audit-ai-frontend

name

audit-ai-frontend

description

Audit AI-generated, AI-shaped, or AI-looking frontend code, UI screenshots, and design diffs. Use for prompts like "audit AI frontend", "de-slop UI", "componentize this screen", "parameterize this React/Tailwind/shadcn UI", "make it responsive/accessible", or "review design-system drift"; check component APIs, reusable props/data models, modular composition, shared primitives/tokens, responsive resilience, accessibility, copy quality, hard-coded fixture screens, one-off CSS piles, and generic cards/gradients/fonts.

AI Frontend Audit

Use

Audit or repair frontend UI/code that looks generically AI-generated, while preserving existing product structure unless the user asks for a redesign.

Review in this order:

1. Establish the local contract.

   • Read components, routes/pages, CSS/theme tokens, existing primitives, design-system conventions, copy style, and data/state patterns.
   • If runnable, inspect the UI in a real browser with whatever browser tooling is available; this skill decides what to inspect, not browser mechanics.
   • If screenshot-only, review visuals but label implementation risks as Inferred.

2. Inspect data flow and component shape before styling.

   • Check whether repeated UI is parameterized through props/data or hard-coded as a fixture screen.
   • Look for reusable primitives, narrow component APIs, stable variants, shared state/data models, and realistic loading/empty/error/long-content cases.
   • Flag duplicated JSX, one-off CSS piles, brittle utility strings, boolean-mode soup, over-broad components, and visual constants that should be tokens.

3. Load only the reference you need.

   • references/patterns.md for concrete AI-tell and code-smell fixes.
   • references/rubric.md for broad UX/a11y/component/design audits.
   • references/workflows.md for code-structure, browser QA, reference-packet, and brief-lock loops.

4. Preserve local system intent while removing accidental defaults.

   • Keep copy/order/IA and known product tokens unless the user asks for a redesign.
   • Keep a common-looking font/card/palette only if adjacent screens or documented tokens already use it; replace it when the style exists only in the generated screen.
   • If references are missing, derive one explicit design contract from product domain + user job + existing primitives; do not fabricate named reference sites.

5. Fix in this order.

   • P0: keyboard, labels, contrast, touch targets, mobile overflow, missing loading/empty/error states.
   • P1: hard-coded fixture screens, weak data models, duplicated markup/styles, brittle component APIs, token drift, boolean-mode soup.
   • P1: generic SaaS layout, card overuse, icon-pill repetition, Inter/Roboto/system defaults, purple/indigo/cyan gradient/glass tropes, vague CTA/copy.
   • P2: spacing rhythm, token consistency, one memorable visual rule, reduced-motion and state polish.

6. Re-verify in browser after edits whenever possible.

Output

For each finding, include:

• Issue
• Evidence
• Class (P0, P1, P2)
• Root cause (Component/API, Data/state, Responsive/a11y, Design-system, Copy, Visual default)
• Why it matters / why it reads as generic
• Possible non-AI explanation
• Smallest fix
• Acceptance check
• Confidence (High, Medium, Low)
• File/line when code is available

Return only the top 5-8 findings and merge repeated symptoms under one root cause. End with one line: If I had to change only one thing: ...

For implementation asks, patch the code directly. Prefer the smallest local abstraction that makes the next screen/state easier: typed data, props, variants, slots/children, existing primitives, or tokens. Summarize only meaningful component/design changes and remaining risk.

Guardrails

• Treat "AI-looking" as a quality smell, not a provenance claim.
• Prefer objective defects over taste opinions.
• Prefer local idiom over a new abstraction. Componentize only when it removes duplication, supports real states/data, or matches established primitives.
• When auditing shadcn/ui projects, preserve semantic component usage and tokens. Use the shadcn skill if component APIs, registry install/update, or shadcn-specific composition rules are part of the fix.
• Avoid anti-slop overcorrection: no random ornaments, novelty fonts, or one-off visual chaos.
• Anchor each finding in code, screenshots, DOM/a11y snapshots, or browser behavior, and separate fact from inference.

Resource

• references/patterns.md: checklist of AI-frontend tells, code smells, and repair patterns.
• references/rubric.md: compact UX/a11y/component/design-quality rubric for broader audits.
• references/workflows.md: code-structure audit, browser QA, reference-packet, and brief-lock loops.
• references/sources.md: research basis and links for periodic prompt refreshes.