Brain:wiki Skill for Claude

Browse, search, and generate Wikipedia-style knowledge articles from the brain. Auto-generated from brain DB entities, emails, docs, and decisions.

4k tokens

context cost

the whole folder, loaded on every use

files

instructions only

copies elsewhere

how many repositories repackaged it

196

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/coco-research/coco --skill brain:wiki

The instruction itself

10 sections, as written by the author

/brain-wiki — CoCo Knowledge Articles

Browse, search, and generate Wikipedia-quality articles about people, systems, teams,

and org units across all CoCo brain DB projects.

Articles are auto-generated from the brain DB by the daily knowledge engine cron

(~/.coco/knowledge/cron.py). Each article synthesizes all evidence available about

an entity — decisions, events, relationships, tasks — into a structured, versioned

knowledge artifact.

Commands

`/brain-wiki [entity]` — Show article (or list all)

With entity name: Look up and display a knowledge article.

python3 ~/.claude/skills/brain/scripts/brain/brain_cli.py wiki --name "{entity}"

Display format:

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
{Title}                                    [{type}]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Infobox:  Projects: {list} | Role: {role} | Team: {team}

{Summary paragraph}

## Role
{content}

## Relationships
{content}

## Timeline
{content}

## Decisions
{content}

## Open Questions
{content}

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Generated: {date}  ·  Confidence: {0-100}%  ·  Sources: N chunks
GID: {uuid}  ·  v{version}

If article not found → run wiki-search with the entity name as query and show top 3 candidates:

No article found for "{entity}". Did you mean:
  1. {title}  ({confidence}%)  — /brain-wiki {gid}
  2. {title}  ({confidence}%)
  3. {title}  ({confidence}%)

Warnings to show inline:

If confidence < 30%: ⚠ Low confidence — this article needs more source data. Run /brain-update after adding more context.
If pending merge proposals exist for this entity: ℹ Possible duplicate: matches "{other_name}" ({similarity}%) — run /brain-wiki review-merges to resolve

Without entity name: List all available articles.

python3 ~/.claude/skills/brain/scripts/brain/brain_cli.py wiki-search "*" --limit 50

Display as table:

KNOWLEDGE BASE  ·  N articles
═══════════════════════════════════════════════════════════
Name                    Type       Confidence   Updated
─────────────────────────────────────────────────────────
Alice Example               person     87%          2h ago
VendorPortal            system     91%          yesterday
DataPipeline            system     76%          2d ago
Platform Team           team       82%          2d ago
...

`/brain-wiki search <query>` — Unified FTS5 + semantic search

python3 ~/.claude/skills/brain/scripts/brain/brain_cli.py wiki-search "{query}"

Runs both FTS5 keyword search and MemPalace semantic search, merges via RRF.

Display format:

SEARCH: "{query}"  ·  N results  ·  FTS5 + semantic
══════════════════════════════════════════════════════════════
  #  Name                Type      Confidence  Projects     Updated
 ─────────────────────────────────────────────────────────────────
  1  {title}             {type}    {conf}%     {projects}   {time}
  2  ...

Run /brain-wiki {name} to read the full article.

If 0 results:

No articles found for "{query}".
Entity may not be in any brain DB yet, or articles haven't been generated.
Run: /brain-wiki generate  to generate articles for all brain entities.

`/brain-wiki generate [project]` — Generate / refresh articles

Generates or refreshes knowledge articles from brain DB evidence.

Procedure:

If a project is specified, confirm scope:

   Generate articles for project "{project}"?
   This will use Claude API (estimated $0.XX for N entities).
   [Y/n]

If no project specified, confirm all:

   Generate articles for ALL registered projects?
   Registered: {slug1}, {slug2}, ...  (N projects, ~N entities)
   Estimated cost: $0.XX  ·  Estimated time: N minutes
   [Y/n]

On confirmation, run:

   # Single project
   python3 ~/.coco/knowledge/cron.py --run --project {slug} --phases 2,3,5

   # All projects
   python3 ~/.coco/knowledge/cron.py --run --phases 2,3,5

Show phase-by-phase progress as output streams:

   Phase 2: Harvesting evidence...
     ✓ {project}: N entities, N evidence chunks

   Phase 3: Generating articles...
     ✓ Generated: Alice Example (confidence: 87%)
     ✓ Generated: VendorPortal (confidence: 91%)
     ~ Skipped:   3 entities (unchanged)

   Phase 5: Indexing...
     ✓ N articles indexed (FTS5)

   ─────────────────────────────────────────
   KNOWLEDGE ENGINE
   ================
   Articles generated:  N new, N updated
   FTS5 indexed:        N
   Estimated cost:      $0.XXX

   Articles written to: ~/.coco/knowledge/articles/
   Search with: /brain-wiki search "{project}"

Add --force flag to regenerate all articles regardless of staleness.

