claude-code/skills/rag-search/SKILL.md

name, description, triggers

name	description	triggers
rag-search	Semantic search across personal state files and external documentation	search find lookup what did how did when did past decisions previous documentation docs

RAG Search Skill

Semantic search across two indexes:

• personal: Your state files, memory, decisions, preferences
• docs: External documentation (k0s, ArgoCD, etc.)

When to Use

• "What decisions did I make about X?"
• "How did I configure Y?"
• "What does the k0s documentation say about Z?"
• "Find my past notes on..."
• Cross-referencing personal context with official docs

Scripts

All scripts use the venv at ~/.claude/skills/rag-search/venv/.

Search (Primary Interface)

# Search both indexes
~/.claude/skills/rag-search/venv/bin/python \
  ~/.claude/skills/rag-search/scripts/search.py "query"

# Search specific index
~/.claude/skills/rag-search/scripts/search.py --index personal "query"
~/.claude/skills/rag-search/scripts/search.py --index docs "query"

# Control result count
~/.claude/skills/rag-search/scripts/search.py --top-k 10 "query"

Index Management

# Reindex personal state files
~/.claude/skills/rag-search/venv/bin/python \
  ~/.claude/skills/rag-search/scripts/index_personal.py

# Index all doc sources
~/.claude/skills/rag-search/venv/bin/python \
  ~/.claude/skills/rag-search/scripts/index_docs.py --all

# Index specific doc source
~/.claude/skills/rag-search/scripts/index_docs.py --source k0s

Adding Doc Sources

# Add a git-based doc source
~/.claude/skills/rag-search/venv/bin/python \
  ~/.claude/skills/rag-search/scripts/add_doc_source.py \
  --id "argocd" \
  --name "ArgoCD Documentation" \
  --type git \
  --url "https://github.com/argoproj/argo-cd.git" \
  --path "docs/" \
  --glob "**/*.md"

# List configured sources
~/.claude/skills/rag-search/scripts/add_doc_source.py --list

Output Format

Search returns JSON:

{
  "query": "your search query",
  "results": [
    {
      "rank": 1,
      "score": 0.847,
      "source": "personal",
      "file": "memory/decisions.json",
      "chunk": "Relevant text content...",
      "metadata": {"date": "2025-01-15"}
    }
  ],
  "searched_collections": ["personal", "docs"],
  "total_chunks_searched": 1847
}

Search Strategy

1. Start broad - Use general terms first
2. Refine if needed - Add specific keywords if results aren't relevant
3. Cross-reference - When both personal and docs results appear, synthesize them
4. Cite sources - Include file paths and dates in your answers

Example Workflow

User asks: "How should I configure ArgoCD sync?"

1. Search both indexes:

   search.py "ArgoCD sync configuration"
   

2. If personal results exist, prioritize those (user's past decisions)

3. Supplement with docs results for official guidance

4. Synthesize answer:

   Based on your previous decision (decisions.json, 2025-01-15), you configured ArgoCD with auto-sync enabled but self-heal disabled. The ArgoCD docs recommend this for production environments where you want automatic deployment but manual intervention for drift correction.

Maintenance

Indexes should be refreshed periodically:

• Personal: After significant state changes
• Docs: After tool version upgrades

A systemd timer can automate this (see design doc for setup).