frontend-design-optimizer
Find the best UI/UX design patterns and architectures using deep research. Use when user asks to "improve UI", "optimize UX", "best design for [feature]", or "modern UI patterns".
About frontend-design-optimizer
frontend-design-optimizer is a Claude AI skill developed by HR-AR. Find the best UI/UX design patterns and architectures using deep research. Use when user asks to "improve UI", "optimize UX", "best design for [feature]", or "modern UI patterns". This powerful Claude Code plugin helps developers automate workflows and enhance productivity with intelligent AI assistance.
Why use frontend-design-optimizer? With 0 stars on GitHub, this skill has been trusted by developers worldwide. Install this Claude skill instantly to enhance your development workflow with AI-powered automation.
| name | frontend-design-optimizer |
| description | Find the best UI/UX design patterns and architectures using deep research. Use when user asks to "improve UI", "optimize UX", "best design for [feature]", or "modern UI patterns". |
| version | 1.0.0 |
| agents | ["codex-deep-research","gemini-research-analyst"] |
Frontend UI/UX Design Optimizer
Deep research-driven skill for finding optimal frontend design patterns.
When to Use
Invoke this skill when the user mentions:
- "What's the best UI pattern for..."
- "How should I design the frontend for..."
- "Improve the UX of..."
- "Modern design patterns for..."
- "Find examples of [component/feature] design"
- "Best practices for [UI element]"
Research-First Methodology
This skill uses multi-agent deep research to find proven, production-ready design patterns.
Step 1: Understand Context
# First, analyze the current codebase - What framework are we using? (React, Vue, vanilla JS) - What UI library is present? (Bootstrap, Tailwind, custom) - What's the design system? (Material, custom, none) - Who are the users? (internal tools, customer-facing, admin panels)
Step 2: Launch Deep Research
Use the codex-deep-research agent to investigate:
Invoke Task tool with subagent_type="codex-deep-research" Prompt: "Research the best UI/UX design patterns for [specific feature/component]. Context: - Tech stack: [from Step 1] - User type: [from Step 1] - Requirements: [user's specific needs] Please provide: 1. Top 3-5 proven design patterns with examples 2. Pros/cons of each approach 3. Real-world implementations (with links to examples) 4. Accessibility considerations (WCAG compliance) 5. Performance implications 6. Mobile responsiveness strategies 7. Recommendations ranked by: usability, accessibility, performance Include code examples and visual descriptions where possible."
Step 3: Compare with Modern Standards
Use the gemini-research-analyst agent (if Gemini-specific UI tools are relevant):
Invoke Task tool with subagent_type="gemini-research-analyst" Prompt: "Research if Google's Gemini AI has any UI/UX design tools, guidelines, or recommended patterns for [specific feature]. Specifically check for: 1. Gemini-powered design assistants 2. Google's Material Design 3 updates 3. AI-assisted UI generation tools 4. Accessibility tools from Google AI 5. Any Gemini integrations for design workflows If Gemini has relevant tools, explain how to integrate them."
Step 4: Synthesize Recommendations
After agents return results:
-
Compare patterns from research
-
Rank by criteria:
- User experience (most important)
- Accessibility (WCAG AA minimum)
- Performance (Lighthouse score impact)
- Maintainability (code complexity)
- Browser compatibility
- Mobile-first design
-
Provide decision matrix:
## Design Pattern Comparison | Pattern | UX Score | A11y | Perf | Maintainability | Best For | |---------|----------|------|------|----------------|----------| | [Pattern 1] | ⭐⭐⭐⭐⭐ | WCAG AA | 95/100 | Low complexity | [Use case] | | [Pattern 2] | ⭐⭐⭐⭐ | WCAG AAA | 88/100 | Medium | [Use case] |
- Recommend top choice with justification
Step 5: Provide Implementation Plan
## Recommended: [Pattern Name] ### Why This Pattern? - [Justification based on research] - [Link to production examples] - [Performance benchmarks] ### Implementation Steps 1. [Step 1 with code example] 2. [Step 2 with code example] 3. [Step 3 with code example] ### Accessibility Checklist - [ ] Keyboard navigation - [ ] Screen reader support (ARIA labels) - [ ] Color contrast (4.5:1 minimum) - [ ] Focus indicators - [ ] Semantic HTML ### Testing Strategy - [ ] Cross-browser testing (Chrome, Firefox, Safari, Edge) - [ ] Mobile responsive testing (320px to 1920px) - [ ] Lighthouse audit (>90 accessibility score) - [ ] Screen reader testing (NVDA, JAWS, VoiceOver) ### Example Code ```javascript // [Full working example from research]
Live Examples
- [Link to CodeSandbox/CodePen]
- [Link to production site using this pattern]
- [Link to design system documentation]
## Validation Criteria
Before presenting recommendations, ensure:
- ✅ At least 3 different patterns researched
- ✅ Each pattern has production examples
- ✅ Accessibility compliance verified (WCAG AA minimum)
- ✅ Performance benchmarks included
- ✅ Mobile responsiveness addressed
- ✅ Code examples are complete and working
- ✅ Browser compatibility documented
## Anti-Patterns to Avoid
**NEVER recommend without research:**
- Trends without proven track record
- Patterns with poor accessibility
- Solutions that don't match tech stack
- Overcomplicated solutions for simple problems
**ALWAYS prioritize:**
- User experience over aesthetics
- Accessibility over visual flair
- Performance over feature bloat
- Maintainability over cleverness
## Example Invocation
```markdown
User: "What's the best way to design a real-time dashboard with live metrics?"

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