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Found 18 Skills
Review the README or a documentation page from several real reader points of view at once. Fans out one parallel reviewer per audience — Claude Code newcomer, power user, plugin/skill author, skeptical senior engineer, non-running decision-maker — each scoring it x/5 and naming concrete, line-level fixes. Use when asked to review, critique, grade, or "get to N/5" the README or any front-door doc, or to check how a doc reads for real users. Not for code review (use /code-review for that).
Use when the user asks to research a topic in depth, map a competitive/market landscape, run a multi-source investigation, or "fan out" parallel research agents — anything where many findings must be gathered and then NOT lost. Enforces durable, detail-preserving research (write full findings to disk; keep a full appendix beside the synthesis).
Scan the current repo and score its feedback loop maturity for AI-assisted development
Read the README (or any front-door doc) through the eyes of several distinct audience personas and report what each would think, miss, or bounce on
Audit whether a repo's docs actually ANSWER the questions a reader has — by spawning fresh, cheap (Haiku) agents that cold-read ONLY the docs and measuring how fast they reach the answer, whether they hit dead-ends, whether they fall back to source code, and whether they cite docs that contradict each other. Use after a doc reorg, when docs "feel scattered," or when the same confusion keeps recurring. Surfaces findability gaps (a corpus can be COMPLETE — every doc indexed — yet not FINDABLE) plus a prioritized fix list. Works on any repo's docs, not just this one.
Synthesize a recurring code-review rule into a custom lint rule — gated by an independent soundness test that abstains rather than ship a checker it can't prove sound