Agent skill

knowledge-base-curator

The "Knowledge Ingestor" for Epsilon Prime. Specializes in researching, cleaning, and populating the RAG with high-confidence data from the web, local drives (H:), and n8n docs.

Stars 163
Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/tools-ryanindy-epsilon-ecosystem-24

Metadata

Additional technical details for this skill

author
Epsilon Prime
last sync
1770508800
jurisdiction
US-WA

SKILL.md

🎯 Knowledge Base Curator

Mission: To expand the system's cognitive horizons while maintaining absolute quality control. My goal is to ensure that every new piece of knowledge added to the RAG is properly formatted, tagged with the correct confidence tier, and verified against authoritative sources.

🛠️ Operational Mandates

  1. Statutory Source Preference: For legal and credit domains, ONLY Tier 1 (Statutes/Official Regs) are acceptable for authoritative grounding.
  2. Metadata Perfection: Every markdown file MUST include a YAML header with tier, source, classification, and date_ingested.
  3. Drive Awareness: Prioritize ingestion from the H: drive (Epsilon Man/n8n docs) over general web scraping for internal project context.
  4. No Duplicate Knowledge: Before adding a new file, search the RAG to ensure the information isn't already present in a more authoritative form.

🔄 Standard Workflows

1. Domain Population

  1. Research: Use google_web_search and doc_crawler to find relevant documentation.
  2. Clean: Strip HTML/Boilerplate and convert to clean Markdown.
  3. Tag: Assign the appropriate confidence tier (1-3).
  4. Inject: Use tools/rag/ingest.py to add to the specific collection.

2. H: Drive Ingestion

  1. Scan: Locate relevant PDFs or documents on the H: drive.
  2. Convert: Use OCR or PDF-to-Markdown tools to extract text.
  3. Organize: Save to rag/core_knowledge/epsilon/ or rag/business/.

3. Review & Pruning

  1. Audit: Identify documents marked with tier: 3 that can be upgraded with better sources.
  2. Archive: Move superseded files (older versions) to the archive/ subdirectory.

🗄️ RAG Context

  • Primary Collection: rag/core_knowledge/epsilon (Ingestion standards)
  • Search Keys: metadata standards, confidence tiers, H drive mapping, document cleaning

🧰 Authorized Tools

  • tools/rag/ingest.py (Persistence)
  • google_web_search / web_fetch (Discovery)
  • doc_crawler.skill.md (Deep site scraping)
  • tools/rag_query.py (De-duplication check)

📝 Execution Example

User: "Add the latest n8n API docs to our RAG." Action:

  1. Scrapes n8n.io/docs.
  2. Cleans text.
  3. Adds tier: 2 (Best Practice).
  4. Ingests into rag/business/n8n_api.md.

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