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-performancegit 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-performance)<a href="https://agentmods.dev/skills/bbeierle12/skill-mcp-claude/r3f-performance"><img src="https://agentmods.dev/badge/skills/bbeierle12/skill-mcp-claude/r3f-performance/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-performance"><img src="https://agentmods.dev/badge/skills/bbeierle12/skill-mcp-claude/r3f-performance.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 | $0.00056 | $0.02607 |
| Opus 5 | $0.00028 | $0.01303 |
| Sonnet 5 | $0.00011 | $0.00521 |
| Haiku 4.5 | $0.00006 | $0.00261 |
Grade A, and why
r3f-performance 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 — 441 lines — stays where its author put it; the contents beside it link to each section on GitHub.
R3F Performance
Optimize render performance through draw call reduction, geometry optimization, smart loading, and profiling.
Quick Start
// Performance-optimized Canvas
<Canvas
dpr={[1, 2]} // Limit pixel ratio
performance={{ min: 0.5 }} // Adaptive performance
frameloop="demand" // Only render on change
gl={{
powerPreference: 'high-performance',
antialias: false // Disable for mobile
}}
>
<Suspense fallback={null}>
<Scene />
</Suspense>
</Canvas>
Frame Budget
Target 60fps = 16.67ms per frame. Budget breakdown:
| Phase | Target | Notes |
|---|---|---|
| JavaScript | < 4ms | useFrame logic, state updates |
| GPU Render | < 10ms | Draw calls, shaders |
| Compositing | < 2ms | Post-processing, overlays |
| Buffer | ~1ms | Safety margin |
Draw Call Optimization
The Golden Rule
Fewer draw calls > fewer triangles
A scene with 100 meshes of 1000 triangles each is slower than 1 mesh of 100,000 triangles.
Reduction Techniques
| Technique | Draw Calls | When to Use |
|---|---|---|
| Instancing | 1 per unique mesh | 100+ identical objects |
| Merged geometry | 1 per merged batch | Static scene parts |
| Texture atlases | Fewer materials | Many similar textures |
| LOD | Reduces complexity | Large/distant objects |
Instancing (Best for Identical Meshes)
// 10,000 cubes = 1 draw call
<instancedMesh args={[undefined, undefined, 10000]}>
<boxGeometry />
<meshStandardMaterial />
</instancedMesh>
Geometry Merging (Static Scenes)
import { useMemo } from 'react';
import { mergeGeometries } from 'three/examples/jsm/utils/BufferGeometryUtils';
import * as THREE from 'three';
function MergedScene() {
const mergedGeometry = useMemo(() => {
const geometries: THREE.BufferGeometry[] = [];
// Create many positioned geometries
for (let i = 0; i < 100; i++) {
const geo = new THREE.BoxGeometry(1, 1, 1);
geo.translate(
(Math.random() - 0.5) * 20,
(Math.random() - 0.5) * 20,
(Math.random() - 0.5) * 20
);
geometries.push(geo);
}
return mergeGeometries(geometries);
}, []);
return (
<mesh geometry={mergedGeometry}>
<meshStandardMaterial />
</mesh>
);
}
What ships with it
1 file 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 · 441 lines · 56 tokens per session scan A 9db6f5158051
r3f-performance is a skill published in the GitHub repository Bbeierle12/Skill-MCP-Claude (8 stars, last pushed today), licensed MIT. It adds 56 tokens to every session and 2,607 once invoked, about $0.0003 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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