name: eiirp version: 1.1.0 prompt_version: 1 description: | Everything In Its Right Place. The universal post-work organizer. After any significant work session, EIIRP runs a 7-phase audit: (1) inventory every output, (2) walk taxonomy to decide where each lands, (3) check schema-pack consistency against the brain's actual shape, (4) file enriched brain pages, (5) audit the skill graph for DRY+MECE, (6) verify resolvability, (7) report. Named after the Radiohead song. Nothing produced during significant work lives only in chat — knowledge becomes permanent, patterns become reusable. Also carries the always-on auto-fire gate: when >=500 words of structured analysis on a user-shared document is about to be delivered, file the brain page first, then deliver the analysis with the link in that same reply. triggers:

"everything in its right place"
"eiirp"
"store this research"
"put this in the brain"
"file this properly"
"where does this research go"
"make this permanent"
"archive this research"
"archive this research thread"
"brain this"
"file all of this"
"organize all of this"
"organize all of this work"
"make this re-doable"
"DRY this up"
"check everything is in the right place"
"analyze this document"
"deep analysis"
"review this report" tools:
search
query
get_page
put_page
add_link
add_timeline_entry mutating: true writes_pages: true

EIIRP files across the full canonical set — the actual destination

per page is decided by brain-taxonomist consulting the active schema

pack via `gbrain schema show --json`. List the gbrain-recommended set

of canonical directories here so the filing-audit gate passes; on

brains with custom packs, the routing surface is broader and routes

through loadActivePack at write time.

writes_to:

people/
companies/
deals/
meetings/
concepts/
projects/
civic/
writing/
analysis/
guides/
research/ filing_exempt: true

The auto-fire gate section below was merged from an upstream

deep-analysis auto-filing skill:

upstream: deep-analysis-brain-auto distinct_from:

name: brain-taxonomist reason: "brain-taxonomist classifies individual pages at write time (the filing GATE). EIIRP orchestrates the full post-work LIFECYCLE — inventory + taxonomy + schema + skillify + verify."
name: ingest reason: "ingest handles NEW content from external URLs/media. EIIRP handles COMPLETED research that needs to be decomposed and filed across multiple brain locations."
name: skillify reason: "skillify is the meta-skill for turning a feature into a tested skill. EIIRP calls skillify when Phase 5 identifies a reusable pattern."
name: signal-detector reason: "signal-detector ambiently captures the USER's ideas + entity mentions on every inbound message. EIIRP's auto-fire gate files the AGENT's own deliverable analysis at reply time. Both are always-on; they watch opposite directions of the conversation."
name: meeting-ingestion reason: "meeting-ingestion (like idea-ingest, media-ingest, voice-note-ingest, book-mirror) is a dedicated pipeline with its own brain-write logic. The auto-fire gate EXEMPTS dedicated-pipeline content — it never double-files."

EIIRP — Everything In Its Right Place

"Everything in its right place" — Radiohead, Kid A

Contract

After any significant work, EIIRP organizes ALL outputs across two domains:

Knowledge domain (brain):

Every piece of knowledge lands in the correct brain location.
All sources are cited and linked.
The active schema pack is updated if a new content type emerged.
Entity pages created/updated with cross-links.

Capability domain (skills): 5. Every reusable pattern becomes a composable skill. 6. Existing skills are audited for DRY violations. 7. Skill graph is MECE — no gaps, no overlaps, no ambiguous routing.

The meta-guarantee: Nothing produced during significant work lives only in chat. Knowledge → brain. Patterns → skills. Everything in its right place.

When to Use

After completing a deep research thread.
After building something new (code, pipeline, workflow).
After a multi-source analysis that produced significant findings.
When the user says "EIIRP", "organize this", "DRY this up", "make this re-doable".
When a work session produced both knowledge AND new capabilities.
When you notice skill overlap, duplication, or gaps.

Auto-Fire Gate — file before you deliver (ALWAYS-ON)

Convention: see conventions/brain-first.md — this is its write side. Substantial analysis belongs in the brain, not only in chat.

Unlike the 7-phase audit above (which the user invokes after a work session), this gate is an always-on agent-side convention, like signal-detector: the agent applies it on every substantive reply, not when a trigger phrase routes here. Always-on is a harness-routing convention that a well-behaved agent follows — not a mechanical guarantee; nothing in the gbrain runtime blocks a reply if the skill never loads.

