Filing rule: Read

skills/_brain-filing-rules.md

before creating any new page.

• Every fact written to a brain page carries an inline

  [Source: ...]

  citation with date and provenance.
• Every entity mention creates a back-link from the entity's page to the page mentioning them (Iron Law).
• Raw sources are preserved for provenance via

  gbrain files upload-raw

  with automatic size routing.
• State sections are rewritten with current best understanding, never appended to.
• Entity detection fires on every inbound message; notable entities get pages or updates.

Convention: See

skills/conventions/quality.md

for Iron Law back-linking.

skills/_brain-filing-rules.md

[Source: ...]

• User's statements:

  [Source: User, {context}, YYYY-MM-DD]

• Meeting data:

  [Source: Meeting "{title}", YYYY-MM-DD]

• Email/message:

  [Source: email from {name} re: {subject}, YYYY-MM-DD]

• Web content:

  [Source: {publication}, {URL}, YYYY-MM-DD]

• Social media:

  [Source: X/@handle, YYYY-MM-DD](URL)

  (include link)
• Synthesis:

  [Source: compiled from {sources}]

Router note: This skill is a router. For specialized ingestion, see: idea-ingest, media-ingest, meeting-ingestion.

1. Parse the source. Extract people, companies, dates, and events from the input.
2. For each entity mentioned:
   • Read the entity's page from gbrain to check if it exists
   • If exists: update compiled_truth (rewrite State section with new info, don't append)
   • If new: check notability gate, then store the page in gbrain with the appropriate type and slug
3. Append to timeline. Add a timeline entry in gbrain for each event, with date, summary, and source citation.
4. Create cross-reference links. Link entities in gbrain for every entity pair mentioned together, using the appropriate relationship type.
5. Back-link all entities. Update EVERY mentioned entity's page with a back-link to this page (Iron Law).
6. Timeline merge. The same event appears on ALL mentioned entities' timelines. If Alice met Bob at Acme Corp, the event goes on Alice's page, Bob's page, and Acme Corp's page.

1. Scan the message for entity mentions: people, companies, concepts, original thinking. Fire on every message (no exceptions unless purely operational).
2. For each entity detected:

   • gbrain search "name"

     -- does a page already exist?
   • If yes: load context with

     gbrain get <slug>

     . Use the compiled truth to inform your response. Update the page if the message contains new information.
   • If no: assess notability (see

     skills/_brain-filing-rules.md

     ). If the entity is worth tracking, create a new page with

     gbrain put <type/slug>

     and populate with what you know.
3. After creating or updating pages: sync to gbrain:
   bash

   gbrain sync --no-pull --no-embed

4. Don't block the conversation. Entity detection and enrichment should happen alongside the response, not before it. The user shouldn't wait for brain writes to get an answer.

• People the user interacts with or discusses (not random mentions)
• Companies relevant to the user's work or interests
• Concepts or frameworks the user references or creates
• The user's own original thinking (ideas, theses, observations) -- highest value
• See

  skills/_brain-filing-rules.md

  for the full notability gate

• Novel observations or theses
• Frameworks, mental models, heuristics
• Connections between ideas that others miss
• Contrarian positions with reasoning
• Strong reactions to external stimuli (what triggered it and why)

1. Fetch content (

   web_fetch

   or equivalent)
2. Extract: title, author, publication, date, full text
3. Summarize: executive summary + key arguments (not a rehash)
4. Extract entities: people, companies, concepts mentioned
5. Save raw source for provenance (see Raw Source Preservation below)
6. Analyze for the user: don't just summarize. What's interesting given what you know about them? Flag connections, contradictions, content opportunities.

people/

companies/

concepts/

sources/

1. Get transcript -- speaker-diarized if possible (services like Diarize.io provide speaker-labeled, word-level timing)
2. Save raw transcript (both JSON and human-readable TXT)
3. Analyze: executive summary, key ideas, key quotes with speaker attribution, notable stories/anecdotes, people and companies mentioned
4. Extract and cross-reference all entities mentioned
5. HARD RULE: every video/podcast brain page MUST link to the raw diarized transcript. A page without transcript links is incomplete.

