personal memory agent
feat(sense): require facets array minItems: 1; hydrator drops constraint on empty journals
Tightens talent/sense.schema.json so the sense talent must attribute every
active segment to at least one configured facet. The runtime hydrator drops
the minItems constraint when the journal has no valid facets so the schema
stays satisfiable on fresh journals. Prompt copy updated to require closest-
match attribution; no behavior change to the activity state machine's no-
facet sentinel branch (kept as defense-in-depth).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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talent/sense.md
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talent/sense.md
···
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- **other**: Use only when the entity is grounded in another clear signal that does not fit the categories above.
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### facets
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Classify into the owner's configured facets. Only include facets with clear, direct evidence of activity. Be precise — assign exactly ONE primary facet in most cases. Only add a second facet if there is genuinely distinct secondary activity. For each:
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Classify into the owner's configured facets. Always include at least one facet — pick the closest configured facet. If multiple facets fit, include the dominant one as `level: high` and others at `level: medium` or `level: low`. For each:
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- `facet`: The facet ID slug — MUST be one of the configured facets listed in the input
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- `activity`: 1-sentence description of what was observed for this facet
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- `level`: "high" (primary focus), "medium" (significant), "low" (brief/peripheral)
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**Facet assignment rules:** Do not invent facet IDs that are not in the configured journal facet list. Empty array is acceptable when no configured facet matches.
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**Facet assignment rules:** Do not invent facet IDs that are not in the configured journal facet list. The array always has at least one entry — pick the closest configured facet even when the match is loose, and use `level: low` to signal weak fit.
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### meeting_detected
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`true` ONLY if you can identify distinct, named participants in a live multi-person interaction:
···
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1. Every field is required. Never omit a field.
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2. `entities` and `speakers` may be empty arrays `[]`.
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3. `facets` may be empty array `[]` if no configured facets match.
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3. `facets` always has at least one entry — the closest configured facet for the activity. Empty array is not allowed.
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4. Be precise with density — misclassifying active segments as idle is the worst error.
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5. For `content_type`, choose the single best match — the dominant activity in the segment. If two activities are roughly equal, pick the one with more durable continuation evidence (entities, repeated screen content); the `facets[]` array's `level` field already encodes secondary activity.
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6. Activity summary must describe observable actions, not inferred states.
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talent/sense.schema.json
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talent/sense.schema.json
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tests/test_sense_schema.py
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tests/test_sense_schema.py
···
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assert hydrated["properties"]["facet"]["enum"] == ["alpha", "valid_one"]
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def test_sense_schema_facets_array_requires_minItems_one():
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schema = json.loads(SENSE_SCHEMA_PATH.read_text(encoding="utf-8"))
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facets_node = schema["properties"]["facets"]
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assert facets_node["type"] == "array"
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assert facets_node.get("minItems") == 1
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Draft202012Validator.check_schema(schema)
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def test_hydrate_runtime_enums_preserves_facet_minItems_when_facets_exist(
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monkeypatch,
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):
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monkeypatch.setattr(
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"think.talent.get_facets",
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lambda: {"alpha": {}, "Beta": {}, "weird,name": {}, "valid_one": {}},
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)
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schema = {
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"type": "object",
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"properties": {
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"facets": {
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"type": "array",
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"minItems": 1,
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"items": {
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"type": "object",
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"properties": {
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"facet": {
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"type": "string",
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"enum": [RUNTIME_FACETS_SENTINEL],
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}
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},
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},
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}
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},
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}
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hydrated = hydrate_runtime_enums(schema)
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facets_node = hydrated["properties"]["facets"]
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facet_schema = facets_node["items"]["properties"]["facet"]
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assert facets_node["minItems"] == 1
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assert facet_schema["enum"] == ["alpha", "valid_one"]
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Draft202012Validator.check_schema(hydrated)
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def test_hydrate_runtime_enums_empty_facets_fallback(monkeypatch):
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monkeypatch.setattr("think.talent.get_facets", lambda: {})
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schema = {
···
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facet_schema = hydrated["properties"]["facet"]
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assert facet_schema == {"type": "string", "minLength": 1}
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Draft202012Validator.check_schema(hydrated)
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def test_hydrate_runtime_enums_drops_facet_minItems_on_empty_facets_fallback(
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monkeypatch,
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):
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monkeypatch.setattr("think.talent.get_facets", lambda: {})
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schema = {
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"type": "object",
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"properties": {
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"facets": {
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"type": "array",
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"minItems": 1,
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"items": {
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"type": "object",
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"properties": {
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"facet": {
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"type": "string",
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"enum": [RUNTIME_FACETS_SENTINEL],
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}
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},
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},
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}
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},
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}
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hydrated = hydrate_runtime_enums(schema)
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facets_node = hydrated["properties"]["facets"]
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facet_schema = facets_node["items"]["properties"]["facet"]
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assert "minItems" not in facets_node
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assert facet_schema["minLength"] == 1
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assert "enum" not in facet_schema
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Draft202012Validator.check_schema(hydrated)
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+4
think/talent.py
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think/talent.py
···
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replaces it with the sorted list of valid runtime facet slugs. If no
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valid facets exist, drops the `enum` key and sets `minLength: 1` on
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that node so the schema remains satisfiable.
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Also removes the parent facets array `minItems` constraint in that case.
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Returns None when given None. Deep-copies non-None input. Idempotent
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for already-hydrated schemas (sentinel is gone after first call).
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_walk(hydrated)
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if used_empty_fallback:
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facets_node = hydrated.get("properties", {}).get("facets")
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if isinstance(facets_node, dict):
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facets_node.pop("minItems", None)
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LOG.info(
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"hydrate_runtime_enums: no valid runtime facets; using minLength fallback"
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)