Meeting Ingestion Skill — Unified Pipeline

Filing rule: Read skills/_brain-filing-rules.md before creating any new page.

Convention: See skills/conventions/quality.md for Iron Law back-linking, and skills/conventions/brain-first.md for the lookup chain — resolve every name against the brain BEFORE reaching for external lookups.

Contract

This skill guarantees:

• Works with ANY meeting recorder — AI notetaker export, webhook payload, share link, raw audio transcription, or manual paste. The normalized transcript record (below) is the contract; per-source fetch/parse is the host agent's job
• One brain page per REAL meeting — multi-meeting recordings are split first
• Meeting page created with attendees, summary, key decisions, action items, notable quotes
• Speakers resolved by evidence, never by guess
• Recorder auto-summaries treated as CLAIMS, not facts — every surprising claim passes the consistency check before it touches an entity page
• EVERY attendee gets a people page (created or updated)
• EVERY company discussed gets entity propagation
• Timeline entries on ALL mentioned entities (timeline merge)
• Back-links created bidirectionally
• Meeting is NOT fully ingested until enrich runs for every entity
• The meeting is never REPORTED as ingested until the verification checklist (below) passes — every quote grounded, every slug backed by a page and a timeline backlink, every speaker resolved or flagged
• The narrated SEQUENCE is verified independently of substance: a sequence contradiction BLOCKS ingestion until fixed or explicitly waived by the user

Every attendee and company mentioned MUST get a back-link from their page to the meeting page. An unlinked mention is a broken brain.

Any recorder, one pipeline

Meeting content arrives from many sources: an AI notetaker (Granola and Circleback are common examples), a phone voice memo, a video-call transcript export, or a transcript the user pastes directly. Do NOT build per-vendor pipelines or paraphrase this skill in ad-hoc instructions — normalize whatever the source provides into the transcript record below, then run the shared phases. Source-specific logic ends at normalization.

The normalized transcript record

Before running the pipeline, reduce the input to this shape (mentally or as a scratch file — it does not get written to the brain as-is):

source: "<recorder name, or 'manual'>"
source_id: "<unique recording id from the source, if any>"
title: "Meeting Title"
date: YYYY-MM-DD
time: "HH:MM TZ"               # null if unknown
duration: "45m"                # null if unknown
attendees:                     # the SOURCE'S notion of who was there —
  - name: "..."                # may need correction during speaker resolution
    email: "..."               # only if the source provides it
    role: "..."                # only if known
transcript_segments:           # structured form when the source diarizes
  - speaker: "..."             # resolved name OR "UNKNOWN_N" if unresolved
    speaker_raw: "..."         # the source's raw speaker label, for traceability
    text: "..."
raw_transcript_text: "..."     # the complete transcript. NEVER truncate.
source_summary: "..."          # the recorder's AI summary if present — a CLAIM, not a FACT
source_url: "..."              # link back to the source platform, if any

Invariants:

• raw_transcript_text is complete and untruncated. Always.
• attendees is a claim by the source. People invited ≠ people present.
• source_summary is TWO lossy layers deep (speech-to-text, then AI summarization). Both layers confabulate. Verify before writing anything from it into the brain.

Retain the raw transcript when the source provides one: file it as a sidecar page (e.g. meetings/YYYY-MM-DD-{slug}-transcript) or keep the source file reachable, and link it from the meeting page. The transcript is the canonical evidence for every quote and claim check downstream.

Redact before you retain. A raw transcript routinely captures pasted secrets and PII (a read-aloud API key, a screen-shared token, a private phone number). Before writing the sidecar, scan for secret-shaped strings (sk-…, ghp_…, AKIA…, bearer tokens, long hex/base64 blobs) and PII, and redact matches to labeled placeholders — same deterministic deny-list / runPrivacyLint model as conversation-archive. "Untruncated" means the transcript's substance, never a live credential.

Phases

Phase 1: Normalize the input

Build the transcript record from whatever arrived. If the input is malformed (empty transcript, summary-only payload with no transcript, in-progress recording), STOP — do not create a meeting page from a summary alone. Surface the problem to the user.

For raw transcript files with no structure at all, gbrain capture is the preferred entry (it handles dedup and frontmatter routing); this pipeline is for building structured meeting pages.

Phase 2: Split detection — one recording is not always one meeting

A single recording is often several distinct meetings stitched together (a recorder left running across back-to-back sessions). Detect this BEFORE page creation, so each real meeting becomes its own page and dedupes/enriches correctly.

