return "No recordings"
436
+
437
+
# Compute total duration from segment keys (HHMMSS_LEN format)
438
+
total_seconds = 0
439
+
for seg in segments:
440
+
key = seg.get("key", "")
441
+
if "_" in key:
442
+
parts = key.split("_")
443
+
if len(parts) >= 2 and parts[1].isdigit():
444
+
total_seconds += int(parts[1])
445
+
446
+
# Format duration
447
+
if total_seconds < 60:
448
+
duration_str = f"~{total_seconds} seconds"
449
+
elif total_seconds < 3600:
450
+
minutes = total_seconds / 60
451
+
duration_str = f"~{minutes:.0f} minutes"
452
+
else:
453
+
hours = total_seconds / 3600
454
+
duration_str = f"~{hours:.1f} hours"
455
+
456
+
segment_count = len(segments)
457
+
458
+
# Categorize activity level
459
+
if segment_count < 5 or total_seconds < 1800: # < 5 segments or < 30 min
460
+
return f"Light activity: {segment_count} segment{'s' if segment_count != 1 else ''}, {duration_str}"
461
+
else:
462
+
return f"{segment_count} segments, {duration_str}"
463
+
464
+
413
465
def touch_health(name: str) -> None:
414
466
"""Update the journal's ``name`` heartbeat file.
415
467