skills-impeccable/i-critique/SKILL.md
Use when the user says: "critique this UI", "design critique", "review this interface", "does this look AI-generated". Evaluate design effectiveness with actionable feedback.
npx skillsauth add NodeJSmith/Claudefiles i-critiqueInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Read ${CLAUDE_HOME:-~/.claude}/skills/i-frontend-design/SKILL.md for design principles and anti-patterns. Check for design context (design/context.md, .impeccable.md, or design/direction.md) — if found, use it to inform brand-specific judgments. If no context exists, proceed anyway but note: "No design context found — critique uses universal design principles only. Run /i-teach-impeccable to establish brand context." Additionally gather: what the interface is trying to accomplish.
Critiques are read-only diagnostics — they should never be blocked by missing context.
Conduct a holistic design critique, evaluating whether the interface actually works—not just technically, but as a designed experience. Think like a design director giving feedback.
Evaluate the interface across these dimensions:
This is the most important check. Does this look like every other AI-generated interface from 2024-2025?
Review the design against all the anti-patterns in ../i-frontend-design/reference/anti-patterns.md — they are the fingerprints of AI-generated work.
The test: If you showed this to someone and said "AI made this," would they believe you immediately? If yes, that's the problem.
Work each as a single judgment call:
Structure your feedback as a design director would:
Start here. Pass/fail: Does this look AI-generated? List specific tells from the anti-patterns reference. Be brutally honest.
A brief gut reaction—what works, what doesn't, and the single biggest opportunity.
Highlight 2-3 things done well. Be specific about why they work.
The 3-5 most impactful design problems, ordered by importance:
For each issue:
/i-colorize, layout → /i-layout, typography → /i-typeset, performance → /i-optimize, responsive → /i-adapt, consistency → /i-polish). Do not suggest diagnostic skills.Quick notes on smaller issues worth addressing.
Provocative questions that might unlock better solutions:
Remember: Be direct and specific ("the submit button," not "some elements") — name what's wrong, why it hurts users, and the concrete fix. Don't soften criticism, and prioritize ruthlessly: if everything is important, nothing is.
Run get-skill-tmpdir i-critique and write the audit report to <tmpdir>/critique-YYYY-MM-DD.md. Then summarize in conversation:
development
Use when the user says: "humanize this", "unslop this", "de-slop this", "fix AI writing", "remove AI tells", "clean up AI prose". Edits prose to remove AI writing patterns and add human voice. Analyzes first, then asks how to fix. Prose complement to mine.clean-code.
development
Use when the user says: "why is this code like this", "why does this exist", "why was this built this way", "decision rationale", "what's the history behind". Decision archaeology — reconstructs historical rationale from evidence, not speculation.
development
Use when the user says: "how does X work", "walk me through", "explain this subsystem", "explain how", "trace the flow". Complexity-adaptive subsystem explanation — builds mental models conversationally, not documentation artifacts.
development
Use when the user says: 'create an issue', 'file an issue', 'open an issue', 'write an issue', 'new issue for this'. Codebase-aware issue creation — investigates the code to produce well-structured issues with acceptance criteria, affected areas, and enough detail for automated triage.