Emit the four-layer memory model's L1 (.ai-memory/) from a CodeMap index
Project description
codemap-aimemory
Emits the four-layer memory model's
L1 (.ai-memory/) output from a CodeMap index.
What it writes
.ai-memory/
├── entities/
│ ├── functions.yml fn-* / cls-* entities, with calls / called_by /
│ │ related_tables / signature / line_range
│ ├── tables.yml tbl-* entities
│ └── files.yml file-* entities
├── relations/
│ ├── call-graph.yml from / to / type=calls / confidence
│ ├── table-relations.yml from / to / type=accesses_table / confidence
│ └── rule-constraints.yml (empty; managed by L2)
└── enrichment/ optional LLM overlay (one file per enriched
symbol, loaded by the emitter to fill
business_meaning / related_rules)
All writes are atomic per file (tmp + rename), so an Agent reading
.ai-memory/ never sees a half-written tree.
Two-layer separation
The core L1 output (above) is purely deterministic — no LLM. The optional
enrich CLI fills business_meaning / related_rules into separate
enrichment/*.yml files. The emitter merges enrichment values when it
re-emits, but the core JSON-store index never carries explanation text.
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