The moment of evaluation is delivery, not request. The gate evaluates when substantial analysis (>=500 words of structured output on a user-shared document) is ABOUT to be delivered — the analysis is done and the reply is being composed. At that moment, file the brain page FIRST, then deliver the analysis plus the page link in that same reply. The user should never have to ask "did you file this?"

Fire conditions (all three must hold)

The user shared a document — a PDF, a file attachment, a link to a doc, or pasted long-form content.
The reply about to be delivered contains substantial analysis:

=500 words of structured output (findings, recommendations, or extracted data — not restatement or formatting).
The content is knowledge worth re-finding — someone reading the brain months later would want this page.

Does NOT fire

Quick answers ("what page is X on?", "what date is on this?").
Simple lookups, or forwarding a document unchanged.
Purely operational content (task lists, calendar items, status pings).
Documents already flowing through a dedicated pipeline (next list).
Users who have turned auto-filing off (storage policy below).

Dedicated-pipeline exemptions

These pipelines own their brain-write logic; the gate must NOT double-file on top of them. If one of these is the right route, invoke it and let it file:

skills/meeting-ingestion/SKILL.md — transcripts + attendee propagation
skills/idea-ingest/SKILL.md — articles with author/publication metadata
skills/media-ingest/SKILL.md — bulk file ingestion
skills/voice-note-ingest/SKILL.md — voice notes
skills/book-mirror/SKILL.md — personalized book mirrors

Filing mechanics (before the reply goes out)

Path — consult skills/brain-taxonomist/SKILL.md. It reads the active schema pack (gbrain schema show --json); document analysis usually lands under analysis/ or research/, entity-centric findings under people/ or companies/.
Write — file via capture:
```
gbrain capture --file <analysis.md> --slug <taxonomist-path>
```
(or put_page over MCP on thin-client installs). Full frontmatter per Phase 4a. The page must be self-contained — a reader months later gets the full picture without the chat thread.
Link in the SAME reply — the analysis inline (conversational, not just "see the brain page") plus a link line to the filed page, formatted per skills/brain-link-discipline/SKILL.md (it owns the link format and the resolve-verification step). Multiple pages → list every link.
First-fire notice. The very first time the gate fires for a user, append one line to the delivery reply so they learn about auto-filing at the moment it starts, not after: Auto-filed to <path>; say "stop auto-filing" to disable. Record that the notice was given (a per-user storage-policy note) so it never repeats. Alternatively, ask once at setup and record the policy before the first write.

Per-user storage policy

Auto-filing is a DEFAULT, not a mandate — a per-user storage policy. If the user says to stop auto-filing document analyses (or asks for chat-only handling of a specific document), record that preference and stop firing the gate: deliver the analysis without a page. Re-enable on request.

Relationship to the 7-phase audit

The gate is the single-deliverable fast path: one document → one page → link in the delivery reply. A full work session still deserves the complete EIIRP pass below; the gate just ensures no individual analysis waits for it.

Phase 1: INVENTORY — What did we produce?

Scan the current session/thread and identify ALL outputs across both domains.

Knowledge outputs

□ Primary findings (the synthesis)
□ Source documents (URLs, PDFs, articles, tweets)
□ Entity mentions (people, companies, organizations, places)
□ Concepts/frameworks (reusable mental models)
□ Data artifacts (structured data, timelines, statistics)

Capability outputs

□ New skills created or modified
□ Scripts/code written (should they be in lib/ or scripts/?)
□ Methodology used (search patterns, source chains, verification steps)
□ Workflows that could be automated (cron, pipeline, webhook)
□ Patterns that will recur (→ candidate for skillification)

Produce a manifest:

## EIIRP Manifest
- Topic: [topic]
- Date: [date]
- Knowledge outputs: [count] (sources, entities, concepts)
- Capability outputs: [count] (skills, scripts, patterns)
- Reusable methodology: [yes/no — describe if yes]

Phase 2: TAXONOMY — Where does each piece go?

Read the active schema pack first (the single source of truth for filing decisions in v0.39+):

gbrain schema show --json

The pack's page_types[] lists every directory the brain accepts plus the primitive each maps to. Walk it for each output and pick the directory whose path_prefixes matches the content's primary subject.

If brain-taxonomist is installed, INVOKE IT for ambiguous cases. It runs the same decision protocol against the active pack and gives you a single recommended filing path with reasoning.

Output: a filing plan table:

| Content | Brain path | Action |
|---------|-----------|--------|
| Primary research | reference/.../page.md | CREATE |
| Person X | people/x-slug.md | CREATE |
| Person Y | people/y-slug.md | UPDATE (already exists) |
| ... | ... | ... |

Phase 3: SCHEMA CHECK — Does the active pack cover this content?