Split signals (one is enough to investigate; two or more = split almost certainly):

• Roster shift — a new person arrives mid-transcript (a greeting deep into the file), or the speaker set in the back half differs from the front
• Topic hard-cut with no continuity between the halves
• Context reset — "ok, next one", a fresh intro round, a restart phrase
• The source's own title/agenda names multiple sessions

When a split is detected:

1. Find the boundary segments — the exact points where roster/topic flips.
2. Partition the segments into N contiguous chunks, one per real meeting. Never drop or duplicate a segment; the union must equal the original, in order.
3. Run the remaining phases once per chunk → N separate meeting pages, each with its own corrected attendees, title, and time.
4. Cross-link the sibling pages ("same recording, session k of N") and note the shared source_id so dedup never re-merges them.

Borderline judgment: same people + one flowing conversation that wanders topics = ONE meeting; don't over-split. The test is roster + hard context break, not "the topic changed." If you genuinely cannot tell, surface the boundary to the user rather than guessing.

Phase 3: Dedup across recorders

Users increasingly run two recorders at once as a backup. Before creating a page, check whether the same meeting already exists: gbrain search "{title or attendee names}", then match by date ± 1 day + attendee overlap ≥ 50% + similar title.

• If a page exists, MERGE into it instead of creating a duplicate: build from the RICHER transcript, record both source ids in frontmatter.
• Source priority (which diarization to trust) is not source completeness (which transcript is fuller). One recorder may capture 20% of a session the other captured fully. Compare lengths; keep the fuller transcript as the grounding evidence.

Phase 4: Speaker resolution — before writing the page

Recorders ship anonymous labels (UNKNOWN_N, Participant 2, microphone) and sometimes confidently WRONG names. Resolve by evidence:

1. Start from the source's attendee list, corrected by any roster evidence the user can provide (an invite list, an event page, "it was just me and charlie-example").
2. Never guess. When uncertain, write [Room] or UNKNOWN and flag it. A wrong attribution is worse than no attribution.
3. Cross-reference the brain: gbrain search "{name}" for each candidate; read their page before accepting an identification.
4. Assign each named speaker a confidence: high (roster-confirmed), medium (named unambiguously in the transcript), low (inferred from content — flag explicitly).
5. Content-identity check: for every named speaker who claims a role/company/product in their own words ("I founded X", "at my company Y we…"), verify the claim against that person's brain page. If the named person's established identity CONTRADICTS what the speaker says about themselves, the recorder substituted the wrong person — resolve by identity, not by name, and reattribute the whole track.
6. Phantom-speaker check: if the recorder reports MORE distinct speakers than the known attendee count, suspect over-splitting — one real voice diarized into two labels. Tells: two labels never address each other, or hand off mid-thought. Collapse phantoms into the real attendee.
7. User ground truth overrides everything. If the user states who was in the room, that beats the recorder's diarization AND the roster. Reattribute, fix the page, and never re-litigate a room the user has confirmed.
8. Speech-to-text garbles names constantly. Before creating a NEW person page from a transcript-only name, search the brain for plausible spelling variants of the surname; default assumption is that a near-miss IS the existing person with a mangled name. Update the existing page and record the variant as an alias rather than creating a duplicate.

Phase 5: Create meeting page

# {Meeting Title} — {Date}

**Attendees:** {list with links to people pages}
**Date:** {YYYY-MM-DD}
**Duration:** {if available}

## Summary
{3-5 bullet key outcomes}

## Key Decisions
{Decisions with context. If none: _No decisions — discussion only._}

## Action Items
{Tasks with owners and deadlines. If none: _None — exploratory conversation._}

## Notable Quotes
{Verbatim from the transcript, attributed, `>` blockquotes.
If none: _No notable quotes — operational/logistics meeting._}

## Discussion Notes
{Structured notes by topic}

The four required sections are Summary, Key Decisions, Action Items, and Notable Quotes — additional sections (Discussion Notes, a link to the transcript sidecar) are additive, never replacements. An empty section always carries an explicit reason; a bare - None. is a dodge, not an answer.

Quotes are VERBATIM. Write what was said the way it was said — a paraphrase in a blockquote is a fabricated quote.

Phase 6: Claim verification + consistency check (gate for every entity write)

Recorder summaries inject false facts: speech-to-text garbles proper nouns, and AI summaries turn banter into commitments. Before writing ANY of the following claim types to a person/company page (compiled truth, frontmatter, or timeline), verify:

Consistency check — transcript support alone is NOT sufficient. A claim can be faithfully transcribed and still wrong. Every claim that passes the transcript bar ALSO gets:

1. Brain contradiction check. gbrain query "{entity}" and read the relevant pages. Does the new claim CONTRADICT established brain truth? When it does, the ESTABLISHED truth wins by default — flag the conflict to the user, don't silently overwrite. New claims override old truth only with explicit, verbatim, unambiguous transcript support, and even then the change is flagged in the ingest report.
2. Logic/plausibility check. Is the claim POSSIBLE given what else is known? Two people can't both independently "start" the same project; a company founded last year can't have been acquired five years ago. A logical impossibility means a probable garble — investigate before writing.
3. Surprise = signal. If a claim would make the user say "wait, what?", that surprise is exactly when these checks are mandatory. Boring claims ("discussed metrics", "attended") pass on transcript verification alone; surprising claims need every layer. Don't rationalize surprise into a story that fits — surface it as a question.

