Render millions of interactive 3D particles at 60fps using BufferGeometry and InstancedMesh.
mkdir -p ~/.agents/skills/threejs-particle-system-gpu && curl -fsSL https://askills.dev/api/skills/threejs-particle-system-gpu/raw -o ~/.agents/skills/threejs-particle-system-gpu/SKILL.md
Client Trigger & Invocation Simulator
$threejs-particle-system-gpu <your task>Type `$threejs-particle-system-gpu` in the chat or invoke via natural language. Codex automatically identifies the skill from ~/.agents/skills or project .skills, mounts bundled scripts, and executes inside the workspace sandbox.
$threejs-particle-system-gpu Render a galaxy spiral particle cloud with 200,000 points and dynamic rotation.
Overview & Problem Solved
When modern frontier LLMs (like Claude 3.7, GPT-4o, or deep reasoning agents) execute complex domain tasks without standard operating procedures, they frequently suffer from context drift, incorrect CLI arguments, or non-standard file hierarchies. Three.js GPU Instanced Particle Systems eliminates probabilistic guessing by supplying the Agent with an authoritative, sandboxed execution specification.
By packaging verified workflows into a structured SKILL.md manifest, this skill establishes deterministic boundaries, verifies dependencies, and executes tasks using proven engineering conventions.
Operational Impact: Without Skill vs. With Skill
Raw frontier models possess deep knowledge, but probabilistic prompting lacks rigid engineering guardrails. Packaging Three.js GPU Instanced Particle Systems into a verified SKILL.md transforms speculative model behavior into reproducible, deterministic delivery.
- Speculative CLI Flags: Model guesses experimental command arguments or deprecated API endpoints.
- Lazy Placeholder Code: Outputs
// TODO: implement error handlingor skips critical verification phases. - Directory Pollution: Generates non-standard file structures that break existing project linters and monorepo roots.
- Extraneous Context Bloat: Wastes thousands of output tokens on narrative pleasantries rather than verified deliverables.
function process() {
// TODO: Connect database here
console.log("Done");
}- Codified Workflow Stages: Follows strict step-by-step algorithms explicitly codified in SKILL.md.
- Zero-Placeholder Delivery: Every deliverable is 100% implemented, with complete error boundaries and types.
- Automatic Pre-Flight Check: Agent inspects environment dependencies (Python/Node/Docker) before modifying files.
- Self-Healing Verification: Runs automated linting, test suites, or syntax parsers before concluding the turn.
export async function execute() {
const validated = schema.parse(input);
return await auditAndPersist(validated);
}Core Capabilities & Guarantees
Follows pre-tested instructions and step-by-step algorithms, avoiding experimental or hallucinated flags.
Runs with identical behavioral fidelity across OpenAI Codex, Claude Code, Cursor IDE, and Windsurf Cascade.
Enforces workspace-scoped file mutations and shields environment secrets against accidental prompt leakage.
Automates test verification, linter checks, and syntax validation before completing any user turn.
Agent Execution Pipeline
Intent Matching & Context Ingestion
The agent scans the user request against the skill's YAML frontmatter triggers and loads the verified instructions into active working memory.
Toolchain & Dependency Validation
The runtime verifies that necessary tools, interpreters, and environment configurations exist within the workspace sandbox before proceeding.
Deterministic Execution & Delivery
The agent executes the codified SOP, runs verification checks, and outputs high-fidelity deliverables without extraneous narration.
Validated Prompt Templates
(Click to copy)“Render a galaxy spiral particle cloud with 200,000 points and dynamic rotation.”
“Animate instanced cube meshes responding to audio frequency data or cursor proximity.”
“Apply circular alpha mask textures to PointsMaterial to eliminate rectangular particle artifacts.”
Automated Security & Audit Report
Workspace Scoped
Cannot escape workspace rootInstruction Only
Zero system subprocessesOffline Sandbox
No internet egressNone Required
Runs fully standaloneEnterprise & Production Use Cases
Frequently Asked Questions
Q: What makes Three.js GPU Instanced Particle Systems different from a standard MCP server?
MCP (Model Context Protocol) provides external protocol connections to databases or APIs. In contrast, Three.js GPU Instanced Particle Systems is a high-level operational skill (SKILL.md) that teaches AI Agents procedural intelligence, deterministic step-by-step SOPs, parameter constraints, and self-correction workflows.
Q: Is Three.js GPU Instanced Particle Systems compatible with frontier models like Claude 3.7 Sonnet, GPT-4o, and DeepSeek-R1?
Yes. The skill is packaged with standard markdown instructions (SKILL.md) and YAML frontmatter, adhering to the universal agent skill standard natively supported across Codex, Claude Code, Cursor, and Windsurf.
Q: What permissions does Three.js GPU Instanced Particle Systems require in agent mode?
Every listed skill undergoes automated static analysis scoring 98/100. It strictly adheres to workspace-scoped filesystem boundaries and does not execute untrusted remote code.
Q: Can our team customize or extend the rules in this SKILL.md?
Yes. Once installed in your project root (.skills/threejs-particle-system-gpu/SKILL.md or ~/.agents/skills/threejs-particle-system-gpu/), you can customize the instructions to include internal team guidelines, custom linters, or proprietary APIs.
SKILL.md Source Specification
---
name: "threejs-particle-system-gpu"
description: "Render millions of interactive 3D particles at 60fps using BufferGeometry and InstancedMesh."
metadata:
author: "Mr.doob"
version: "1.0.0"
runtime_compatibility:
- "codex"
- "claude-code"
- "cursor"
- "windsurf"
triggers:
- "create particle cloud threejs"
- "use instancedmesh threejs"
- "animate points buffergeometry"
permissions:
fs_read: true
fs_write: "workspace"
shell_exec: false
net_access: false
---
# Three.js GPU Instanced Particle Systems
Builds high-performance particle fields, galaxy simulations, and point clouds using Three.js PointsMaterial, custom Float32Array buffer attributes, and GPU instancing.
## When to Invoke
Invoke this skill whenever you need to:
- create particle cloud threejs
- use instancedmesh threejs
- animate points buffergeometry
## Execution SOP & Rules
1. Store positions in a flat Float32Array and attach to BufferGeometry with setAttribute('position').
2. Use InstancedMesh when particles require distinct 3D geometry rather than flat billboard points.
3. Enable pointsMaterial.depthWrite = false and blending = THREE.AdditiveBlending for luminous effects.
4. Compute transformations on the GPU or via Web Workers to keep the JavaScript main thread idle.
## Verification Checklist
- Run local linting, syntax validation, and type-checks before reporting completion.
- Ensure all created or modified files adhere to workspace boundaries and avoid uncommitted secrets.
- Verify tests or build commands exit cleanly with return code 0.
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