Enrich

Philosophy

A brain page should read like an intelligence dossier, not a LinkedIn scrape. Facts are table stakes. Texture is the value -- what do they believe, what are they building, what makes them tick, where are they headed.

Citation Requirements (MANDATORY)

Every fact must carry an inline [Source: ...] citation.

Three formats:

• Direct attribution: [Source: User, {context}, YYYY-MM-DD]
• API/external: [Source: {provider} enrichment, YYYY-MM-DD]
• Synthesis: [Source: compiled from {list of sources}]

Source precedence (highest to lowest):

1. User's direct statements
2. Compiled truth (pre-existing brain synthesis)
3. Timeline entries (raw evidence)
4. External sources (API enrichment, web search)

When sources conflict, note the contradiction with both citations.

When To Enrich

Primary triggers

• User mentions an entity in conversation
• Entity appears in a meeting transcript or email
• New contact appears with significant context
• Entity makes news or has a major event
• Any ingest pipeline encounters a notable entity

Do NOT enrich

• Random mentions with no relationship signal
• Bot/spam accounts
• Entities with no substantive connection to the user's work
• Same page enriched within the past week (unless new signal warrants it)

Enrichment Tiers

Scale enrichment to importance. Don't waste API calls on low-value entities.

The Enrichment Protocol (7 Steps)

Step 1: Identify entities

Extract people, companies, concepts from the incoming signal.

Step 2: Check brain state

For each entity:

• gbrain search "name" -- does a page already exist?
• If yes: UPDATE path (add new signal, update compiled truth if material)
• If no: CREATE path (check notability gate first, then create)

Step 3: Extract signal from source

Don't just capture facts. Capture texture:

Step 4: External data source lookups

Priority order -- stop when you have enough signal for the entity's tier.

4a. Brain cross-reference (always, all tiers)

• gbrain search "name" and gbrain query "what do we know about name"
• Check related pages: company pages for person enrichment and vice versa
• This is free and often the richest source

4b. Web research (Tier 1 and 2)

• Use Perplexity, Brave Search, Exa, or equivalent web research tool
• Key pattern: Send existing brain knowledge as context so the search returns DELTA (what's new vs what you already know), not a rehash
• Opus-class models for Tier 1 deep research, lighter models for Tier 2

4c. Social media lookup (all tiers when handle known)

• Pull recent posts/tweets for tone, interests, current focus
• Social media is the highest-texture signal for what someone actually thinks

4d. People enrichment APIs (Tier 1)

• LinkedIn data, career history, connections, education

4e. Company enrichment APIs (Tier 1)

• Company data, financials, headcount, key hires, recent news

Step 5: Save raw data (preserves provenance)

Store raw API responses via put_raw_data in gbrain:

{
  "source": "crustdata",
  "fetched_at": "2026-04-11T...",
  "query": "jane doe",
  "data": { ... }
}

Raw data preserves provenance. If the compiled truth is ever questioned, the raw data shows exactly what the API returned.

Step 6: Write to brain

CREATE path

1. Check notability gate (see skills/_brain-filing-rules.md)
2. Check filing rules -- where does this entity go?
3. Create page with the appropriate template (below)
4. Fill compiled truth with citations
5. Add first timeline entry
6. Leave empty sections as [No data yet] (don't fill with boilerplate)

UPDATE path

1. Add new timeline entries (reverse-chronological, append-only)
2. Update compiled truth ONLY if the new signal materially changes the picture
3. Update State section with new facts
4. Flag contradictions between new signal and existing compiled truth
5. Don't overwrite user-written assessments with API boilerplate

Person page template

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