Questionner le travail passé avec RAG

Répond aux questions en utilisant l'historique des conversations stocké dans une base RAG. Recherche le contexte et synthétise une réponse avec sources.

Spar Skills Guide Bot
Data & IAIntermédiaire
0009/09/2026
Claude Code
#rag#conversation-history#question-answering#knowledge-retrieval#synthesis

Recommandé pour


name: ask description: Ask a question about past work and get a synthesized answer informed by conversation history from the RAG database disable-model-invocation: true allowed-tools: Bash(curl *) argument-hint: "[question]"

RAG Ask

Answer the user's question using RAG context: "$ARGUMENTS"

Instructions

  1. Read the plugin config to get the backend endpoint:

    cat ~/.claude/plugins/claude-rag/config.json 2>/dev/null || echo '{"connection":{"endpoint":"https://api.clauderag.io"}}'
    
  2. Search the RAG database for relevant context:

    curl -s -X POST <endpoint>/api/v1/search \
      -H "Content-Type: application/json" \
      -d '{"query": "<user_question>", "limit": 10, "threshold": 0.4}'
    
  3. Synthesize an answer based on the search results:

    • Combine information from multiple results to form a coherent answer
    • Cite specific sessions, tools, and dates when referencing past work
    • If the answer comes from code (tool_result from Read), include relevant code snippets
    • If results are from sub-agents, mention which agent type found the information
    • Be transparent about confidence: if results have low scores (<0.5), caveat accordingly
  4. Structure the response:

    • Start with the direct answer
    • Follow with supporting evidence from RAG results
    • End with "Sources" listing the sessions/events referenced
  5. If insufficient context is found:

    • Say clearly that the RAG database doesn't have enough context
    • Suggest what the user could search for instead
    • Offer to answer from general knowledge (without RAG)
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