AI Skill Report Card
Figma Design to Code Generation
Figma Design-to-Code Generation
Quick Start14 / 15
JavaScript// 1. Connect to Figma file const figmaFile = await figma.getFile('your-file-id'); // 2. Extract component with full specifications const componentData = await figma.getNode('component-node-id', { includeStyles: true, includeVariables: true, includeConstraints: true, includePrototypes: true }); // 3. Generate React component const reactCode = generateReactComponent(componentData);
Recommendation▾
Add more concrete input/output examples showing actual Figma JSON data and the exact generated code
Core Workflow
Progress:
- Extract Figma component specifications
- Parse design tokens and variables
- Generate base component structure
- Apply responsive constraints
- Add interaction states
- Implement accessibility features
- Validate visual accuracy
- Export production code
1. Component Specification Extraction
Prompt Template:
Extract complete specifications from this Figma component:
Component: [NODE_ID]
Required data:
- Dimensions: width, height, padding, margins
- Design tokens: colors, typography, spacing, shadows
- Variants: all property combinations and values
- States: default, hover, focus, active, disabled
- Auto-layout: direction, alignment, spacing, constraints
- Variable mappings: semantic tokens to primitive values
Output as structured JSON with exact CSS property names.
2. Design System Generation
Prompt Template:
Generate React design system from Figma variables:
Variables: [VARIABLE_COLLECTION]
Requirements:
- CSS custom properties for all design tokens
- TypeScript interfaces for component props
- Styled-components theme object
- Component variants using design tokens
- Dark/light mode token mappings
Structure:
```typescript
// tokens.ts
export const tokens = {
colors: { /* from Figma color variables */ },
typography: { /* from Figma text variables */ },
spacing: { /* from Figma number variables */ }
};
// Component.tsx
export const Button = styled.button<ButtonProps>`
/* CSS using design tokens */
`;
3. Responsive Code Generation
Prompt Template:
Convert Figma auto-layout to responsive CSS:
Component: [NODE_ID]
Auto-layout data: [CONSTRAINTS_DATA]
Generate:
- CSS Grid/Flexbox matching Figma layout
- Responsive breakpoints from min/max constraints
- Container queries for component-level responsiveness
- Fluid typography and spacing calculations
Output mobile-first CSS with exact breakpoint values from Figma constraints.
4. Animation Code Generation
Prompt Template:
Convert Figma prototype interactions to CSS/JS:
Interaction: [PROTOTYPE_DATA]
Trigger: [TRIGGER_TYPE] (click, hover, etc.)
Animation: [TRANSITION_DATA]
Generate:
- CSS transitions/keyframes for simple animations
- Framer Motion code for complex interactions
- React state management for multi-step flows
- Performance-optimized animation properties
Match Figma easing curves and timing exactly.
Advanced Prompt Templates
Component Variant Generation
Create React component with all Figma variants:
Variants: [COMPONENT_VARIANTS]
States: [INTERACTION_STATES]
Generate:
- TypeScript props interface
- Styled-components with variant logic
- Default props matching Figma defaults
- Comprehensive prop combinations
Use compound variants for multi-property combinations.
Accessibility Code Generation
Generate accessibility code from Figma annotations:
Annotations: [A11Y_LAYER_DATA]
Component type: [COMPONENT_TYPE]
Required:
- ARIA labels and descriptions
- Keyboard navigation support
- Focus management
- Screen reader optimization
- Color contrast compliance
- Semantic HTML structure
Reference WCAG 2.1 AA standards.
Examples16 / 20
Example 1: Button Component Input: Figma button with size/variant properties
JSON{ "variants": { "size": ["small", "medium", "large"], "variant": ["primary", "secondary", "ghost"] }, "states": ["default", "hover", "focus", "disabled"] }
Output:
TypeScriptinterface ButtonProps { size?: 'small' | 'medium' | 'large'; variant?: 'primary' | 'secondary' | 'ghost'; disabled?: boolean; } const Button = styled.button<ButtonProps>` padding: ${({ size }) => tokens.spacing[size]}; background: ${({ variant }) => tokens.colors.button[variant]}; &:hover:not(:disabled) { background: ${({ variant }) => tokens.colors.button[`${variant}Hover`]}; } `;
Example 2: Responsive Card Layout Input: Figma auto-layout card with min-width constraints Output:
CSS.card-grid { display: grid; grid-template-columns: repeat(auto-fit, minmax(320px, 1fr)); gap: clamp(1rem, 2.5vw, 2rem); container-type: inline-size; } @container (max-width: 400px) { .card { padding: 1rem; } }
Recommendation▾
Include specific error handling and troubleshooting for common Figma API limitations or design inconsistencies
Best Practices
Token Extraction:
- Map Figma variables to CSS custom properties 1:1
- Preserve semantic naming from Figma
- Extract computed values for complex expressions
Component Structure:
- Use compound components for complex UI patterns
- Implement forwarded refs for DOM access
- Include TypeScript for design system consistency
Visual Accuracy:
- Compare rendered output to Figma screenshots
- Use browser dev tools to match exact spacing/sizing
- Test across breakpoints defined in Figma
Performance:
- Generate minimal CSS without unused properties
- Use CSS containment for layout optimization
- Lazy load complex interactions
Common Pitfalls
Avoid:
- Hardcoding pixel values instead of using design tokens
- Missing responsive behavior from auto-layout constraints
- Incomplete variant combinations
- Ignoring Figma component instance overrides
- Not handling edge cases in interaction states
Validation Steps:
- Screenshot comparison between Figma and rendered code
- Test all variant/state combinations
- Verify responsive behavior at constraint breakpoints
- Validate accessibility with screen readers
- Check performance with React DevTools
Production Export
Final checklist:
- All design tokens properly referenced
- TypeScript interfaces complete
- Documentation generated from Figma descriptions
- Storybook stories for all variants
- Unit tests for component logic
- Visual regression tests setup
Target: 80% visual accuracy on first generation, 95% after one iteration.