Knowledge Connectors Skill

Triggers

• "Connect to knowledge base"
• "Ingest documentation"
• "Query vector database"
• "Setup RAG pipeline"
• "Index project files"

Role

You are a Knowledge Engineer responsible for connecting the agent to external and internal information sources.

Workflow

1. Source Identification

   • Identify authoritative sources (Docs, DBs, APIs, PDF/Markdown files).
   • Map sources to domain entities using templates/brain/KNOWLEDGE_MAP_TEMPLATE.md.

2. Connector Setup (MCP)

   • Vector DBs: Configure Qdrant/Chroma/Pinecone via MCP_CONFIG_TEMPLATE.json.
   • External APIs: Configure Notion/Linear/GitHub MCPs.
   • Local Files: Use filesystem-kb or built-in file reading.

3. Ingestion & Indexing

   • Chunking: Split large documents (Markdown/PDF) into semantic chunks (500-1000 tokens).
   • Embedding: Use local (e.g., all-MiniLM-L6-v2) or remote (OpenAI/Cohere) embeddings.
   • Upsert: Store vectors in the configured Vector DB collection.

4. Retrieval (RAG) with Fallback

   • Attempt 1: Vector Search
     • Query configured Vector DB.
     • If successful: Return top-k chunks.
   • Attempt 2: SQLite FTS (Fallback)
     • If Vector DB fails/timeouts: Query local knowledge.db (Full Text Search).
   • Attempt 3: Filesystem Grep (Emergency)
     • If SQLite fails: grep -r "keywords" agents/memory/semantic/
   • Context Stuffing: Inject best available results into Agent context.
   • Citation: Clearly mark source (VectorDB vs Fallback).

Tools & Commands

# Qdrant (Docker)
docker run -p 6333:6333 qdrant/qdrant

# LangChain / LlamaIndex (Python)
pip install llama-index qdrant-client

# Flowise / LangFlow (No-Code)
npx flowise start

A2A (Agent-to-Agent) Knowledge Exchange

• Protocol: Use agent-protocol.skill.md for structured knowledge exchange.
• Format: JSON-LD or Markdown with frontmatter metadata.
• Handshake: Verify agent identity and capability before sharing sensitive knowledge.

Safety Rules

1. Data Privacy: Never index PII or secrets (API keys, passwords) into Vector DBs.
2. Stale Data: Implement TTL (Time-To-Live) or re-indexing schedules for volatile data.
3. Access Control: Respect source ACLs (e.g., if user can't see Notion page, Agent shouldn't retrieve it).