`/brain-wiki people` — Show cross-project people graph

Show all person-type articles and cross-project relationship statistics.

Procedure:

Query knowledge.db directly (do NOT invoke cron --dry-run, per review finding m4):

   import sys, sqlite3, json
   sys.path.insert(0, str(Path("~/.coco/knowledge").expanduser()))
   from schema import KNOWLEDGE_DB_PATH
   conn = sqlite3.connect(KNOWLEDGE_DB_PATH)

   # People articles
   people = conn.execute("""
       SELECT ge.canonical_name, ge.aliases_json, ge.merged_from_json,
              a.confidence, a.generated_at, a.version
       FROM global_entities ge
       LEFT JOIN articles a ON a.gid = ge.gid
       WHERE ge.type = 'person'
       ORDER BY a.confidence DESC NULLS LAST
   """).fetchall()

   # Pending merges
   merges = conn.execute("""
       SELECT COUNT(*) FROM cross_project_connections
       WHERE connection_type = 'proposed_merge'
   """).fetchone()[0]

   # Works-with edges
   edges = conn.execute("""
       SELECT COUNT(*) FROM cross_project_connections
       WHERE connection_type = 'works_with'
   """).fetchone()[0]

Display:

   PEOPLE GRAPH  ·  N people across N projects
   ════════════════════════════════════════════════════════
   Name                    Projects     Confidence   Updated
   ─────────────────────────────────────────────────────────
   Alice Example               my-project       87%          2h ago
   ...

   Works-with relationships:  N edges inferred
   Pending merge proposals:   N  — run /brain-wiki review-merges to resolve

If no people articles yet:

   No people articles found. Run /brain-wiki generate to build the knowledge base.

`/brain-wiki review-merges` — Review and approve entity merge proposals

Interactively review merge proposals (entities that may be duplicates).

Procedure:

List pending merges:

   python3 ~/.claude/skills/brain/scripts/brain/brain_cli.py wiki --list-merges

For each pending merge, show both entities' summaries side by side:

   MERGE PROPOSAL  (similarity: 92%)
   ══════════════════════════════════════════════════════════
   KEEP candidate A:                KEEP candidate B:
   ─────────────────────────────    ─────────────────────────
   Name: Alice Example                  Name: Alice Examplé
   GID:  {uuid-a}                   GID:  {uuid-b}
   Projects: project-a, project-b    Projects: vendor-integration

   Summary A: {2-3 sentences}       Summary B: {2-3 sentences}
   ══════════════════════════════════════════════════════════
   Action: [A=keep A | B=keep B | s=skip | q=quit]

On approval:

   python3 ~/.claude/skills/brain/scripts/brain/brain_cli.py wiki --approve-merge {gid_keep} {gid_remove}

This:

Reassigns all articles from gid_remove → gid_keep
Adds the removed entity's name to gid_keep's aliases
Deletes gid_remove from global_entities
FIX M6: uses delete-then-reinsert for articles_fts (not UPDATE, which fails on virtual tables):

DELETE FROM articles_fts WHERE gid=gid_remove then re-INSERT with gid_keep

On skip: record the skip decision (do not re-propose the same pair for 30 days).

Show completion summary:

   MERGE REVIEW COMPLETE
   =====================
   Approved:  N merges
   Skipped:   N pairs
   Remaining: N pending

`/brain-wiki install-cron` — Set up daily improvement cron

Install the daily knowledge engine job via macOS launchd.

Procedure:

Check that claude binary is resolvable first (the installer validates this):

   python3 ~/.coco/knowledge/cron.py --install

Show confirmation:

   KNOWLEDGE CRON INSTALLED
   ========================
   Schedule:       Daily at 02:00
   Claude binary:  {resolved path}
   Python binary:  {resolved path}
   Plist:          ~/Library/LaunchAgents/com.coco.knowledge-cron.plist
   Log:            ~/.coco/knowledge/cron.log

   To uninstall:  /brain-wiki uninstall-cron
   To test now:   python3 ~/.coco/knowledge/cron.py --run --dry-run

If claude binary not found, show the error from _find_claude_binary() with install instructions.

