Report store statistics: total/active memory counts, breakdowns by space, silo, status, and kind, schema version, and database size. Read-only; no side effects. Use to inspect the store's overall state and health, not to retrieve memories (use search or pack for that).

Find individual memories ranked by relevance to a query. Semantic-primary when embedding models are loaded, falling back to deterministic BM25/FTS keyword search otherwise; cross-encoder reranked by default. Read-only. Returns scored, individual memory records (with ids) — use this to locate or inspect specific memories. To assemble a prompt-ready context block, use pack instead; to browse recent memories without a query, use memory_list.

Fetch one memory by its exact id (for example, an id returned by search or memory_list). Read-only. Use when you already have the id and want the full record; use search to find a memory by its content.

List recent memories in reverse-chronological order for review or cleanup, optionally filtered. Read-only. Use to browse or audit what is stored (including stale or superseded entries); use search or pack for relevance-ranked retrieval against a query.

Search the entity graph by key, canonical name, alias, or type (substring match). Read-only. Returns entity records, not memories — use it to resolve an entity_key or canonical name from a partial term. For memory content use search; to traverse outward from a known entity use graph_neighbors or graph_context.

Traverse the entity graph outward from a starting entity, returning connected entities and the relationships between them up to a bounded depth. Read-only. Use to explore how an entity connects to others (raw graph structure); use graph_context if you want a prose, prompt-ready context pack instead of edges.

Build a compact, prompt-ready context pack centered on an entity: the entity, its graph neighbors, and the most relevant linked memories, budgeted to a character limit. Read-only. Use when an agent needs ready-to-inject context about one specific entity; use pack for query-driven context, or graph_neighbors for raw graph edges.

Preview the graph-maintenance pass in dry-run (proposal-only) mode: surfaces the entity and relationship extractions and merges the nightly dream job would make, without writing anything. Read-only; no side effects. Use to inspect what graph changes are pending before they are applied.

Write one durable memory the agent should be able to recall later. Mutating: persists a memory (set dry_run to validate without writing). Store exactly one atomic, self-contained fact, decision, preference, or lesson per call — include enough context that it stands alone ("the user deploys from the release branch, never main", not just "release branch"). Do not store secrets or raw transcripts. For a plausible-but-unverified inference, use candidate_submit instead so a human approves it first.

Retire one specific memory by id. Mutating: tombstones the memory (a soft delete that preserves audit history), so it stops surfacing in recall; it is not a hard delete. Set mode='correct' when retiring a memory because it is WRONG (e.g. a surfaced/recalled fact the user contradicted), as opposed to routine cleanup: this records a distinct correct event with the memory's provenance, and if you pass corrected_by (the id of the memory holding the right answer) it also records a contradicts link. Use mode='correct' for factual corrections so the signal is captured explicitly rather than inferred later.

Create or update one entity in the graph projection (register it, rename it, or add aliases). Mutating. The graph is a rebuildable projection over memories, which remain the source of truth — use this to curate entity identity, not to store facts (use remember for facts).

Create or update one directed relationship in the graph: subject --relation_type--> object. Mutating. Identify each endpoint by entity_key (preferred) or internal entity_id. The graph is a rebuildable projection over memories — curate structure here, store facts with remember.

Re-confirm that an existing memory is still accurate as of now, stamping its last-verified time. Mutating: updates verification metadata only — it does NOT change the memory's content or promote it to a durable tier. If the value has CHANGED, do not verify; write a new memory with remember and supersede the old one instead.

Assemble a compact, prompt-ready context block from one or more queries: retrieves, reranks, and budgets the top memories into injectable text. Read-only. This is the retrieval path for putting memory into an agent's prompt; use search instead when you want individual scored records rather than an assembled block.

Queue a proposed memory for human review instead of writing it to recall directly. Mutating: adds an item to the review queue (it does not enter recall until a human approves it via CLI/dashboard). Use this for plausible-but-unverified inferences; use remember when the fact is confirmed and should be recallable immediately.

List memories in the human-review queue, filtered by review status. Read-only. Use to see what has been proposed via candidate_submit and its disposition; approving or rejecting candidates is a human action in the CLI/dashboard.