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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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