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Snapdom

CommunityPopular
2025Emma
snapdom

snapDOM is a fast, accurate DOM-to-image capture tool that converts HTML elements into scalable SVG images. Use for capturing HTML elements, converting DOM to images (SVG, PNG, JPG, WebP), preserving styles, fonts, and pseudo-elements.

Overview

Publisher2025Emma
Repositoryvibe-coding-cn
Skill namesnapdom
Stars
23K
Forks
2.4K
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by 2025Emma on GitHub. Read the source before you install it.

Installation

Install the Snapdom AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/2025Emma/vibe-coding-cn.git /tmp/vibe-coding-cn
mkdir -p .claude/skills
cp -r /tmp/vibe-coding-cn/i18n/zh/skills/snapdom .claude/skills/snapdom
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Snapdom in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Snapdom on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Snapdom is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

SnapDOM Skill

Fast, dependency-free DOM-to-image capture library for converting HTML elements into scalable SVG or raster image formats.

When to Use This Skill

Use SnapDOM when you need to:

  • Convert HTML elements to images (SVG, PNG, JPG, WebP)
  • Capture styled DOM with pseudo-elements and shadows
  • Export elements with embedded fonts and icons
  • Create screenshots with custom dimensions or scaling
  • Handle CORS-blocked resources using proxy fallback
  • Implement custom rendering pipelines with plugins
  • Optimize performance on large or complex elements

Key Features

Universal Export Options

  • SVG - Scalable vector format, embeds all styles
  • PNG, JPG, WebP - Raster formats with configurable quality
  • Canvas - Get raw Canvas element for further processing
  • Blob - Raw binary data for custom handling

Performance

  • Ultra-fast capture (1.6ms for small elements, ~171ms for 4000×2000)
  • No dependencies - Uses standard Web APIs only
  • Outperforms html2canvas by 10-40x on complex elements

Style Support

  • Embedded fonts (including icon fonts)
  • CSS pseudo-elements (::before, ::after)
  • CSS counters
  • CSS line-clamp
  • Transform and shadow effects
  • Shadow DOM content

Advanced Capabilities

  • Same-origin iframe support
  • CORS proxy fallback for blocked assets
  • Plugin system for custom transformations
  • Straighten transforms (remove rotate/translate)
  • Selective element exclusion
  • Tight bounding box calculation

Installation

NPM/Yarn

bash
npm install @zumer/snapdom
# or
yarn add @zumer/snapdom

CDN (ES Module)

html
<script type="module">
  import { snapdom } from "https://unpkg.com/@zumer/snapdom/dist/snapdom.mjs";
</script>

CDN (UMD)

html
<script src="https://unpkg.com/@zumer/snapdom/dist/snapdom.umd.js"></script>

Quick Start Examples

Basic Reusable Capture

javascript
// Create reusable capture object
const result = await snapdom(document.querySelector('#target'));

// Export to different formats
const png = await result.toPng();
const jpg = await result.toJpg();
const svg = await result.toSvg();
const canvas = await result.toCanvas();
const blob = await result.toBlob();

// Use the result
document.body.appendChild(png);

One-Step Export

javascript
// Direct export without intermediate object
const png = await snapdom.toPng(document.querySelector('#target'));
const svg = await snapdom.toSvg(element);

Download Element

javascript
// Automatically download as file
await snapdom.download(element, 'screenshot.png');
await snapdom.download(element, 'image.svg');

With Options

javascript
const result = await snapdom(element, {
  scale: 2,                    // 2x resolution
  width: 800,                  // Custom width
  height: 600,                 // Custom height
  embedFonts: true,            // Include @font-face
  exclude: '.no-capture',      // Hide elements
  useProxy: true,              // Enable CORS proxy
  straighten: true,            // Remove transforms
  noShadows: false             // Keep shadows
});

const png = await result.toPng({ quality: 0.95 });

Essential Options Reference

OptionTypePurpose
scaleNumberScale output (e.g., 2 for 2x resolution)
widthNumberCustom output width in pixels
heightNumberCustom output height in pixels
embedFontsBooleanInclude non-icon @font-face rules
useProxyString|BooleanEnable CORS proxy (URL or true for default)
excludeStringCSS selector for elements to hide
straightenBooleanRemove translate/rotate transforms
noShadowsBooleanStrip shadow effects