Downgrade protocol: if the transcript supports only an inference, record it as an explicitly-uncertain note on the meeting page — never in an entity page's compiled truth or frontmatter.

Propagation rule: a claim that fails verification must not fan out. Do not copy it to other entity pages or timeline entries. A false claim written to five pages costs five corrections.

Phase 7: Attendee enrichment (MANDATORY)

For EACH attendee:

1. gbrain search "{name}" — does a people page exist?
2. If NO → create via the enrich skill (skills/enrich/SKILL.md). Every person who was actually IN the meeting gets a page, even a thin one. Skip only ephemeral third-party mentions (a name invoked about someone not present, with no standalone context) and non-participants (a server taking orders).
3. If YES → update compiled truth with meeting context (subject to Phase 6).
4. Add a timeline entry on the person's page: gbrain timeline-add {person-slug} {date} "Attended {meeting-title}"

Back-link known people who are MENTIONED or SPEAK in the transcript too, not just attendees — but high-confidence identifications only. Never backlink a garbled name or a low-confidence guess; a wrong backlink pollutes the graph worse than a missing one.

Note: Once the meeting page is written via gbrain put, the auto-link post-hook automatically creates attended links from the meeting to each attendee whose page is referenced as [Name](people/slug). You don't need to call gbrain link for attendees. You DO still need gbrain timeline-add for dated events (auto-link only handles links, not timeline entries).

Phase 8: Entity propagation + timeline merge (MANDATORY)

For each company, project, or concept discussed:

1. Check the brain for an existing page (gbrain search, then gbrain get).
2. Create/update as needed (claims subject to Phase 6).
3. Add a timeline entry referencing the meeting.
4. Back-link from entity page to meeting page.

Timeline merge: the same event appears on ALL mentioned entities' timelines. If alice-example met charlie-example at acme-example, the event goes on alice-example's page, charlie-example's page, AND acme-example's page. For a multi-company session (e.g. group office hours), disaggregate the feedback per company — each company's timeline entry carries its own content, not a blob about the whole session.

If the meeting contains original thinking worth extracting beyond the page itself, chain into skills/signal-detector/SKILL.md after ingestion.

Phase 9: Sync

gbrain sync to update the index.

Verify before declaring done (HARD GATE)

The write phases do the work; this phase verifies the work was actually done. Run the checklist on the finished page — every item, every meeting, including "quick" logistics meetings. Never report a meeting as ingested until every item passes. Saying "ingested" first and fixing later is a contract violation; a false completion report is worse than an honest partial one.

V1 — Required sections have substance.

• ## Summary carries real outcomes (2+ bullets or a few substantive sentences), not one vague line.
• ## Key Decisions, ## Action Items, and ## Notable Quotes each have real content OR an explicit reason (_None — exploratory conversation._).
• A bare - None. or _n/a_ written to silence the checklist is a violation. Before writing "none", confirm against the transcript that there truly were no decisions/commitments/quotes worth keeping.

V2 — Every people/companies slug has a page AND a timeline backlink. For each person/company slug referenced by the meeting page:

gbrain get people/{slug}          # page exists?
gbrain timeline people/{slug}     # has an entry pointing back at this meeting?

A slug with no page means Phase 7/8 was skipped — go do it. A page with no timeline entry for this meeting means the merge was incomplete — add it.

V3 — Speaker map resolved. No Participant N / UNKNOWN_N / raw recorder labels remain in the page without either a resolution or an explicit uncertainty flag ([Room], ⚠️ attribution uncertain). Every named speaker carries a confidence from Phase 4. An unflagged anonymous label means speaker resolution was skipped.

V4 — Every quote grounded VERBATIM in the transcript.

• Deterministic check (transcript retained): for each > blockquote, verify its contiguous span appears in the transcript sidecar. Filler words (like, you know, I mean) may be stripped from both sides; a genuine quote still shares a long contiguous run of content words, a fabricated one does not.

  gbrain get meetings/{date}-{slug}-transcript   # then locate each quote span

• Prompt checklist (no transcript retained): re-read the source notes and attest that each quote traces to them word-for-word.
• When a quote fails grounding, the fix is almost always to restore the spoken phrasing (or pick a cleaner contiguous span) — NOT to delete the quote, and never to keep the paraphrase inside the blockquote.

V5 — Fabricated-attendee sanity checks. Recorders confidently invent names and emails for unlabeled speakers.

