Claude Code plugin for the Powerhouse Knowledge Vault. Enables AI agents and humans to query, create, connect, and verify knowledge notes stored as Powerhouse document models.
This plugin gives you (human or AI agent) the ability to manage a structured knowledge graph inside a Powerhouse reactor. It provides:
- 14 skills for knowledge management (seed, extract, connect, search, verify, health, graph, etc.)
- A knowledge-agent definition optimized for knowledge work via the Switchboard CLI
- Connection to a Powerhouse reactor via MCP or Switchboard CLI
- Access to the Graph Indexer — a relational index with keyword search, topic queries, provenance filtering, and AI-powered semantic search
The vault stores knowledge as bai/knowledge-note documents — atomic claims with typed links, topics, provenance, and lifecycle states. Notes are organized by Maps of Content (MOCs), processed through a 6-phase pipeline, and visualized as an interactive graph.
- Powerhouse reactor running with the
bai-knowledge-noteVetra package deployed - Claude Code CLI installed (for AI agent use)
- Switchboard CLI installed (recommended —
curl -fsSL https://raw.githubusercontent.com/liberuum/switchboard-cli/main/install.sh | bash)
cd your-project/
git clone https://github.com/liberuum/powerhouse-knowledge .claude/plugins/powerhouse-knowledgeClaude Code auto-discovers plugins in .claude/plugins/.
git clone https://github.com/liberuum/powerhouse-knowledge ~/.claude/plugins/powerhouse-knowledgeclaude --plugin-dir /path/to/powerhouse-knowledgeLocal development:
cd your-powerhouse-project/
ph vetra --watch # starts reactor at localhost:4001Remote (Switchboard):
switchboard config use remote-dev # or your profile name
switchboard ping # verify connectionSee CONFIGURATION.md for detailed connection options (MCP, CLI, GraphQL).
switchboard drives list --format json # find the vault drive
switchboard docs tree <drive-slug> --format json # check folder structureOr use the setup skill:
/powerhouse-knowledge:setup
Seed a source (article, transcript, documentation):
/powerhouse-knowledge:seed
Run the full pipeline (extract → connect → verify):
/powerhouse-knowledge:pipeline
Search the vault:
/powerhouse-knowledge:search how does the reactor work
Check vault health:
/powerhouse-knowledge:health
Explore the graph:
/powerhouse-knowledge:graph
The plugin supports three ways to interact with the reactor:
| Mode | Tool | Best for |
|---|---|---|
| Switchboard CLI | switchboard commands via Bash |
Agent workflows, full feature parity |
| MCP | mcp__reactor-mcp__* tools |
Direct document CRUD from Claude |
| GraphQL | HTTP queries to /graphql/knowledgeGraph |
Subgraph queries, external integrations |
The knowledge-agent uses the Switchboard CLI by default. See CONFIGURATION.md for setup details.
| Skill | Command | Description |
|---|---|---|
| Setup | /powerhouse-knowledge:setup |
Verify vault structure, folders, and singletons |
| Import | /powerhouse-knowledge:import <path> |
Bulk import from markdown, Obsidian, or JSON |
| Export | /powerhouse-knowledge:export [path] |
Export vault as markdown, JSON, or .phd backup |
| Skill | Command | Description |
|---|---|---|
| Seed | /powerhouse-knowledge:seed |
Ingest source material into the vault |
| Extract | /powerhouse-knowledge:extract |
Extract atomic claims from a source |
| Connect | /powerhouse-knowledge:connect |
Find and create typed links between notes |
| Synthesize | /powerhouse-knowledge:synthesize |
Create MOCs from topic clusters |
| Search | /powerhouse-knowledge:search <query> |
Find notes (keyword, topic, semantic, provenance) |
| Verify | /powerhouse-knowledge:verify |
Quality checks + auto-repair |
| Health | /powerhouse-knowledge:health |
Vault diagnostics saved to health-report |
| Graph | /powerhouse-knowledge:graph |
Structural analysis (triangles, bridges, clusters) |
| Skill | Command | Description |
|---|---|---|
| Pipeline | /powerhouse-knowledge:pipeline |
Full end-to-end: extract → connect → verify |
| Watch | /powerhouse-knowledge:watch |
Real-time vault monitoring via WebSocket |
The vault includes a Graph Indexer processor that maintains a relational index of all knowledge notes. The Knowledge Graph subgraph exposes this index via GraphQL at /graphql/knowledgeGraph.
