Agent skill
mock-spec-extractor
Extracts design specifications from mock images including colors, typography, spacing, and component details
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/mock-spec-extractor
Metadata
Additional technical details for this skill
- author
- babysitter-sdk
- version
- 1.0.0
- category
- design-analysis
SKILL.md
mock-spec-extractor
You are mock-spec-extractor - a specialized skill for extracting comprehensive design specifications from mock images.
Overview
This skill analyzes design mock images to extract structured specifications including colors, typography, spacing patterns, and component details that serve as the source of truth for pixel-perfect implementation.
Prerequisites
- Node.js 18+ installed
- Image processing libraries (sharp, jimp)
- Color extraction libraries (node-vibrant, color-thief)
- OCR capabilities for text analysis (optional)
Capabilities
1. Color Palette Extraction
const Vibrant = require('node-vibrant');
async function extractColors(mockPath) {
const palette = await Vibrant.from(mockPath).getPalette();
return {
primary: palette.Vibrant?.hex,
secondary: palette.Muted?.hex,
accent: palette.DarkVibrant?.hex,
background: palette.LightMuted?.hex,
text: palette.DarkMuted?.hex,
allColors: Object.entries(palette)
.filter(([_, swatch]) => swatch)
.map(([name, swatch]) => ({
name,
hex: swatch.hex,
rgb: swatch.rgb,
population: swatch.population
}))
};
}
2. Layout Structure Analysis
async function analyzeLayout(mockPath) {
const image = await sharp(mockPath).metadata();
// Detect major sections through edge detection
const edges = await detectEdges(mockPath);
// Identify grid patterns
const gridAnalysis = await detectGridPattern(edges);
return {
dimensions: { width: image.width, height: image.height },
sections: identifySections(edges),
grid: gridAnalysis,
hierarchy: buildHierarchy(sections)
};
}
3. Typography Detection
async function detectTypography(mockPath, regions) {
const textStyles = [];
for (const region of regions) {
// Extract text regions
const textAreas = await findTextAreas(mockPath, region);
for (const area of textAreas) {
textStyles.push({
region: region.name,
estimatedSize: estimateFontSize(area),
estimatedWeight: estimateWeight(area),
color: extractDominantColor(area),
position: area.bounds
});
}
}
return deduplicateStyles(textStyles);
}
4. Spacing Pattern Recognition
async function analyzeSpacing(mockPath, elements) {
const spacingValues = [];
// Analyze gaps between elements
for (let i = 0; i < elements.length - 1; i++) {
const gap = calculateGap(elements[i], elements[i + 1]);
spacingValues.push(gap);
}
// Identify spacing scale
const scale = identifySpacingScale(spacingValues);
return {
scale,
patterns: groupByPattern(spacingValues),
recommendations: suggestCSSVariables(scale)
};
}
5. Component Detection
async function detectComponents(mockPath) {
const components = [];
// Detect buttons
const buttons = await detectButtons(mockPath);
components.push(...buttons.map(b => ({ type: 'button', ...b })));
// Detect cards
const cards = await detectCards(mockPath);
components.push(...cards.map(c => ({ type: 'card', ...c })));
// Detect inputs
const inputs = await detectInputs(mockPath);
components.push(...inputs.map(i => ({ type: 'input', ...i })));
return components;
}
Input Schema
{
"type": "object",
"required": ["mockSource"],
"properties": {
"mockSource": {
"type": "object",
"properties": {
"type": { "type": "string", "enum": ["image", "figma", "url"] },
"path": { "type": "string" }
}
},
"analysisDepth": {
"type": "string",
"enum": ["basic", "detailed", "comprehensive"],
"default": "detailed"
},
"focusAreas": {
"type": "array",
"items": { "type": "string" }
}
}
}
Output Schema
{
"type": "object",
"properties": {
"success": { "type": "boolean" },
"designSpec": {
"type": "object",
"properties": {
"layout": { "type": "object" },
"typography": { "type": "object" },
"colorPalette": { "type": "object" },
"spacing": { "type": "object" },
"components": { "type": "array" },
"decorativeElements": { "type": "array" }
}
},
"cssVariables": { "type": "object" },
"implementationNotes": { "type": "array" }
}
}
Process Integration
This skill integrates with:
pixel-perfect-implementation.js- Provides mock analysis for convergencedesign-system.js- Extracts design tokenscomponent-library.js- Identifies component patterns
Usage Example
/skill mock-spec-extractor \
--mock designs/dashboard-mock.png \
--depth comprehensive \
--focus "header,sidebar,cards"
Best Practices
- High-resolution mocks - Use 2x resolution for better analysis
- Clean backgrounds - Solid backgrounds improve detection
- Consistent naming - Name regions consistently for tracking
- Validate extractions - Review and refine extracted specs
- Iterate with feedback - Use scoring feedback to improve extraction
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agent-ops-spec
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agent-ops-state
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