deep-research

name	deep-research
description	IterDRAG iterative retrieval-augmented generation pattern — search, summarize, reflect loop for deep research tasks
tags	["research","search","rag","deep-research","analysis"]

Deep Research — IterDRAG Pattern

When assigned a research task, follow this iterative loop until the answer is comprehensive and well-sourced.

The Loop

QUERY → DECOMPOSE → SEARCH → SUMMARIZE → REFLECT → (gaps?) → SEARCH again → REPORT

Stop when: all sub-questions have authoritative answers, OR 3 iterations complete, OR new searches return no new information.

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Phase 1: Decompose the Query

Before searching, break the research question into 3–5 independently searchable sub-questions that together cover the full topic.

Example — "What are best practices for Connect-RPC in Go?":

1. What is Connect-RPC and how does it differ from standard gRPC?
2. What are the recommended project structure conventions?
3. How should error handling work in Connect-RPC handlers?
4. What are the performance best practices for streaming RPCs?
5. How does Connect-RPC handle backward compatibility?

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Phase 2: Search (per sub-question)

For each sub-question:

1. Formulate a precise search query (use technical terms, avoid ambiguity).
2. Execute search via available tool (web search, document retrieval, code search).
3. Collect 3–5 relevant sources. Prefer: official docs > source code > RFC/specs > engineering blogs > forum posts.
4. Note the URL/reference, title, and key claims from each source.

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Phase 3: Summarize

After searching all sub-questions:

1. Write a structured summary per sub-question.
2. Cite sources inline for every claim.
3. Flag contradictions between sources explicitly.
4. Mark what is authoritative (spec, official docs) vs. community opinion.

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Phase 4: Reflect on Gaps

Ask:

• What questions remain unanswered?
• What claims lack good sourcing?
• Are there edge cases or failure modes not covered?
• Is the information current? (check publication dates)

If gaps found → formulate new targeted queries and return to Phase 2. If confident → proceed to Phase 5.

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Phase 5: Produce the Report

# [Topic] — Research Report

## Summary
[2–3 sentences: key findings]

## Findings

### [Sub-question 1]
[Answer with inline citations]

### [Sub-question 2]
[Answer with inline citations]

## Key Recommendations
- [Actionable recommendation 1]
- [Actionable recommendation 2]

## Sources
- [URL or doc name] — [why relevant]

## Gaps and Caveats
- [What remains uncertain or needs verification]

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Configuration

Mode	When to use
Local (Ollama)	Private data, offline, cost-sensitive. Models: llama3, mistral, deepseek-r1
Cloud	High accuracy on complex topics. Models: claude-sonnet-4-6, gpt-4o

Search providers (no key required): DuckDuckGo instant answers. Search providers (API key): Brave Search API, Tavily API, SerpAPI.

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Quality Signals

Good output:

• Every claim has a source
• Contradictions are surfaced, not hidden
• Distinguishes spec/official vs. community practice
• Gaps section is honest

Poor output:

• Confident claims without sources
• No alternatives or tradeoffs discussed
• Single-source conclusions on contested topics
• Missing a gaps/caveats section