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Webf Native Plugins

OrganizationPopular
openwebf
webf-native-plugins

Install WebF native plugins to access platform capabilities like sharing, payment, camera, geolocation, and more. Use when building features that require native device APIs beyond standard web APIs.

Overview

Publisheropenwebf
Repositorywebf
Skill namewebf-native-plugins
Stars
2.5K
Forks
163
Bundled files
1
LicenseGPL-3.0
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Webf Native Plugins 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/openwebf/webf.git /tmp/webf
mkdir -p .claude/skills
cp -r /tmp/webf/skills/webf-native-plugins .claude/skills/webf-native-plugins
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Webf Native Plugins 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 Webf Native Plugins 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 Webf Native Plugins 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.

WebF Native Plugins

When building WebF apps, you often need access to native platform capabilities like sharing content, accessing the camera, handling payments, or using geolocation. WebF provides native plugins that bridge JavaScript code with native platform APIs.

What Are Native Plugins?

Native plugins are packages that:

  • Provide native platform capabilities (share, camera, payments, sensors, etc.)
  • Work across iOS, Android, macOS, and other platforms
  • Use JavaScript APIs in your code
  • Require both Flutter and npm package installation
  • Bridge to native platform APIs through Flutter

When to Use Native Plugins

Use native plugins when you need capabilities that aren't available in standard web APIs:

Use Native Plugins For:

  • Sharing content to other apps
  • Accessing device camera or photo gallery
  • Processing payments
  • Getting geolocation with native accuracy
  • Push notifications
  • Biometric authentication (Face ID, fingerprint)
  • Device sensors (accelerometer, gyroscope)
  • File system access beyond web storage
  • Native calendar/contacts integration

Standard Web APIs Work Without Plugins:

  • fetch() for HTTP requests
  • localStorage for local storage
  • Canvas 2D for graphics
  • Geolocation API (basic)
  • Media queries for responsive design

Finding Available Plugins

Before implementing a feature, always check if a pre-built native plugin exists:

  1. Visit the official plugin registry: https://openwebf.com/en/native-plugins
  2. Browse available plugins by category
  3. Check the plugin documentation for installation steps

Installation Process

Every native plugin requires TWO installations:

  1. Flutter side (in your Flutter host app)
  2. JavaScript side (in your web project)

Step 1: Check Plugin Availability

Visit https://openwebf.com/en/native-plugins and search for the capability you need:

  • Click on the plugin to view details
  • Note the Flutter package name (e.g., webf_share)
  • Note the npm package name (e.g., @openwebf/webf-share)

Step 2: Install Flutter Package

If you have access to the Flutter project hosting your WebF app:

  1. Open the Flutter project's pubspec.yaml
  2. Add the plugin dependency:
    yaml
    dependencies:
      webf_share: ^1.0.0  # Replace with actual plugin name
  3. Run flutter pub get
  4. Register the plugin in your main Dart file:
    dart
    import 'package:webf/webf.dart';
    import 'package:webf_share/webf_share.dart';  // Import the plugin
    
    void main() {
      // Initialize WebFControllerManager
      WebFControllerManager.instance.initialize(WebFControllerManagerConfig(
        maxAliveInstances: 2,
        maxAttachedInstances: 1,
      ));
    
      // Register the native plugin module
      WebF.defineModule((context) => ShareModule(context));
    
      runApp(MyApp());
    }

Step 3: Install npm Package

In your JavaScript/TypeScript project:

bash
# For the Share plugin example
npm install @openwebf/webf-share

# Or with yarn
yarn add @openwebf/webf-share

Step 4: Use in Your JavaScript Code

Import and use the plugin in your application:

typescript
import { WebFShare } from '@openwebf/webf-share';

// Use the plugin API
const success = await WebFShare.shareText({
  title: 'My App',
  text: 'Check out this amazing content!',
  url: 'https://example.com'
});

Available Plugins

Share Plugin (webf_share)

Description: Share content, text, and images through native platform sharing

Capabilities:

  • Share text, URLs, and titles to other apps
  • Share images using native sharing mechanisms
  • Save screenshots to device storage
  • Create preview images for temporary display

Flutter Package: webf_share: ^1.0.0

npm Package: @openwebf/webf-share

Example Usage:

typescript
import { WebFShare, ShareHelpers } from '@openwebf/webf-share';

// Share text content
await WebFShare.shareText({
  title: 'Article Title',
  text: 'Check out this article!',
  url: 'https://example.com/article'
});

// Share an image from canvas
const canvas = document.getElementById('myCanvas');
const imageData = ShareHelpers.canvasToArrayBuffer(canvas);
await WebFShare.shareImage(imageData);

// Save screenshot
await WebFShare.saveScreenshot(imageData);

Storage Locations:

  • Android: Downloads folder (/storage/emulated/0/Download/)
  • iOS: App documents directory (accessible via Files app)
  • macOS: Application documents directory (accessible via Finder)

See the Native Plugins Reference for more available plugins.

