Sharp

Name: Sharp
Author: aidotnet

aidotnet/moyucode

30 installs
84 repo stars
Updated January 28, 2026
aidotnet/moyucode

sharp is a Claude Code skill that provides TypeScript recipes for the lovell/sharp Node.js library to resize, convert, and manipulate images.

About

sharp is a Claude Code skill that wraps the lovell/sharp Node.js image-processing library. It gives the agent ready TypeScript recipes to resize, convert format, crop, watermark, and generate thumbnails for JPEG, PNG, WebP, AVIF, and TIFF images. A developer uses it when adding image transformation to a Node backend or build pipeline.

Wraps the lovell/sharp Node.js library for image processing
Resize, convert, and manipulate JPEG, PNG, WebP, AVIF, and TIFF images
Includes recipes for watermarks, thumbnails, and stream processing

Sharp by the numbers

30 all-time installs (skills.sh)
Ranked #969 of 1,335 Generative Media skills by installs in the Skillselion catalog
Data as of Jul 28, 2026 (Skillselion catalog sync)

At a glance

sharp capabilities & compatibility

Capabilities: image resize · format conversion · thumbnail generation · watermark
Use cases: image generation
Pricing: Free

From the docs

What sharp says it does

High-performance image processing for resizing, converting, and manipulating images.

SKILL.md

npm install sharp

SKILL.md

`image`, `resize`, `convert`, `thumbnail`, `processing`

SKILL.md

npx skills add https://github.com/aidotnet/moyucode --skill sharp

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Installs	30
repo stars	★ 84
Last updated	January 28, 2026
Repository	aidotnet/moyucode ↗

What it does

Generate TypeScript code to resize, convert, watermark, and thumbnail images with the sharp library in a Node.js project.

Who is it for?

Adding image resize, format conversion, and thumbnail generation to a Node.js backend or build step.

When should I use this skill?

You need to resize, convert, watermark, or thumbnail images in a Node.js/TypeScript project.

What you get

Produces working sharp TypeScript code for resize, convert, crop, watermark, and thumbnail tasks.

TypeScript image-processing code
thumbnail generation function
watermark compositing function

By the numbers

Covers 5 image formats: JPEG, PNG, WebP, AVIF, TIFF

Files

SKILL.mdMarkdownGitHub ↗

Sharp Tool

Description

High-performance image processing for resizing, converting, and manipulating images.

Source

Repository: lovell/sharp
License: Apache-2.0

Installation

npm install sharp

Usage 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'));