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affaan-m/design-system

affaan-m

design-system

Use this skill to generate or audit design systems, check visual consistency, and review PRs that touch styling.

global
0installs0uses~600
v1.1Saved Apr 20, 2026

Design System — Generate & Audit Visual Systems

When to Use

  • Starting a new project that needs a design system
  • Auditing an existing codebase for visual consistency
  • Before a redesign — understand what you have
  • When the UI looks "off" but you can't pinpoint why
  • Reviewing PRs that touch styling

How It Works

Mode 1: Generate Design System

Analyzes your codebase and generates a cohesive design system:

1. Scan CSS/Tailwind/styled-components for existing patterns
2. Extract: colors, typography, spacing, border-radius, shadows, breakpoints
3. Research 3 competitor sites for inspiration (via browser MCP)
4. Propose a design token set (JSON + CSS custom properties)
5. Generate DESIGN.md with rationale for each decision
6. Create an interactive HTML preview page (self-contained, no deps)

Output: DESIGN.md + design-tokens.json + design-preview.html

Mode 2: Visual Audit

Scores your UI across 10 dimensions (0-10 each):

1. Color consistency — are you using your palette or random hex values?
2. Typography hierarchy — clear h1 > h2 > h3 > body > caption?
3. Spacing rhythm — consistent scale (4px/8px/16px) or arbitrary?
4. Component consistency — do similar elements look similar?
5. Responsive behavior — fluid or broken at breakpoints?
6. Dark mode — complete or half-done?
7. Animation — purposeful or gratuitous?
8. Accessibility — contrast ratios, focus states, touch targets
9. Information density — cluttered or clean?
10. Polish — hover states, transitions, loading states, empty states

Each dimension gets a score, specific examples, and a fix with exact file:line.

Mode 3: AI Slop Detection

Identifies generic AI-generated design patterns:

- Gratuitous gradients on everything
- Purple-to-blue defaults
- "Glass morphism" cards with no purpose
- Rounded corners on things that shouldn't be rounded
- Excessive animations on scroll
- Generic hero with centered text over stock gradient
- Sans-serif font stack with no personality

Examples

Generate for a SaaS app:

/design-system generate --style minimal --palette earth-tones

Audit existing UI:

/design-system audit --url http://localhost:3000 --pages / /pricing /docs

Check for AI slop:

/design-system slop-check
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Overall Score

68/100

Grade

C

Adequate

Safety

85

Quality

62

Clarity

75

Completeness

55

Summary

This skill guides AI agents to generate, audit, or quality-check design systems within a codebase. It can scan for design tokens (colors, typography, spacing), score visual consistency across 10 dimensions, research competitor designs, and flag generic AI-generated UI patterns. The skill produces design documentation, token files, and audit reports.

Detected Capabilities

Codebase scanning for CSS/design patternsDesign token extraction and generationVisual consistency scoring (10-dimension framework)Competitor site research via browser MCPHTML preview generation (self-contained)Design documentation authoringAI-generated design pattern detectionPR review for styling changes

Trigger Keywords

Phrases that MCP clients use to match this skill to user intent.

design system auditvisual consistency checkdesign token generationui polish reviewai slop detectionstyle pr reviewdesign system starter

Risk Signals

INFO

Browser MCP research on competitor sites

Mode 1, step 3: 'Research 3 competitor sites for inspiration (via browser MCP)'
INFO

File write operations to project root

Output section: 'DESIGN.md' + 'design-tokens.json' + 'design-preview.html'
INFO

Code analysis and pattern matching

Mode 1, steps 1-2: scanning CSS/Tailwind and extracting design patterns
INFO

URL parameter in audit command

Examples: '/design-system audit --url http://localhost:3000'

Referenced Domains

External domains referenced in skill content, detected by static analysis.

localhost

Use Cases

  • Generate a cohesive design system from existing CSS/Tailwind patterns
  • Audit an existing UI codebase for visual consistency and polish
  • Identify generic AI-generated design patterns (AI slop)
  • Review design PRs for consistency with established system
  • Establish design guidelines before a product redesign
  • Score UI quality across accessibility, spacing, typography, and responsiveness

Quality Notes

  • Strength: Three distinct modes (generate, audit, slop-check) are clearly separated with concrete workflows.
  • Strength: Visual audit scoring framework (10 dimensions) is detailed and actionable with 'fix with exact file:line' guidance.
  • Strength: Examples are provided for each mode, making invocation clear.
  • Strength: 'When to Use' section directly addresses user scenarios.
  • Weakness: No error handling guidance — what happens if codebase has no CSS? What if pages fail to load during audit?
  • Weakness: No limitations documented — unclear whether skill works with CSS-in-JS, SASS, PostCSS, or only Tailwind.
  • Weakness: Mode 1 output structure (DESIGN.md, design-tokens.json) is mentioned but format/schema not detailed.
  • Weakness: 'Research 3 competitor sites' — how are sites selected? Manual input or automatic?
  • Weakness: No guidance on handling large codebases or performance constraints.
  • Weakness: Mode 3 (AI slop detection) lacks detailed examples — what specific code patterns trigger each detection?
  • Weakness: No mention of scope boundaries — will skill touch non-design files or cross project boundaries?
Model: claude-haiku-4-5-20251001Analyzed: Apr 20, 2026

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Version History

v1.1

Content updated

2026-04-20

Latest
v1.0

No changelog

2026-04-12

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