ingest
Route content to specialized ingestion skills. Detects input type and delegates.
What this skill does
# Ingest Skill
Ingest meetings, articles, media, documents, and conversations into the brain.
> **Filing rule:** Read `skills/_brain-filing-rules.md` before creating any new page.
## Contract
- 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.
Every mention of a person or company with a brain page MUST create a back-link
FROM that entity's page TO the page mentioning them. An unlinked mention is a
broken brain. See `skills/_brain-filing-rules.md` for format.
## Citation Requirements (MANDATORY)
Every fact written to a brain page must carry an inline `[Source: ...]` citation.
- **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}]`
## Phases
> **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.
## Entity Detection on Every Message
Production agents should detect entity mentions on EVERY inbound message. This is
the signal detection loop that makes the brain compound over time.
### Protocol
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.
### What counts as notable
- 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
### What to capture from the user's own thinking
Original thinking is the most valuable signal. Capture exact phrasing -- the user's
language IS the insight. Don't paraphrase.
- 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)
## Media Workflows
Content the user encounters should be captured in the brain. File by PRIMARY
SUBJECT, not by format (see `skills/_brain-filing-rules.md`).
### Articles & Web Content
**Input:** URL shared by user, or article mentioned in conversation.
**Process:**
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.
**Write to:** appropriate directory per filing rules (about a person -> `people/`,
about a company -> `companies/`, reusable framework -> `concepts/`, raw data -> `sources/`)
### Videos & Podcasts
**Input:** URL (YouTube, podcast, etc.) or local audio/video file.
**Process:**
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.
**Write to:** `media/videos/` or `media/podcasts/` with back-links to all entities.
**Quality bar:**
- 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
### PDFs & Documents
**Input:** File path or URL.
**Process:**
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
**Write to:** per filing rules (file by primary subject, not format).
### Screenshots & Images
**Input:** Image file.
**Process:**
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
**Write to:** depends on content -- route to the appropriate workflow above.
### Meeting Transcripts
**Input:** Transcript from meeting recording service, or manual notes.
**Process:**
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
**Write to:** `meetings/YYYY-MM-DD-short-description.md`
**What makes a good meeting page:**
- Reveals the real crux, not a bullet dump
- Connects to existing brain pages (people, companies, deals)
- Flags what changed (status, decisions, new info)
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