• An attendee name that appears NOWHERE in the transcript or roster evidence did not survive the evidence — treat it as a guess. Identify the real person from in-call tells (companies, shared history) or remove the name.
• An attendee email whose domain doesn't match the person's claimed org is a fabrication suspect (recorders commonly grab the host's domain). Verify the real address or clear the field.
• When either fires: do NOT auto-rename or auto-fill. Read the transcript, resolve by evidence, correct the page + frontmatter + backlinks, then re-run this checklist.

V6 — Sequence verify (order, not substance). A meeting page can be right on depth and wrong on order — they are independent failure axes, and V1–V5 never look at order. Verify the narrated sequence:

1. Extract event atoms. Walk the page body in document order and list each narrated sub-event as {phase, place, people} — where phase is its position relative to the meeting's central event (before / during / after) as the PROSE claims it.
2. Deterministic checks (agent-executed, mechanical — no judgment needed):
   • PHASE_INVERSION (hard): an atom narrated as "before" appears after the central event in the document's sequence (or vice versa). Example: the page narrates the debrief of alice-example's pitch, then narrates the pitch itself as if still upcoming.
   • TELEPORT (hard): the same person is placed in two non-adjacent locations with no transit or movement narrated between them. Example: alice-example is in the car en route in one paragraph and already inside the acme-example office in the next, with nothing connecting the two.
3. Day-timeline corroboration (soft):

   gbrain day {date}

   assembles that day's events and timeline entries across the whole brain.
   • DAY_TIMELINE_GAP: a narrated participant who never appears in the day's assembled timeline is a SIGNAL, not a hard fail — most often it means their timeline entry was never written (go fix Phase 7/8), and occasionally it means the narration names someone who wasn't there. Investigate; don't auto-block.
4. Verdict — PASS or BLOCK.
   • No hard contradiction → PASS. Proceed to report.
   • Any PHASE_INVERSION or TELEPORT → BLOCK. The meeting is NOT ingested. Fix the narration (re-read the transcript for the true order) and re-run V6 — or, if the user explicitly says the order is fine as written, record a waive. A waive is logged in the report as acknowledged, NOT resolved: sequence: WAIVED by user — {contradiction} stands.
   • Genuinely ambiguous order (flashbacks, prose that implies but doesn't state a sequence) is a judgment call, not a deterministic class — flag it in the report, don't block on it.

The loop: fix → re-check → fix, until every item passes (or V6 is explicitly waived). Only then report.

Sensitive meetings

If the title or transcript signals legal or deeply personal content (deposition, attorney, counsel, privileged, health): keep the page minimal and factual, do not extract biographical color into other pages, and prefer restraint on back-links. When in doubt about whether content should propagate, ask the user.

Output Format

Meeting page created AND the verification checklist passed. Report: "Meeting ingested: {N} attendees enriched, {N} entities updated, {N} action items captured. Verification: passed. Sequence: PASS." If the sequence check was waived, say so explicitly: "Sequence: WAIVED by user — {contradiction} stands (acknowledged, not resolved)." If the recording was split, report one line per resulting meeting page. If a claim was withheld or a contradiction flagged by Phase 6, list each flag — the user resolves them, not silence. If any checklist item cannot be made to pass, report the meeting as NOT ingested and name the failing item.

Anti-Patterns

• Creating the meeting page without enriching attendees
• Skipping entity propagation ("I'll do that later")
• Not merging timelines across all mentioned entities
• Creating attendee stubs without meaningful content
• Filing meeting pages without cross-linking to all participants
• Building a per-vendor pipeline or paraphrasing this skill in ad-hoc instructions instead of normalizing to the transcript record
• Treating a recorder auto-summary name or claim as fact without transcript verification
• Writing a summary's relationship/role/ownership claim into an entity page without finding the verbatim transcript line
• Writing a garbled proper noun bare instead of resolving canonical spelling
• Fanning an unverified claim out to multiple entity pages
• Silently overwriting established brain truth with a new meeting claim instead of flagging the contradiction
• Guessing a speaker identity instead of writing [Room]/UNKNOWN and flagging
• Truncating a transcript, or paraphrasing inside a quote blockquote
• Ingesting one page for a recording that contains two meetings
• Reporting "ingested" before the verification checklist passes
• Writing - None. under a required section to silence the checklist without confirming against the transcript
• Skipping the checklist because "it's just a quick logistics meeting"
• Declaring a page ingested while a sequence contradiction stands unresolved and unwaived
• Treating a user waive as a resolution — a waive is an acknowledgment; the contradiction is still in the page
• Passing a page that puts a person in two non-adjacent places with no transit between them
• Re-checking substance in the sequence pass (or order in V1–V5) — the axes are orthogonal by design