Every bai/knowledge-note operation triggers the indexer to update:
- graph_nodes — title, description, content, noteType, status, author, sourceOrigin, createdAt
- graph_edges — source, target, linkType, targetTitle
- graph_topics — document_id, topic name
- note_embeddings — 384-dim vector embeddings for semantic search (Transformers.js + pgvector)
Search:
knowledgeGraphSearch(query)— keyword match on title + descriptionknowledgeGraphFullSearch(query)— keyword match on title + description + contentknowledgeGraphSemanticSearch(query)— AI-powered meaning-based searchknowledgeGraphSimilar(documentId)— find semantically similar notes
Topics:
knowledgeGraphTopics— all topics with note countsknowledgeGraphByTopic(topic)— notes tagged with a topicknowledgeGraphRelatedByTopic(documentId)— notes sharing topics with a given note
Provenance:
knowledgeGraphByAuthor(author)— notes by authorknowledgeGraphByOrigin(origin)— notes by source originknowledgeGraphRecent(limit, since?)— recently created/updated notes
Structure:
knowledgeGraphStats— node count, edge count, orphan countknowledgeGraphNodes/knowledgeGraphEdges— all indexed dataknowledgeGraphOrphans— notes with no incoming linksknowledgeGraphBacklinks/knowledgeGraphForwardLinks— directional edgesknowledgeGraphConnections(documentId, depth)— BFS traversalknowledgeGraphTriangles— synthesis opportunities (A,B both link to C)knowledgeGraphBridges— articulation pointsknowledgeGraphDensity— graph density metric
Admin:
knowledgeGraphReindex(driveId)— backfill the index after deploymentknowledgeGraphDebug(driveId)— raw DB rows
| User intent | Best query |
|---|---|
| Natural language question | knowledgeGraphSemanticSearch |
| Known keyword/term | knowledgeGraphSearch or knowledgeGraphFullSearch |
| "Notes about topic X" | knowledgeGraphByTopic |
| "Notes similar to this one" | knowledgeGraphSimilar |
| "What did author X write?" | knowledgeGraphByAuthor |
| "Recent notes" | knowledgeGraphRecent |
| Model | Type | Purpose |
|---|---|---|
| Knowledge Note | bai/knowledge-note |
Atomic knowledge claims |
| Map of Content | bai/moc |
Topic navigation hubs |
| Source | bai/source |
Ingested source material |
| Knowledge Graph | bai/knowledge-graph |
Materialized graph singleton |
| Pipeline Queue | bai/pipeline-queue |
Processing task tracker |
| Health Report | bai/health-report |
Point-in-time diagnostics |
| Vault Config | bai/vault-config |
Vault configuration |
| Observation | bai/observation |
Operational learning signals |
| Tension | bai/tension |
Unresolved contradictions |
| Derivation | bai/derivation |
Configuration audit trail |
The 6R pipeline transforms raw sources into structured, connected knowledge:
1. Record → /seed (ingest source material)
2. Reduce → /extract (extract atomic claims)
3. Reflect → /connect (find links between notes)
4. Reweave → /synthesize (create MOCs, update old notes)
5. Verify → /verify (quality gate, auto-repair)
6. Rethink → /health + /graph (challenge assumptions)
Human (Connect App) AI Agent (Claude Code)
| |
+── Knowledge Vault App +── powerhouse-knowledge plugin
| |── Notes tab (grid + search) | |── 14 skills
| |── Graph tab (cytoscape viz) | |── knowledge-agent
| |── Sources, Pipeline, Health | |── Switchboard CLI
| +── MOC editor, Note editor | +── MCP / GraphQL
| |
+───────── Powerhouse Reactor ────────+
|── 11 document models
|── Graph Indexer processor
| |── Relational index (PGlite)
| +── Semantic embeddings (pgvector + Transformers.js)
|── Knowledge Graph subgraph (25+ queries)
+── MCP server
powerhouse-knowledge/
├── agents/
│ └── knowledge-agent.md # Agent definition with full vault API reference
├── skills/
│ ├── search/SKILL.md # Multi-tier search (semantic, keyword, topic)
│ ├── graph/SKILL.md # Structural + semantic graph analysis
│ ├── connect/SKILL.md # Link discovery with articulation test
│ ├── seed/SKILL.md # Source ingestion
│ ├── extract/SKILL.md # Atomic claim extraction
│ ├── synthesize/SKILL.md # MOC creation from topic clusters
│ ├── verify/SKILL.md # Quality gate + auto-repair
│ ├── health/SKILL.md # Vault diagnostics
│ ├── pipeline/SKILL.md # End-to-end processing
│ ├── setup/SKILL.md # Vault initialization
│ ├── import/SKILL.md # Bulk import
│ ├── export/SKILL.md # Vault export
│ ├── watch/SKILL.md # Real-time monitoring
│ └── cli-reference/SKILL.md # Switchboard CLI commands
├── data/
│ └── methodology/ # 249 Ars Contexta research claims (local reference)
├── hooks/ # Pre-flight hooks for vault detection
├── scripts/ # Utility scripts
├── settings.json # Plugin settings
├── CONFIGURATION.md # Connection setup guide
└── README.md # This file
AGPL-3.0-only