To uninstall:

python3 ~/.coco/knowledge/cron.py --uninstall

`/brain-wiki stats` — Show knowledge engine statistics

Display current state of the knowledge engine without running any generation.

Procedure:

Query knowledge.db directly:

import sqlite3, json
from pathlib import Path
conn = sqlite3.connect(Path("~/.coco/knowledge/knowledge.db").expanduser())

stats = {
    "entities":        conn.execute("SELECT COUNT(*) FROM global_entities").fetchone()[0],
    "articles":        conn.execute("SELECT COUNT(*) FROM articles").fetchone()[0],
    "fts_rows":        conn.execute("SELECT COUNT(*) FROM articles_fts").fetchone()[0],
    "pending_merges":  conn.execute(
        "SELECT COUNT(*) FROM cross_project_connections WHERE connection_type='proposed_merge'"
    ).fetchone()[0],
    "works_with":      conn.execute(
        "SELECT COUNT(*) FROM cross_project_connections WHERE connection_type='works_with'"
    ).fetchone()[0],
    "last_gen":        conn.execute(
        "SELECT MAX(run_at) FROM generation_log WHERE phase='3_generate' AND status='ok'"
    ).fetchone()[0],
    "last_sync":       conn.execute(
        "SELECT MAX(run_at) FROM generation_log WHERE phase='6_sync' AND status='ok'"
    ).fetchone()[0],
    "by_type":         conn.execute(
        "SELECT type, COUNT(*) FROM global_entities GROUP BY type"
    ).fetchall(),
}

Display format:

KNOWLEDGE ENGINE STATS
══════════════════════════════════════════════════
Entities:          N  (person: N, system: N, team: N ...)
Articles:          N  (FTS5 indexed: N)
Relationships:     N works_with edges
Pending merges:    N proposals awaiting review

Last generation:   {time ago}
Last MemPalace sync: {time ago}

Articles directory: ~/.coco/knowledge/articles/  (N files)
DB size:            {KB/MB}
══════════════════════════════════════════════════
Commands: /brain-wiki generate · /brain-wiki search · /brain-wiki review-merges

If knowledge.db does not exist:

Knowledge engine not initialized.
Run /brain-wiki generate to bootstrap, or /brain-wiki install-cron for daily automation.

Implementation Notes

FTS5 scoring: BM25 rank in SQLite FTS5 is negative (more negative = better match).

Score normalization: score = 1.0 / (1.0 + abs(rank)) — higher score = more relevant.

(FIX M5 from review findings.)

body_json → FTS5 text: FTS5 indexes plain text, not raw JSON. The engine extracts

section["content"] from each section in body_json before inserting into articles_fts.

(FIX C3 from review findings.)

articles_fts updates: Virtual tables cannot be bulk-UPDATEd. Always use

DELETE WHERE gid=? then re-INSERT for any gid change (e.g., merge approvals).

(FIX M6 from review findings.)

Project registration: Before the cron can harvest a project, it must be registered:

  python3 ~/.claude/skills/brain/scripts/brain/brain_cli.py wiki-register \
    --slug {slug} --db {path/to/project_brain.db}

brain-init Step 8 calls this automatically. (FIX M1 from review findings.)

Kill switch: If ~/.coco/disabled exists, all brain-wiki commands should exit silently

(consistent with CoCo kill switch convention).

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How to use it

Copy the folder

Take coco-research/brain:wiki from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.

Brain:wiki Skill for Claude

Install

The instruction itself

/brain-wiki — CoCo Knowledge Articles

Commands

/brain-wiki [entity] — Show article (or list all)

/brain-wiki search <query> — Unified FTS5 + semantic search

/brain-wiki generate [project] — Generate / refresh articles

/brain-wiki people — Show cross-project people graph

/brain-wiki review-merges — Review and approve entity merge proposals

/brain-wiki install-cron — Set up daily improvement cron

/brain-wiki stats — Show knowledge engine statistics

Implementation Notes

Other skills for the same job

How to use it

`/brain-wiki [entity]` — Show article (or list all)

`/brain-wiki search <query>` — Unified FTS5 + semantic search

`/brain-wiki generate [project]` — Generate / refresh articles

`/brain-wiki people` — Show cross-project people graph

`/brain-wiki review-merges` — Review and approve entity merge proposals

`/brain-wiki install-cron` — Set up daily improvement cron

`/brain-wiki stats` — Show knowledge engine statistics