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Webgpu Threejs Tsl

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dgreenheck
webgpu-threejs-tsl

Comprehensive guide for developing WebGPU-enabled Three.js applications using TSL (Three.js Shading Language). Covers WebGPU renderer setup, TSL syntax and node materials, compute shaders, post-processing effects, and WGSL integration. Use this skill when working with Three.js WebGPU, TSL shaders, node materials, or GPU compute in Three.js.

Overview

Publisherdgreenheck
Repositorywebgpu-claude-skill
Skill namewebgpu-threejs-tsl
Stars
1.2K
Forks
110
Bundled files
15
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.

  • 15 bundled files

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

  • Open source

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

Installation

Install the Webgpu Threejs Tsl 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/dgreenheck/webgpu-claude-skill.git /tmp/webgpu-claude-skill
mkdir -p .claude/skills
cp -r /tmp/webgpu-claude-skill/skills/webgpu-threejs-tsl .claude/skills/webgpu-threejs-tsl
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Webgpu Threejs Tsl 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 Webgpu Threejs Tsl 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 Webgpu Threejs Tsl 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.

WebGPU Three.js with TSL

TSL (Three.js Shading Language) is a node-based shader abstraction that lets you write GPU shaders in JavaScript instead of GLSL/WGSL strings.

Quick Start

javascript
import * as THREE from 'three/webgpu';
import { color, time, oscSine } from 'three/tsl';

const renderer = new THREE.WebGPURenderer();
await renderer.init();

const material = new THREE.MeshStandardNodeMaterial();
material.colorNode = color(0xff0000).mul(oscSine(time));

Skill Contents

Documentation

  • docs/core-concepts.md - Types, operators, uniforms, control flow
  • docs/materials.md - Node materials and all properties
  • docs/compute-shaders.md - GPU compute with instanced arrays
  • docs/post-processing.md - Built-in and custom effects
  • docs/wgsl-integration.md - Custom WGSL functions
  • docs/device-loss.md - Handling GPU device loss and recovery
  • docs/limits-and-features.md - WebGPU device limits and optional features

Examples

  • examples/basic-setup.js - Minimal WebGPU project
  • examples/custom-material.js - Custom shader material
  • examples/particle-system.js - GPU compute particles
  • examples/post-processing.js - Effect pipeline
  • examples/earth-shader.js - Complete Earth with atmosphere

Templates

  • templates/webgpu-project.js - Starter project template
  • templates/compute-shader.js - Compute shader template

Reference

  • REFERENCE.md - Quick reference cheatsheet

Key Concepts

Import Pattern

javascript
// Always use the WebGPU entry point
import * as THREE from 'three/webgpu';
import { /* TSL functions */ } from 'three/tsl';

Node Materials

Replace standard material properties with TSL nodes:

javascript
material.colorNode = texture(map);        // instead of material.map
material.roughnessNode = float(0.5);      // instead of material.roughness
material.positionNode = displaced;         // vertex displacement

Method Chaining

TSL uses method chaining for operations:

javascript
// Instead of: sin(time * 2.0 + offset) * 0.5 + 0.5
time.mul(2.0).add(offset).sin().mul(0.5).add(0.5)

Custom Functions

Use Fn() for reusable shader logic:

javascript
const fresnel = Fn(([power = 2.0]) => {
  const nDotV = normalWorld.dot(viewDir).saturate();
  return float(1.0).sub(nDotV).pow(power);
});

When to Use This Skill

  • Setting up Three.js with WebGPU renderer
  • Creating custom shader materials with TSL
  • Writing GPU compute shaders
  • Building post-processing pipelines
  • Migrating from GLSL to TSL
  • Implementing visual effects (particles, water, terrain, etc.)

Resources

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 Webgpu Threejs Tsl AI skill do?

Comprehensive guide for developing WebGPU-enabled Three.js applications using TSL (Three.js Shading Language). Covers WebGPU renderer setup, TSL syntax and node materials, compute shaders, post-processing effects, and WGSL integration. Use this skill when working with Three.js WebGPU, TSL shaders, node materials, or GPU compute in Three.js.

Why use Webgpu Threejs Tsl on TypingMind?

Because you install it once and use it with any model. Webgpu Threejs Tsl 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 Webgpu Threejs Tsl in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dgreenheck/webgpu-claude-skill/tree/main/skills/webgpu-threejs-tsl. 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 Webgpu Threejs Tsl?

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 Webgpu Threejs Tsl?

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

Is the Webgpu Threejs Tsl AI skill free?

It is published on GitHub by dgreenheck. Check the repository for licensing terms. 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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