etc/claude/skills/proofread/SKILL.md
Review text for AI writing tropes and mechanical prose patterns, then report findings with concrete rewrite suggestions. Use when the user asks to proofread, lint, or polish writing — especially docs, blog posts, READMEs, commit messages, PR descriptions, or any prose that should read as human-written. Also use when the user says "check for AI slop", "does this sound like AI", "make this sound more natural", or wants to de-AI their text.
npx skillsauth add shuymn/dotfiles proofreadInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
<skill-root> means the directory containing this SKILL.md.references/... relative to <skill-root>, not the caller's current working directory.Load the tropes catalog: Read <skill-root>/references/tropes.md. This is the authoritative list of patterns to scan for.
Read the target text: Read all target files or accept inline text. For each file, note its purpose (README, blog post, documentation, etc.) — context affects severity. A single "Not X — it's Y" in a 3000-word post is fine; five instances is a problem.
Scan for tropes: Walk through the text looking for matches against the catalog. For each finding:
Draft rewrite suggestions: For every finding, suggest a concrete rewrite. Preserve the author's meaning while sounding like something a human would actually write. Do not over-polish — imperfect but natural beats pristine but robotic.
Produce the report: List all findings with rewrite suggestions. Include a count at the top.
## Proofread Report: <filename or "inline text">
**Findings**: N
#### <Trope Category> — <Specific Pattern>
> <quoted passage>
Line: <line number or range, if from a file>
Suggestion: <concrete rewrite>
...
--help output or API reference are conventional, not tropes.The full catalog lives in <skill-root>/references/tropes.md. It covers:
Read the catalog before every review — it contains example patterns that help distinguish real findings from false positives.
development
Simplifies recently changed code by running three parallel reviews (reuse, quality, efficiency) and applying only behavior-preserving fixes. Use when the user asks to simplify, clean up, reduce duplication, improve code reuse, or optimize recently changed code, a staged diff, a branch diff, or explicitly listed files. Also use when the user says things like 'simplify this', 'まとめて整理して', 'コードをスリムにして', or invokes `/simplify`.
tools
Use when the user invokes /workflow. Injects project workflow methodology as context. Accepts argument: plan, exec, review (default: all).
development
Processes AI reviewer feedback and applies only verified fixes. Works in two modes: (1) fetches comments from a PR URL or current branch, (2) processes feedback pasted directly into the conversation. Trigger when the user wants to bulk-process or apply AI review suggestions — from a GitHub PR or pasted text. Do NOT trigger for single questions about what a bot said, or general code review discussion.
testing
Prepares .ralph/ runtime state from an approved and reviewed plan bundle. Syncs plan tasks into prd.json and updates prompt.run.md with project-specific context and quality gates. Use after plan approval, decompose-plan review PASS, and ralph init.