/brain-wiki
Browse, search, and generate Wikipedia-style knowledge articles from the brain. Auto-generated from brain DB entities, emails, docs, and decisions.
$ npx -y skills add coco-research/coco --skill brain-wiki --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/brain-wiki
Context preview
The summary Claude sees to decide when to auto-load this skill.
Browse, search, and generate Wikipedia-style knowledge articles from the brain. Auto-generated from brain DB entities, emails, docs, and decisions.
SKILL.md
brain-wiki.SKILL.mdname: brain:wiki
description: "Browse, search, and generate Wikipedia-style knowledge articles from the brain. Auto-generated from brain DB entities, emails, docs, and decisions."
/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:**
1. 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]2. 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 2,3,53. 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}"4. 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:**
1. 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_Read more
name: brain:wiki description: "Browse, search, and generate Wikipedia-style knowledge articles from the brain. Auto-generated from brain DB entities, emails, docs, and decisions."
/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:**
1. 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]2. 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 2,3,53. 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}"4. 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:**
1. 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_Meet Coco. A superintelligent agent framework powered by an advisory board of 389 world-class minds. Scale your AI assistant into a complete engineering department with 142 skills, 277 commands, and persistent state. Universal compatibility. Local privacy. Free and open source.
Repo: coco-research/coco
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