
Deep Research
This is a lead-agent-plus-subagents architecture for writing research reports with evidence tracking and citation governance. The lead agent dispatches parallel research tasks to subagents who write distilled notes, then builds from those notes instead of raw search results, which cuts context usage by 60-70%. You get source type labels (official, academic, journalism, community), freshness checks against an AS_OF date, and counter-review passes before final output. It enforces quality gates like minimum 30% official sources and maximum 25% from any single domain. The architecture splits into enterprise mode for company research with SWOT and risk matrices, or general mode for industry and policy work. Useful when you need a proper literature review or competitive analysis instead of a quick summary.
- skills.sh installs
- 1.8K
- GitHub stars
- 1.5K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add daymade/claude-code-skills --skill deep-research --agent claude-codeInstalls into .claude/skills of the current project.
Files
Deep Research
Create high-fidelity research reports with strict format control, evidence mapping, source governance, and multi-pass synthesis.
Architecture: Lead Agent + Subagents
Lead Agent (coordinator — minimizes raw search context)
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P0: Environment + source policy setup
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P1: Question and claim map (decision questions, evidence routes, stop rules)
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Dispatch ──→ Subagent A ──→ writes task-a.md ──┐
──→ Subagent B ──→ writes task-b.md ──┤ (parallel)
──→ Subagent C ──→ writes task-c.md ──┘
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| research-notes/ <────────────────────────┘
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P2: Dispatch + investigate → evidence packets
P3: Citation registry + source governance
P4: Evidence-mapped outline with counter-evidence and unknowns
P5: Draft from evidence packets; reopen decisive originals
P6: Counter-review (claims, confidence, alternatives)
P7: Verify → asset check and catalog registration
Sponsors
Details
- Repository
- github.com/daymade/claude-code-skills
- Categories
- Git & Pull Requests, Code Review & Quality, Data Science & ML, Design & UI/UX
- First seen
- Jun 3, 2026
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