Tracely is a CI/CD system for AI agents that turns failed production traces into replayable regression tests. Development teams use it to detect and group agent failures, run the resulting cases on pull requests, and block changes that reproduce those failures. The catalogue entries provide skills for operating this trace-based testing and observability workflow.
Borrowing it
Nothing to install: this file belongs to Jwuthri/Tracely-ai. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Jwuthri/Tracely-ai/master/.agents/skills/threejs-r3f/SKILL.mdgit clone --depth 1 https://github.com/Jwuthri/Tracely-aiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jwuthri/tracely-ai/threejs-r3f)<a href="https://agentmods.dev/skills/jwuthri/tracely-ai/threejs-r3f"><img src="https://agentmods.dev/badge/skills/jwuthri/tracely-ai/threejs-r3f/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jwuthri/tracely-ai/threejs-r3f"><img src="https://agentmods.dev/badge/skills/jwuthri/tracely-ai/threejs-r3f.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00026 | $0.01848 |
| Opus 5.5 | $0.00010 | $0.00739 |
| Sonnet 5.5 | $0.00005 | $0.00370 |
| Haiku 4.5 | $0.00003 | $0.00185 |
Grade A, and why
threejs-r3f scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
2 near-identical copies found in the catalogue:
- threejs-r3f — 100% identical, 0 lines differ
- threejs-r3f — 100% identical
How it starts
The opening of the file, as written. The whole thing — 244 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Three.js & React Three Fiber
3D on the web. Three.js is the engine, R3F is the React renderer. Concise rules here. Deep-dive in
references/.
When to Use What
| Need | Tool | Why |
|---|---|---|
| Full 3D scene (models, lights, physics) | R3F + drei | Declarative, React-friendly, ecosystem |
| Vanilla 3D (no React) | Three.js direct | Lighter, no React overhead |
| Simple 3D transforms on UI | CSS transform3d |
GPU-composited, no WebGL context |
| 2D particles / generative | Canvas 2D | Simpler API, less GPU overhead |
| Shader-only visuals (no scene graph) | Raw WebGL / ShaderMaterial | Maximum control, minimal abstraction |
Scene Setup Patterns
import { Canvas } from '@react-three/fiber'
import { Environment, OrbitControls } from '@react-three/drei'
import { Suspense } from 'react'
<Canvas camera={{ position: [0, 2, 5], fov: 45 }} dpr={[1, 2]} gl={{ antialias: true }}>
<Suspense fallback={null}>
<Environment preset="studio" />
<OrbitControls makeDefault />
<Scene />
</Suspense>
</Canvas>
Rules:
- Always wrap scene content in
<Suspense>-- loaders (GLTF, textures, HDRI) need it - Set
dpr={[1, 2]}to clamp pixel ratio (Retina without melting GPUs) - Keep the Canvas parent component minimal -- re-renders propagate into the scene
R3F Hooks
| Hook | Purpose | Gotcha |
|---|---|---|
useFrame((state, delta) => {}) |
Per-frame logic (animation, physics) | Never setState inside |
useThree() |
Access gl, scene, camera, size, viewport, pointer | Destructure only what you need |
useLoader(TextureLoader, url) |
Load any Three.js resource | Wrap parent in Suspense |
useGraph(scene) |
Extract nodes/materials from loaded scene | Useful after useGLTF |
useFrame Tips
useFrame((state, delta) => {
// Use delta for framerate-independent animation
meshRef.current.rotation.y += delta * 0.5
// Access clock for time-based effects
material.uniforms.uTime.value = state.clock.elapsedTime
})
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 244 lines · 26 tokens per session scan A aeee54f83cd7
threejs-r3f is a skill published in the GitHub repository Jwuthri/Tracely-ai (1,311 stars, last pushed yesterday), licensed MIT. It adds 26 tokens to every session and 1,848 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
threejs-r3f compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| threejs-r3fJwuthri/Tracely-ai | Skill | 1.3k | yesterday | MIT | A | 26 | Claude Code, Codex |
| factory-releasetikalk/adlc-team-skills | Skill | 145 | yesterday | MIT | A | 72 | Claude Code, Codex |
| pin-mcp-serversyotambraun/Toolscore | Skill | 6 | 6d ago | Apache-2.0 | A | 107 | Claude Code |
| Prompt Version Control WorkflowNotysoty/openagentskills | Skill | 9 | 2mo ago | MIT | A | 30 | Claude Code, Codex |
| llm-testerbuiphucminhtam/forgewright | Skill | 49 | 2d ago | none | A | 49 | Claude Code |
| report-repairastandrik/my_instructions | Skill | 6 | 1mo ago | MIT | A | 16 | Claude Code |
| local-validatorastandrik/my_instructions | Skill | 6 | 1mo ago | MIT | A | 20 | Claude Code |