How to install deep-research
npx skills add https://github.com/ruvnet/ruflo --skill deep-researchClaude Code
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Full instructions (SKILL.md)
Source of truth, from ruvnet/ruflo.
name: deep-research description: Orchestrate multi-phase deep research with web search, memory retrieval, pattern matching, and synthesis into structured findings argument-hint: "<topic>" allowed-tools: mcp__claude-flow__memory_store mcp__claude-flow__memory_search mcp__claude-flow__memory_search_unified mcp__claude-flow__agentdb_hierarchical-store mcp__claude-flow__agentdb_hierarchical-recall mcp__claude-flow__agentdb_pattern-search mcp__claude-flow__agentdb_pattern-store mcp__claude-flow__neural_predict mcp__claude-flow__hooks_intelligence_pattern-search mcp__claude-flow__hooks_intelligence_pattern-store mcp__claude-flow__task_create mcp__claude-flow__task_list mcp__claude-flow__task_summary Bash WebSearch WebFetch Read Write
Deep Research
Orchestrate multi-phase deep research campaigns that gather, cross-reference, and synthesize information from multiple sources.
When to use
When you need to investigate a complex topic thoroughly — spanning web sources, codebase patterns, stored memory, and external documentation — and produce a structured synthesis.
Steps
- Define research scope — break the question into 3-7 sub-questions that together answer the main question
- Search existing knowledge — call
mcp__claude-flow__memory_search_unifiedandmcp__claude-flow__agentdb_pattern-searchto check what's already known - Web research — use
WebSearchandWebFetchto gather external information for each sub-question - Codebase analysis — use
Bash(grep/find),Readto examine relevant source files - Cross-reference — compare findings across sources, identify agreements and contradictions
- Store findings — call
mcp__claude-flow__memory_storewith namespaceresearchfor each key finding - Store patterns — call
mcp__claude-flow__agentdb_pattern-storefor reusable patterns discovered - Synthesize — produce a structured research report with:
- Executive summary (2-3 sentences)
- Key findings (bulleted)
- Evidence quality assessment (high/medium/low per finding)
- Open questions remaining
- Recommended next steps
Research depth levels
- Quick — memory search + 1-2 web queries, 2-3 minutes
- Standard — memory + web + codebase scan, 5-10 minutes
- Deep — all sources + cross-referencing + pattern storage, 15-30 minutes
- Exhaustive — deep + spawn sub-agents for parallel research threads, 30+ minutes
Memory namespaces
research— raw findings keyed by topicresearch-synthesis— completed synthesis reportsresearch-sources— source URLs and references
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