Install
npx skillscat add aidotnet/moyucode/sharp Install via the SkillsCat registry.
About this skill
This skill provides a Node.js library for high‑performance image resizing, format conversion, and manipulation using libvips. It solves the need for fast, efficient image processing in applications that handle JPEG, PNG, WebP, AVIF, or TIFF files. Use it when developers require rapid image transformations without heavy resource consumption.
SKILL.md
Sharp Tool
Description
High-performance image processing for resizing, converting, and manipulating images.
Source
- Repository: lovell/sharp
- License: Apache-2.0
Installation
npm install sharpUsage Examples
Resize Image
import sharp from 'sharp';
// Resize to specific dimensions
await sharp('input.jpg')
.resize(800, 600)
.toFile('output.jpg');
// Resize with aspect ratio preserved
await sharp('input.jpg')
.resize(800, null) // Width 800, auto height
.toFile('output.jpg');
// Resize with fit options
await sharp('input.jpg')
.resize(800, 600, {
fit: 'cover', // cover, contain, fill, inside, outside
position: 'center' // center, top, right, bottom, left
})
.toFile('output.jpg');Convert Format
// Convert to WebP
await sharp('input.jpg')
.webp({ quality: 80 })
.toFile('output.webp');
// Convert to AVIF (modern format)
await sharp('input.jpg')
.avif({ quality: 60 })
.toFile('output.avif');
// Convert to PNG with transparency
await sharp('input.jpg')
.png({ compressionLevel: 9 })
.toFile('output.png');Image Manipulation
// Rotate and flip
await sharp('input.jpg')
.rotate(90)
.flip()
.toFile('output.jpg');
// Blur and sharpen
await sharp('input.jpg')
.blur(5)
.sharpen()
.toFile('output.jpg');
// Grayscale and tint
await sharp('input.jpg')
.grayscale()
.tint({ r: 255, g: 128, b: 0 })
.toFile('output.jpg');
// Crop
await sharp('input.jpg')
.extract({ left: 100, top: 100, width: 500, height: 300 })
.toFile('output.jpg');Add Watermark
async function addWatermark(input: string, watermark: string, output: string) {
const image = sharp(input);
const { width, height } = await image.metadata();
// Resize watermark
const watermarkBuffer = await sharp(watermark)
.resize(Math.round(width! * 0.2))
.toBuffer();
await image
.composite([{
input: watermarkBuffer,
gravity: 'southeast',
blend: 'over',
}])
.toFile(output);
}Generate Thumbnails
async function generateThumbnails(input: string, sizes: number[]) {
const image = sharp(input);
await Promise.all(sizes.map(size =>
image
.clone()
.resize(size, size, { fit: 'cover' })
.jpeg({ quality: 80 })
.toFile(`thumb-${size}.jpg`)
));
}
// Usage
await generateThumbnails('photo.jpg', [64, 128, 256, 512]);Stream Processing
import { createReadStream, createWriteStream } from 'fs';
// Process large images with streams
createReadStream('large-input.jpg')
.pipe(sharp().resize(1920, 1080).jpeg({ quality: 85 }))
.pipe(createWriteStream('output.jpg'));Tags
image, resize, convert, thumbnail, processing
Compatibility
- Codex: ✅
- Claude Code: ✅