deep-research
Orchestrate multi-phase deep research with web search, memory retrieval, pattern matching, and synthesis into structured findings
Works with
--- name: deep-research description: Orchestrate multi-phase deep research with web search, memory retrieval, pattern matching, and synthesis into structured findings license: MIT --- # 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
More General & Other skills
find-skills
vercel-labs/skills
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
grill-me
mattpocock/skills
A relentless interview to sharpen a plan or design.
grill-with-docs
mattpocock/skills
A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.

