image-analysis
$
npx mdskill add TerminalSkills/skills/image-analysisExtract dominant colors from images to match design palettes.
- Converts screenshots and mockups into usable color palettes.
- Depends on pixel data processing and color computation algorithms.
- Sorts results by prominence to prioritize the most visible hues.
- Delivers structured hex, RGB, and HSL values in JSON format.
SKILL.md
.github/skills/image-analysisView on GitHub ↗
---
name: image-analysis
description: >-
Analyze images to extract colors, composition, mood, and visual elements using Vision AI.
Use when: extracting color palettes from images, analyzing design screenshots, understanding
visual style of reference images.
license: MIT
compatibility: "Node.js 18+"
metadata:
author: terminal-skills
version: "1.0.0"
category: design
tags: [image-analysis, color-palette, design, visual, claude]
---
# Image Analysis — Color Extraction
## Overview
Extract dominant colors from any image file (PNG, JPG, WebP, BMP, GIF) and return a structured palette. Useful for implementing UIs that match a screenshot, Figma export, or design mockup.
- The user provides a screenshot or design image and wants to implement it
- The user asks to extract or identify colors from an image
- The user wants a color palette from a photo or mockup
- The user wants to match their code's colors to a reference image
## Instructions
1. Reads the image file using `get-pixels` to obtain raw pixel data
2. Passes pixel data to `extract-colors` to compute dominant colors
3. Returns a sorted palette (by area/prominence) with hex, RGB, HSL values, and area coverage
Run the extraction script, passing the image path as the first argument:
```bash
bash <skill-path>/scripts/extract-colors.sh /path/to/image.png
```
**Arguments:**
- `$1` — Path to the image file (required). Supports PNG, JPG, WebP, BMP, GIF.
The script outputs a JSON array of colors sorted by prominence:
```json
[
{
"hex": "#1a1a2e",
"red": 26, "green": 26, "blue": 46,
"hue": 0.6667, "saturation": 0.2778, "lightness": 0.1412,
"area": 0.3241
}
]
```
After extracting colors, present them as a structured palette and suggest how to use them (CSS custom properties, Tailwind config theme colors, design token definitions, or direct usage in component styles).
## Examples
### Example 1: Extract colors from a landing page screenshot
```bash
bash <skill-path>/scripts/extract-colors.sh ./screenshot.png
```
Output:
```
Color Palette (sorted by prominence):
1. #1a1a2e — 32.4% (dark navy) — Primary background
2. #e94560 — 18.6% (coral red) — Accent color
3. #f5f5f5 — 15.2% (light gray) — Secondary background
```
### Example 2: Extract colors from a Figma export for Tailwind config
```bash
bash <skill-path>/scripts/extract-colors.sh ~/Downloads/figma-design.jpg
```
Use the extracted hex values to populate a Tailwind `theme.extend.colors` config:
```js
colors: {
primary: '#1a1a2e',
accent: '#e94560',
surface: '#f5f5f5',
}
```
## Guidelines
- The script auto-installs dependencies (`extract-colors`, `get-pixels`) on first run. If this fails, install them manually with `cd <skill-path>/scripts && npm install`.
- Supported formats: PNG, JPG, GIF, BMP. For other formats, convert the image first.
- The `extract-colors` library automatically downsamples to 64,000 pixels by default, so large images are already handled efficiently.
- Pair with the `contrast-check` skill to verify that extracted color combinations meet WCAG accessibility standards.