SQLite database operations + document-corpus search. Commands: catalog, exec, list_databases, open_database, health_check, docs_search, docs_semantic_search, docs_hybrid, docs_full, docs_context, docs_search_in_doc. docs_search: FTS5 keyword search over the ingested docs corpus. Use for exact terms, API names, phrases. docs_semantic_search: Embedding similarity search over docs. Use for general queries. docs_hybrid: PREFER THIS Run both keyword + semantic with RRF fusion. Best recall. docs_full: Retrieve complete document by exact path. Use sql param with path from search results. Wildcard % optional for fuzzy match. docs_context: Expand around a chunk - params: {chunk_id, before, after}. docs_search_in_doc: Hybrid search within a specific document - params: {query, limit, threshold}. sql=path. Returns chunk positions. All docs search commands: query via 'sql' param. docs_* filters: {doc_type, source, limit, threshold}. docs_* results are pre-chunked - do NOT use file reads; run more searches or use docs_context/docs_full instead.

Unified retrieval across KG, Memory, and Docs with KG-powered query expansion. Use for conceptual queries where keyword search fails. Automatically expands query using KG domain knowledge (e.g., 'transformer optimization' -> includes KV cache, Flash Attention). Fuses results via reciprocal rank fusion. Returns results with source attribution. Default: compact=true (shorter snippets, ~500-800 tokens). Use compact=false for full content (~2000 tokens).

On session start: get session:latest + project:overview. Semantic memory for cross-session persistence. Returns {success, results/value}. Actions: store (save key+message, full overwrite), append (add fragment to existing key without rewriting it - server concatenates and re-embeds), replace_section (in-place edit of marker-bounded region inside an existing entry), search (semantic query), get (exact key), delete, list. RAM-backed with async disk persist - use liberally. Key conventions: session:latest (current state), project:overview (architecture), learn: (discoveries), pref: (user prefs), todo:, code:. For large rolling docs (timelines, session logs) use append instead of store - massive token savings. For in-place section edits inside a long doc, use replace_section with HTML-comment markers like ''/''. Search is semantic with synonym expansion ('fast'->'quick'). Use preprocess=False for exact match. When encountering issues or problems search for related context. On milestones: store session:latest.

Entity-relationship graph for structured facts. Use for entities with relationships - concepts, tools, people, patterns. Check here before semantic_search. For free-form text/learnings, use memory instead. Hybrid search (70% semantic + 30% keyword). Limits: 10K entities, 100 obs/entity. Audit log for destructive ops. Actions: create_entities, create_relations, add_observations, delete_entities, delete_relations, search, neighbors, stats, read, prune, remove_observation, update_entity, rename_entity, merge_entities, batch. IMPORTANT: Always specify entity_type when creating entities - omitting it defaults to 'unknown' which pollutes the graph. Knowledge graph is stored as JSONL.