Individual skill
audit-ai-design-slop
Audit websites, apps, screenshots, mockups, and design code for harmful AI-design clichés, generic generated defaults, and established UI defects. Use when the user wants evidence-backed design feedback, an anti-slop review, or a removal-first cleanup plan without a speculative redesign.
skills-imported/audit-ai-design-slop/SKILL.md
Source commit faf37c0859ebf627bfcb5225e8057d088691e0ae
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- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Instructions only
- Last checked
- Nov 8, 2026
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Repository context
- Repository stars (not skill ratings)
- 53
- Repository last updated
- Oct 10, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- agent-skills Repository topic
- ai-agents Repository topic
- ai-agents-automation Repository topic
- ai-skills Repository topic
- awesome Repository topic
- awesome-list Repository topic
- chatgpt Repository topic
- claude-skills Repository topic
- meta-ai Repository topic
- muse-ai Repository topic
- design Derived category
- security Derived category
- design-interface Derived category
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# Audit AI Design Slop
Run a diagnostic, evidence-backed audit. Identify the smallest set of removals or corrections that would improve the interface while preserving its existing direction.
## Boundaries
- Do not guess whether AI made the design.
- Do not assign a numeric slop score.
- Do not reject a visual technique in isolation. A gradient, serif, dark theme, glass effect, card, animation, or single-font system can be intentional.
- Do not prescribe a new font, palette, layout, design system, or art direction unless the user explicitly asks for one.
- Do not turn an audit into an implementation task.
- Mark anything outside the visible or provided evidence as unknown.
## Audit the Evidence