This is where EIIRP closes the schema-derivation loop. If the work produced content that doesn't fit any existing page_types, propose adding a new type via the v0.39 cathedral:

# What's emerging in the brain that the active pack doesn't cover?
gbrain schema detect --json

# LLM-refined suggestions (heuristic when no API key set).
gbrain schema suggest --json

# Review what's pending; promote or ignore each candidate.
gbrain schema review-candidates --json
gbrain schema review-candidates --apply <prefix-or-type-name>

Confidence floor: when gbrain schema suggest returns confidence < 0.6 on a proposed type, DO NOT auto-apply. Surface the suggestion to the user and let them choose. The schema-cathedral ships the primitives; EIIRP enforces the human-in-the-loop gate.

If schema needs change:

Propose the addition to the user before running review-candidates --apply.
Document the change in the commit message of the next sync.
The schema-pack engine writes the delta to ~/.gbrain/schema-pack-deltas/ — review and merge into the active pack via gbrain schema edit (or hand-edit the YAML).

Phase 4: FILE — Create enriched brain pages

For each item in the filing plan:

4a. Primary research page

Use the brain page template. MUST include:

Proper frontmatter (type, title, date, tags, sources)
State section — current status/key findings
Sources section — every source with URL, author, date, language
Timeline section — chronological development
Entity links — backlinks to all related brain pages
See Also — related concepts, reference pages

4b. Entity pages (people, companies)

For each entity mentioned:

Check if a brain page exists (gbrain search "<name>" or gbrain get people/<slug>).
If exists: update State, append Timeline entry citing this research.
If not: create with enrichment.

4c. Commit and verify

After ALL pages are written, run gbrain sync (or commit + push in the brain repo). Verify every link resolves.

Phase 5: SKILL GRAPH AUDIT — DRY + MECE on capabilities

This phase operates on the SKILL graph, not just the research.

Read-only plugin installs: the shipped plugin snapshot is not writable. New or updated skills and lib/ extractions target your own project skill directory or a brain-resident skillpack (gbrain skillpack init-brain-pack), never the shipped snapshot. Phases 1-4 and the gbrain CLI checks in Phase 6 work everywhere.

5a. New pattern identification

Ask: did this work reveal REPEATABLE patterns that will recur?

Indicators of a reusable pattern:

You used a specific sequence of searches across multiple sources.
You followed a specific verification/cross-referencing methodology.
You wrote code that could be parameterized for different inputs.
The output format is generalizable.
The user is likely to ask for similar work on a different topic.

For each identified pattern:

Identify the composable pieces (DRY, MECE):
- Shared logic → lib/ (not copy-pasted into skills)
- Search methodology → skill or lib function
- Output template → brain template or skill phase
- Filing logic → already covered by brain-taxonomist + active pack
DRY check via the v0.19 resolver:
```
gbrain check-resolvable
```
Look for overlapping triggers or unreachable skills.

5b. Existing skill audit

For ALL skills used or touched during this work, check:

Were any skills BYPASSED? (did you do something manually that a skill should handle?)
Are there skills that OVERLAP with what you just did? (merge candidates)
Is shared code copy-pasted between skills? (extract to lib/)

The MECE question: If someone asked for this exact work again tomorrow on a different topic, which skills would they invoke? Is the path clear and unambiguous? If not, fix the routing.

5c. Present the plan

## Skill Graph Changes

### New skills to create
1. **[skill-name]** — [what it does]
   - DRY check: [clean / overlaps with X]
   - Recommendation: [create / merge into X]

### Existing skills to update
1. **[skill-name]** — [what changed, why]

### Code to extract to lib/
1. **lib/[name].ts** — [what it does, which skills use it]

### Skills to merge or deprecate
1. **[skill-A] + [skill-B]** → [merged-skill] — [why]

On approval: invoke /skillify for each new/modified skill.

Phase 6: CHECK_RESOLVABLE — Verify everything routes

After all filing and skillification:

gbrain check-resolvable                         # routing-table reachability
gbrain doctor --json                            # health surface
gbrain search "<topic keywords>"                # brain pages findable
gbrain orphans                                  # any pages without inbound links?

