From claude-skills
Conducts deep web research, competitor analysis, and technology evaluation. Decomposes work into parallel vertical slices, identifies dependencies, and designs the critical path. Activates on research, planning, or competitor queries.
How this skill is triggered — by the user, by Claude, or both
Slash command
/claude-skills:03-planning-and-research*The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Decompose work into parallel vertical slices using deep web research, competitor scanning, and technology evaluation.
Decompose work into parallel vertical slices using deep web research, competitor scanning, and technology evaluation.
Before any non-trivial implementation:
Use web_search_20260209 + web_fetch_20260209 (free when paired with code_execution_20260120).
For every website build, run rules/competitor-research.md Phase -1 BEFORE Phase 0:
For every new dep / framework / service consideration:
rules/brian-preferences.md priority order)rules/cloudflare-hostable-supervisor.mdPer 06-build-and-slice-loop:
Per rules/parallel-subagent-economy.md:
Every assumption logged in _assumptions.md with:
Confidence <0.7 → research more. Per rules/auto-meta-work.md.
Per ~/.claude/CLAUDE.md § Thinking:
Prefer L3. Best outcome of research is NOT finding a solution to copy — it's understanding the problem deeply enough to design a better one.
Generate strongest counterargument. If you can't defeat it, decision is wrong.
Marginal cost of completeness is near-zero. When complete costs minutes more than shortcut, do complete. Boil lakes, flag oceans.
_research.json — raw findings, source URLs, confidence_assumptions.md — tracked claimsPLAN.md — implementation roadmap w/ parallelism plan + critical path_decisions.md — architectural decisions w/ rationale + alternatives_brief_summary.txt — 100-word digest for downstream agentsnpx claudepluginhub heymegabyte/claude-skillsMulti-agent research skill for technology evaluation, SOTA analysis, codebase archaeology, and competitive analysis. Uses wave-based pattern to gather breadth then synthesize.
Orchestrates multi-AI research across external providers (Claude, Gemini, Copilot, etc.) during the Discover phase of Double Diamond. Initializes project state and synthesizes findings from multiple models.
Conducts deep pre-build research: scans local projects for reusable code, analyzes competitors/forums/ecosystems/technical options, produces research briefs at focused/wide/deep depths.