Common Patterns

Responsive Screenshots

javascript
// Capture at different scales
const mobile = await snapdom.toPng(element, { scale: 1 });
const tablet = await snapdom.toPng(element, { scale: 1.5 });
const desktop = await snapdom.toPng(element, { scale: 2 });

Exclude Elements

javascript
// Hide specific elements from capture
const png = await snapdom.toPng(element, {
  exclude: '.controls, .watermark, [data-no-capture]'
});

Fixed Dimensions

javascript
// Capture with specific size
const result = await snapdom(element, {
  width: 1200,
  height: 630  // Standard social media size
});

CORS Handling

javascript
// Fallback for CORS-blocked resources
const png = await snapdom.toPng(element, {
  useProxy: 'https://cors.example.com/?' // Custom proxy
});

Plugin System (Beta)

javascript
// Extend with custom exporters
snapdom.plugins([pluginFactory, { colorOverlay: true }]);

// Hook into lifecycle
defineExports(context) {
  return {
    pdf: async (ctx, opts) => { /* generate PDF */ }
  };
}

// Lifecycle hooks available:
// beforeSnap → beforeClone → afterClone →
// beforeRender → beforeExport → afterExport

Performance Comparison

SnapDOM significantly outperforms html2canvas:

ScenarioSnapDOMhtml2canvasImprovement
Small (200×100)1.6ms68ms42x faster
Medium (800×600)12ms280ms23x faster
Large (4000×2000)171ms1,800ms10x faster

Development

Setup

bash
git clone https://github.com/zumerlab/snapdom.git
cd snapdom
npm install

Build

bash
npm run compile

Testing

bash
npm test

Browser Support

  • Chrome/Edge 90+
  • Firefox 88+
  • Safari 14+
  • Mobile browsers (iOS Safari 14+, Chrome Mobile)

Resources

Documentation

scripts/

Add helper scripts here for automation, e.g.:

  • batch-screenshot.js - Capture multiple elements
  • pdf-export.js - Convert snapshots to PDF
  • compare-outputs.js - Compare SVG vs PNG quality

assets/

Add templates and examples:

  • HTML templates for common capture scenarios
  • CSS frameworks pre-configured with snapdom
  • Boilerplate projects integrating snapdom

Related Tools

Tips & Best Practices

  1. Performance: Use scale instead of width/height for better performance
  2. Fonts: Set embedFonts: true to ensure custom fonts appear correctly
  3. CORS Issues: Use useProxy: true if images fail to load
  4. Large Elements: Break into smaller chunks for complex pages
  5. Quality: For PNG/JPG, use quality: 0.95 for best quality
  6. SVG Vectors: Prefer SVG export for charts and graphics

Troubleshooting

Elements Not Rendering

  • Check if element has sufficient height/width
  • Verify CSS is fully loaded before capture
  • Try straighten: false if transforms are causing issues

Missing Fonts

  • Set embedFonts: true
  • Ensure fonts are loaded before calling snapdom
  • Check browser console for font loading errors

CORS Issues

  • Enable useProxy: true
  • Use custom proxy URL if default fails
  • Check if resources are from same origin

Performance Issues

  • Reduce scale value
  • Use noShadows: true to skip shadow rendering
  • Consider splitting large captures into smaller sections

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Snapdom AI skill do?

snapDOM is a fast, accurate DOM-to-image capture tool that converts HTML elements into scalable SVG images. Use for capturing HTML elements, converting DOM to images (SVG, PNG, JPG, WebP), preserving styles, fonts, and pseudo-elements.

Why use Snapdom on TypingMind?

Because you install it once and use it with any model. Snapdom is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Snapdom in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/2025Emma/vibe-coding-cn/tree/main/i18n/zh/skills/snapdom. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Snapdom?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Snapdom?

As many as you like. As long as a model supports skills, you can use Snapdom with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Snapdom AI skill free?

Yes. It is published on GitHub by 2025Emma under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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