rag-deep-dive

rag-deep-dive — search + fetch + find similar

When to use this skill

Trigger this skill when the user asks something that needs breadth AND depth:

• "How does X work end-to-end?"
• "Walk me through the authentication flow"
• "Explain the ingestion pipeline"
• "Give me the full picture on X"
• "How is X implemented across our services?"
• Any question where a 500-char snippet is obviously not enough

Do NOT trigger for:

• Simple factual lookups ("what port does X use") — rag-check-first alone is enough
• User explicitly wants a short answer ("TL;DR", "one-liner")
• Time-sensitive triage where speed matters more than depth

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What this skill commits to

The agent runs a 3-tool chain in a fixed order:

1. search_knowledge — find candidates
2. get_document — read the top match in full
3. search_similar — find related material

Then synthesizes an answer that pulls from all three, cites each source, and flags gaps.

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Steps

1. Search — cast a wide net:

   search_knowledge(query="<user's topic>", max_results=8, snippet_mode=true, min_score=0.15)
   

   Wider than usual (8 not 5) because we want candidate diversity for the similar-search step.

2. Fetch — read the winner in full:

   get_document(filepath="<top_hit.source>")
   

   The full document, not just the chunk. This gives you sections that adjacent chunks did not surface.

3. Find similar — discover the surrounding graph:

   search_similar(filepath="<top_hit.source>", max_results=5)
   

   These are documents ChromaDB considers semantically close to the top hit. Often surfaces the "obvious next document" that keyword search missed.

4. Cross-reference the 3 result sets. Look for:

   • Consensus — do multiple docs describe the same thing? Cite them together.
   • Contradiction — flag it explicitly to the user, do not silently pick one.
   • Gap — if similar-search surfaces a doc you did not read yet, decide if it is worth a second get_document.