Confirm:

All brain pages have proper frontmatter against active schema pack
All entity pages are cross-linked
Any new skills have routing entries in skills/RESOLVER.md (where the skills tree is writable)
No DRY violations (no duplicated logic across skills)
No MECE violations (no ambiguous routing between skills)
Active schema pack updated if new content types emerged
gbrain doctor reports schema_pack_consistency: ok

Phase 7: REPORT — Summary

## EIIRP Complete: [Topic]

### Brain pages created/updated
- [path] — [description]
- ...

### Entity pages
- [path] — [created/updated]
- ...

### Schema changes
- [none / description of changes + which pack delta file]

### Skills identified
- [skill-name] — [status: created / merged / deferred]
- ...

### Resolver status
- DRY check: [clean]
- MECE audit: [clean]
- Active pack: [name] v[version]
- schema_pack_consistency: [ok / warn — pct untyped]

Output Format

EIIRP produces a single Phase 7 report block. Plain markdown:

## EIIRP Complete: [topic]

### Brain pages created/updated
- [path] — [description]

### Entity pages
- [path] — [created|updated]

### Schema changes
- [none | description of changes + which pack delta file]

### Skills identified
- [skill-name] — [status: created|merged|deferred]

### Resolver status
- DRY check: [clean|N violations]
- MECE audit: [clean|N overlaps]
- Active pack: [name] v[version]
- schema_pack_consistency: [ok|warn — N% untyped]

Always machine-readable: stable section headers + bullet-per-item. The report doubles as a sync checkpoint for downstream skills (skillpack-check reads it; doctor cross-references the pack version).

Anti-Patterns

Hardcoding directory tables in EIIRP's logic. Every filing decision reads gbrain schema show --json. Users on gbrain-recommended AND custom packs MUST get the right behavior automatically.
Auto-applying low-confidence schema suggestions. Confidence < 0.6 from gbrain schema suggest means manual review is required. EIIRP surfaces it; the user accepts.
Skipping Phase 5 SKILL GRAPH AUDIT because "this was a one-off." If the work took >10 minutes, the methodology is probably reusable. Audit anyway; defer the skillify decision to the user.
Filing synthesis output by topic alone. Synthesis pages tied to a single source + reader are sui generis; they file under media/<format>/<slug>-personalized.md. See _brain-filing-rules.md "Sanctioned exception" section.
Treating non-English sources as secondary citations. Multilingual sources are first-class.
Delivering substantial document analysis without a filed page + link. The auto-fire gate files FIRST, then delivers analysis + link in the same reply. Never "I'll create the page" as a future action; never the link in a follow-up message; never wait for the user to ask.
Double-filing dedicated-pipeline content. Meeting transcripts, articles, bulk media, voice notes, and book mirrors have their own ingestion skills with their own brain-write logic. The gate exempts them.
Auto-filing after the user turned it off. Auto-filing is a per-user storage-policy default, not a mandate. Honor the recorded preference.

Hard Rules

Knowledge domain

Never leave research only in chat. If it took >10 minutes to produce, it gets a brain page.
Every source gets a citation. No "according to reports" without a URL.
Entity pages get updated, not just created. If a brain page exists, UPDATE it.
Schema changes require confirmation. The active pack is load-bearing.
Multilingual sources are first-class. Never treat non-English sources as secondary.

Capability domain

DRY is sacred. If the same logic appears in two skills, extract it to lib/.
MECE is sacred. Every trigger phrase routes to exactly one skill.
Composability over monoliths. Small skills that compose > one giant skill that does everything.
Skillify only what recurs. One-off work doesn't need a skill. Patterns that repeat 2+ times do.

Changelog

v1.1.0 — auto-fire gate merge (from an upstream deep-analysis auto-filing skill)

Merged the always-on auto-fire gate: when >=500 words of structured analysis on a user-shared document is about to be delivered, file the brain page first, then deliver analysis + link in that same reply.
Filing routes through brain-taxonomist (active schema pack) + gbrain capture instead of the donor's git-commit mechanics; the donor's direct GitHub-API link check was dropped in favor of the brain-link-discipline skill's link format + verify step.
Donor examples and origin story genericized per CLAUDE.md privacy rules; added dedicated-pipeline exemptions and the per-user storage-policy off switch.

v1.0.0 — gbrain v0.39.0.0

Initial port from upstream OpenClaw. Genericized — no references to private fork names per CLAUDE.md privacy rules.
Phase 3 SCHEMA CHECK rewritten to consume the v0.39 cathedral CLI (detect | suggest | review-candidates) instead of a private brain/schema.md.
Phase 5 SKILL GRAPH AUDIT calls gbrain check-resolvable instead of upstream scripts/skill-dry-check.mjs.
Phase 6 verification uses gbrain doctor's schema_pack_consistency check (T7) for the persistent surface.

eiirp