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/deep-research

Orchestrate multi-phase deep research with web search, memory retrieval, pattern matching, and synthesis into structured findings

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claude-flow
67k200 skills157 agents194 commands1 MCP
Install
$ npx -y skills add ruvnet/claude-flow --skill deep-research --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/deep-research

Context preview

The summary Claude sees to decide when to auto-load this skill.

Orchestrate multi-phase deep research with web search, memory retrieval, pattern matching, and synthesis into structured findings

SKILL.md

deep-research.SKILL.md
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__plugin_ruflo-core_ruflo__memory_store mcp__plugin_ruflo-core_ruflo__memory_search mcp__plugin_ruflo-core_ruflo__memory_search_unified mcp__plugin_ruflo-core_ruflo__agentdb_hierarchical-store mcp__plugin_ruflo-core_ruflo__agentdb_hierarchical-recall mcp__plugin_ruflo-core_ruflo__agentdb_pattern-search mcp__plugin_ruflo-core_ruflo__agentdb_pattern-store mcp__plugin_ruflo-core_ruflo__neural_predict mcp__plugin_ruflo-core_ruflo__hooks_intelligence_pattern-search mcp__plugin_ruflo-core_ruflo__hooks_intelligence_pattern-store mcp__plugin_ruflo-core_ruflo__task_create mcp__plugin_ruflo-core_ruflo__task_list mcp__plugin_ruflo-core_ruflo__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

1. **Define research scope** — break the question into 3-7 sub-questions that together answer the main question 2. **Search existing knowledge** — call `mcp__plugin_ruflo-core_ruflo__memory_search_unified` and `mcp__plugin_ruflo-core_ruflo__agentdb_pattern-search` to check what's already known 3. **Web research** — use `WebSearch` and `WebFetch` to gather external information for each sub-question 4. **Codebase analysis** — use `Bash` (grep/find), `Read` to examine relevant source files 5. **Cross-reference** — compare findings across sources, identify agreements and contradictions 6. **Store findings** — call `mcp__plugin_ruflo-core_ruflo__memory_store` with namespace `research` for each key finding 7. **Store patterns** — call `mcp__plugin_ruflo-core_ruflo__agentdb_pattern-store` for reusable patterns discovered 8. **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 topic
  • `research-synthesis` — completed synthesis reports
  • `research-sources` — source URLs and references
Read more
Ships withclaude-flow

An agent meta-harness for Claude Code and Codex. Agent = Model + Harness. The model writes; the harness gives it tools, memory, loops, sandboxes, and controls so it can actually work.

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