media/videos/

media/podcasts/

• Compelling headline (not "This video discusses...")
• Executive summary that makes you want to watch/listen
• Key Ideas as actual insights, not topic labels
• Verbatim quotes with real speaker names (not "speaker_0")
• All entities extracted with context and back-linked

1. Extract text (OCR if scanned/image PDF)
2. Save raw source for provenance
3. Summarize: executive summary + key sections + notable data
4. Extract entities
5. Cross-reference from entity pages

1. Analyze content (OCR for text-heavy images, description for photos)
2. If tweet screenshot: extract text, author, date, route to social media workflow
3. If article screenshot: extract text, route to article workflow
4. If data/chart: extract data points, describe findings

1. Pull full transcript (source of truth -- AI summaries are medium-low trust)
2. Save raw transcript for provenance
3. Write meeting page with YOUR analysis above the line, raw transcript below
4. Entity propagation (MANDATORY): for each attendee and company discussed:
   • Update their brain page State section if new info surfaced
   • Append to their Timeline with link to the meeting page
   • Create page if person/company is notable and has no page yet
5. A meeting is NOT fully ingested until all entity pages are updated

meetings/YYYY-MM-DD-short-description.md

• Reveals the real crux, not a bullet dump
• Connects to existing brain pages (people, companies, deals)
• Flags what changed (status, decisions, new info)
• Names tension or what was left unsaid
• Captures actual dynamic, not performative summary

1. Fetch full content (thread, quote tweets, context)
2. If images present: OCR via vision model for full text extraction
3. Summarize: what's being said, why it matters, who's involved
4. Extract entities and update brain pages
5. Include direct link to the original post (MANDATORY for citations)

media/x/

gbrain files upload-raw

gbrain files upload-raw <file> --page <page-slug> --type <type>

• < 100 MB text/PDF: stays in git (brain repo

  .raw/

  sidecar directories)
• >= 100 MB OR media (video, audio, images): uploaded to cloud storage via TUS resumable upload,

  .redirect.yaml

  pointer left in the brain repo

.redirect.yaml

target: supabase://brain-files/page-slug/filename.mp4
bucket: brain-files
storage_path: page-slug/filename.mp4
size: 524288000
size_human: 500 MB
hash: sha256:abc123...
mime: video/mp4
uploaded: 2026-04-11T...
type: transcript

• gbrain files signed-url <storage-path>

  -- generate 1-hour signed URL for viewing/sharing

• gbrain files restore <dir>

  -- download back to local from cloud storage

put_raw_data

1. Test on 3-5 items first. Run in test mode if available.
2. Read the actual output. Is the quality good? Are titles compelling (not "This video discusses...")? Are entities extracted and back-linked? Is the format clean?
3. Fix what's wrong in the approach/skill, not via one-off patches.
4. Only then: bulk execute with throttling, commits every 5-10 items.

• Executive summary in compiled_truth must be updated, not just timeline appended
• State section is REWRITTEN, not appended to. Current best understanding only.
• Timeline entries are reverse-chronological (newest first)
• Every person/company mentioned gets a page if notable (see filing rules)
• Link types: knows, works_at, invested_in, founded, met_at, discussed
• Source attribution: every timeline entry includes [Source: ...] citation
• Back-links: every entity mention creates a back-link (Iron Law)
• Filing: file by primary subject, not format or source (see filing rules)

• Appending to State sections. State is rewritten with the current best understanding on every update. Append-only State sections grow stale and contradictory.
• Ingesting without back-links. An unlinked mention is a broken brain. Every entity mentioned must have a back-link from their page to the page mentioning them.
• Skipping raw source preservation. Every ingested item must have its raw source preserved. A brain page without provenance is unverifiable.
• Bulk processing without sample test. Test on 3-5 items first. Fix quality issues in the approach, not via one-off patches.
• Paraphrasing the user's original thinking. The user's exact language IS the insight. Capture verbatim phrasing for ideas, theses, and frameworks.

• Read a page from gbrain (get_page)
• Store/update a page in gbrain (put_page)
• Add a timeline entry in gbrain (add_timeline_entry)
• Link entities in gbrain (add_link)
• List tags for a page (get_tags)
• Tag a page in gbrain (add_tag)
• Store raw data in gbrain (put_raw_data)
• Check backlinks in gbrain (get_backlinks)