brain-write

The write surface is small but consequential — every fact you record gets scored by the conflict resolver, may supersede or compete with existing facts, and stays in the audit trail forever. This skill covers when to reach for each tool and how to set the inputs so the resolver does what you mean.

When to use

• The user says "remember that …" / "make a note that …" / "let's record …" → record_fact
• A fact you have on hand says "X is the same person as Y" → link_entities with kind: identity_of
• A typed edge between two known entities (paid_for, mentioned_in, worked_with, …) → link_entities
• Something brain previously believed is now known to be wrong → retract_fact
• "Before I save this, would it conflict with anything?" → detect_contradiction

Do not use for:

• Bulk ingest from a vertical's event stream — that's a /v1/ingest path, not an agent loop
• GDPR-grade hard delete → forget_entity (admin scope; see brain-mcp-setup)

All write tools require the brain:write scope on the API key. forget_entity requires brain:admin.

record_fact — recording one fact

record_fact({
  entityRef: { vertical: "rent", id: "cust_42" }, // or { entityId: "..." }
  predicate: "tier",
  object: "platinum",
  validFrom: "2026-05-01T00:00:00Z",
  validUntil: undefined,            // optional — leave open-ended unless the user said "until X"
  confidence: 0.9,                  // 0..1
  sourceVertical: "rent",
})

Picking confidence

The conflict resolver scores each candidate against existing facts using confidence × CONFLICT_WEIGHT_CONFIDENCE + sourceTrust × CONFLICT_WEIGHT_SOURCE_TRUST + recency + authority. Confidence is the per-fact axis you control; pick it honestly:

A confidence of 1.0 implies a system-grade ground truth source — don't claim it for an LLM extraction.

Preflight with detect_contradiction

When the cost of a contested write is high (e.g. agent loops that pay an ingest credit, or actions that would surface a CHANGED notification), check first:

detect_contradiction({
  entityRef:    { vertical: "rent", id: "cust_42" },
  predicate:    "tier",
  object:       "platinum",
  validFrom:    "2026-05-01T00:00:00Z",
  confidence:   0.9,
  sourceVertical: "rent",
})

Returns { wouldOutcome, reasoning, opposingFacts, predicatePolicy }:

The dry-run is JS-side approximation of fn::resolve_fact — small fidelity gap on source_trust (uses the seed table, not the per-tenant learned rate) but matches the resolver's logic on every other axis.

link_entities — declaring a typed edge

link_entities({
  from: { vertical: "rent", id: "cust_42" },
  to:   { vertical: "shop", id: "buyer_18" },
  kind: "identity_of",                // 'identity_of' merges; other kinds add typed edges
  weight: 1.0,                        // 0..1, optional
  sourceVertical: "rent",
})

kind: identity_of — cross-vertical merge

identity_of is special — it triggers a cascade that merges from into to:

• Every fact on from is reparented to to
• from.mergedAt + from.mergedInto are set so the redirect is auditable
• The conflict resolver runs over the union (so two source-of-truth facts on the same predicate compete properly)

Cycle guards:

• A self-merge (from == to) is rejected.
• A merge that would create a cycle (A → B → A) is rejected.
• A merge against an already-merged entity (B.mergedInto = C) follows the redirect — you end up merging into C, not B. The semantic is "merge the whole identity cluster", not "merge into the row by id".

Non-merge kinds

Typed edges (paid_for, mentioned_in, worked_with, manages, etc.) just add a row in knowledge_edge. They're surfaced by find_related_entities and contribute to PPR / SubgraphRAG context. Free-vocabulary; tenants extend the edge taxonomy without a migration.

retract_fact — walking a belief back

retract_fact({
  factId: "knowledge_fact:01HXYZ...",
  reason: "Source misattributed; was Bob, not Alice.",
})

What happens:

• The fact's status flips to retracted, retractedAt is set, retractionReason recorded.
• The cascade walks derivedFrom — any fact derived from this one is also retracted (depth-first).
• If this fact had previously superseded another, the predecessor is REVIVED (status='active', validUntil restored to its pre-supersede value). The audit trail keeps the supersede/revive chain.
• Cross-vertical changefeed picks up the change so dependent systems are notified.

The row stays for audit. To actually delete (GDPR), use forget_entity — admin scope only.

Predicate-class admin escalation

Three predicate classes require brain:admin for retract, not just brain:write:

• billing_event — affects downstream invoicing audits
• human_declared — represents operator-attested ground truth
• Any fact whose source.kind === 'legal' — regulator-visible

If the API key has only brain:write, the retract on these falls through with a 403. Don't pre-validate this in the agent loop; let brain enforce it and tell the user the scope they need.

retract vs forget — when to use which

Default to retract. Reach for forget only when a DSAR or tenant-offboarding event genuinely requires erasure.

Pitfalls

• Confidence inflation. Don't pad LLM-extracted facts to 0.95 because "the model sounded sure". The resolver weighs confidence honestly; inflated values poison the conflict math for the next legitimate update.
• `validFrom` defaults to "now" feel wrong. Brain has no default — you must pass validFrom. If the user said "Alice is platinum", validFrom is the moment of conversation. If they said "Alice has been platinum since April", validFrom is April. Be precise.
• `sourceVertical` not where the user is. sourceVertical describes WHO is asserting the fact — usually the vertical the agent is operating on behalf of ("rent", "shop"), not the vertical the agent runtime lives in ("chat"). Get this wrong and the conflict resolver's source_trust math goes sideways.
• identity_of as a generic "they're related" edge. Don't. identity_of is a merge directive. For "are connected", use a typed edge like worked_with or interacted_with.
• Recording the same fact twice in a row. The resolver dedups by (entityId, predicate, object) when bitemporal windows match — second call returns INSERTED with the original factId, not a new row. Harmless but wasteful; cache the factId from the first call.

Companion tools

• detect_contradiction — preflight before record_fact
• get_competing_facts — see what's already unresolved on this entity (see brain-conflict)
• search_knowledge / get_entity_profile — find the existing fact before retracting (see brain-search, brain-recall)
• memory_diff — confirm the change landed (see brain-bitemporal)