Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Bbeierle12/Skill-MCP-Claude --skill r3f-fundamentalsgit clone --depth 1 https://github.com/Bbeierle12/Skill-MCP-ClaudeWrote 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/bbeierle12/skill-mcp-claude/r3f-fundamentals)<a href="https://agentmods.dev/skills/bbeierle12/skill-mcp-claude/r3f-fundamentals"><img src="https://agentmods.dev/badge/skills/bbeierle12/skill-mcp-claude/r3f-fundamentals/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/bbeierle12/skill-mcp-claude/r3f-fundamentals"><img src="https://agentmods.dev/badge/skills/bbeierle12/skill-mcp-claude/r3f-fundamentals.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 | $0.00078 | $0.02951 |
| Opus 5 | $0.00039 | $0.01476 |
| Sonnet 5 | $0.00016 | $0.00590 |
| Haiku 4.5 | $0.00008 | $0.00295 |
Grade A, and why
r3f-fundamentals 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 473 lines — stays where its author put it; the contents beside it link to each section on GitHub.
React Three Fiber Fundamentals
Declarative Three.js via React components. R3F maps Three.js objects to JSX elements with automatic disposal, reactive updates, and React lifecycle integration.
Quick Start
import { Canvas } from '@react-three/fiber';
function App() {
return (
<Canvas>
<ambientLight intensity={0.5} />
<pointLight position={[10, 10, 10]} />
<mesh>
<boxGeometry args={[1, 1, 1]} />
<meshStandardMaterial color="hotpink" />
</mesh>
</Canvas>
);
}
Core Principle: Declarative Scene Graph
R3F converts Three.js imperative API to React's declarative model:
| Three.js (Imperative) | R3F (Declarative) |
|---|---|
new THREE.Mesh() |
<mesh> |
mesh.position.set(1, 2, 3) |
<mesh position={[1, 2, 3]}> |
scene.add(mesh) |
JSX nesting handles hierarchy |
mesh.geometry.dispose() |
Automatic on unmount |
Canvas Configuration
import { Canvas } from '@react-three/fiber';
<Canvas
// Renderer settings
gl={{ antialias: true, alpha: false, powerPreference: 'high-performance' }}
dpr={[1, 2]} // Device pixel ratio range
shadows // Enable shadow maps
// Camera (default: PerspectiveCamera)
camera={{
fov: 75,
near: 0.1,
far: 1000,
position: [0, 0, 5]
}}
// Or use orthographic
orthographic
camera={{ zoom: 50, position: [0, 0, 100] }}
// Performance
frameloop="demand" // 'always' | 'demand' | 'never'
performance={{ min: 0.5 }} // Adaptive performance
// Events
onCreated={({ gl, scene, camera }) => {
// Access Three.js objects after mount
}}
// Sizing
style={{ width: '100vw', height: '100vh' }}
/>
Frameloop Modes
| Mode | When to Use |
|---|---|
always |
Continuous animation (games, simulations) |
demand |
Static scenes, only re-render on state change |
never |
Manual control via invalidate() |
What ships with it
3 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.
- 11d ago First seen · 473 lines · 78 tokens per session scan A 3e8511803b62
r3f-fundamentals is a skill published in the GitHub repository Bbeierle12/Skill-MCP-Claude (8 stars, last pushed yesterday), licensed MIT. It adds 78 tokens to every session and 2,951 once invoked, about $0.0004 per session on Opus 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 2026-08-31.
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