Common Patterns

1. Feature Detection

Always check if a plugin is available before using it:

typescript
// Check if plugin is loaded
if (typeof WebFShare !== 'undefined') {
  await WebFShare.shareText({ text: 'Hello' });
} else {
  // Fallback or show message
  console.log('Share plugin not available');
}

2. Error Handling

Wrap plugin calls in try-catch blocks:

typescript
try {
  const success = await WebFShare.shareText({
    title: 'My App',
    text: 'Check this out!'
  });

  if (success) {
    console.log('Content shared successfully');
  }
} catch (error) {
  console.error('Failed to share:', error);
  // Show error message to user
}

3. TypeScript Type Safety

All plugins include TypeScript definitions:

typescript
import type { ShareTextOptions } from '@openwebf/webf-share';

const shareOptions: ShareTextOptions = {
  title: 'Article',
  text: 'Read this article',
  url: 'https://example.com'
};

await WebFShare.shareText(shareOptions);

Creating Custom Plugins

If you need capabilities not provided by existing plugins, you can create your own:

  1. Read the Plugin Development Guide: https://openwebf.com/en/docs/developer-guide/native-plugins
  2. Study existing plugins: https://github.com/openwebf/webf/tree/main/webf_modules
  3. Follow the plugin architecture:
    • Create a Flutter package implementing the native functionality
    • Create an npm package exposing JavaScript APIs
    • Use WebF's module system to bridge between them

Troubleshooting

Issue: Plugin Not Found in JavaScript

Cause: Flutter package not installed or module not registered

Solution:

  1. Check that the Flutter package is in pubspec.yaml
  2. Verify the module is registered with WebF.defineModule() in main.dart
  3. Run flutter pub get
  4. Rebuild the Flutter app
  5. Restart WebF Go or your app

Issue: TypeScript Errors

Cause: npm package not installed correctly

Solution:

bash
# Reinstall the package
npm install @openwebf/webf-share --save

# Clear cache and reinstall
rm -rf node_modules package-lock.json
npm install

Issue: Plugin Works on iOS but Not Android

Cause: Platform-specific permissions or configuration missing

Solution:

  1. Check the plugin documentation for required permissions
  2. Add necessary permissions to AndroidManifest.xml or Info.plist
  3. Some plugins require additional native configuration

Issue: "Module is not defined" Error

Cause: Plugin module not registered in Flutter

Solution: Make sure you're calling WebF.defineModule() in your Flutter main() function before runApp():

dart
void main() {
  WebF.defineModule((context) => ShareModule(context));
  runApp(MyApp());
}

Best Practices

1. Check Plugin Availability First

Before implementing a feature, visit https://openwebf.com/en/native-plugins to see if a plugin already exists. Don't reinvent the wheel.

2. Test on Multiple Platforms

Native plugins may behave differently on iOS vs Android vs macOS:

  • Test on all target platforms
  • Handle platform-specific behavior gracefully
  • Read plugin docs for platform differences

3. Provide Fallbacks

Not all users may have the plugin installed (especially during development):

typescript
if (typeof WebFShare !== 'undefined') {
  // Use native sharing
  await WebFShare.shareText({ text: 'Hello' });
} else {
  // Fallback: copy to clipboard or show a link
  navigator.clipboard.writeText('Hello');
}

4. Handle Permissions Properly

Some plugins require user permissions (camera, location, etc.):

  • Request permissions at appropriate times
  • Explain why you need the permission
  • Handle permission denial gracefully
  • Check plugin docs for permission requirements

5. Keep Plugins Updated

Native plugins are updated to support new platform features and fix bugs:

  • Check for plugin updates regularly
  • Read changelogs before updating
  • Test thoroughly after updating

Production Deployment

When deploying to production:

  1. Flutter App: Make sure all required plugins are in pubspec.yaml
  2. npm Packages: Include all plugin packages in package.json
  3. Permissions: Configure all required permissions in app manifests
  4. Testing: Test on real devices for all target platforms
  5. Documentation: Document which plugins your app requires

Resources

Next Steps

After installing native plugins:

  1. Read plugin documentation: Each plugin has specific APIs and requirements
  2. Test on devices: Native features work differently than web APIs
  3. Handle errors: Native calls can fail due to permissions or platform limitations
  4. Consider alternatives: Check webf-api-compatibility for web API alternatives

Summary

  • Native plugins provide access to platform capabilities beyond web APIs
  • Check https://openwebf.com/en/native-plugins for available plugins
  • Install BOTH Flutter package (pubspec.yaml) AND npm package
  • Register plugins with WebF.defineModule() in main.dart
  • Use feature detection and error handling in JavaScript
  • Test on all target platforms
  • Create custom plugins if needed using the Plugin Development Guide

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 Webf Native Plugins AI skill do?

Install WebF native plugins to access platform capabilities like sharing, payment, camera, geolocation, and more. Use when building features that require native device APIs beyond standard web APIs.

Why use Webf Native Plugins on TypingMind?

Because you install it once and use it with any model. Webf Native Plugins 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 Webf Native Plugins in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/openwebf/webf/tree/main/skills/webf-native-plugins. 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 Webf Native Plugins?

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 Webf Native Plugins?

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

Is the Webf Native Plugins AI skill free?

Yes. It is published on GitHub by openwebf under the GPL-3.0 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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