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 vladmdgolam/agent-skills --skill threejs-perf-loadinggit clone --depth 1 https://github.com/vladmdgolam/agent-skillsWrote 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/vladmdgolam/agent-skills/threejs-perf-loading)<a href="https://agentmods.dev/skills/vladmdgolam/agent-skills/threejs-perf-loading"><img src="https://agentmods.dev/badge/skills/vladmdgolam/agent-skills/threejs-perf-loading/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/vladmdgolam/agent-skills/threejs-perf-loading"><img src="https://agentmods.dev/badge/skills/vladmdgolam/agent-skills/threejs-perf-loading.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 | $0.00262 | $0.06945 |
| Opus 5.5 | $0.00105 | $0.02778 |
| Sonnet 5.5 | $0.00052 | $0.01389 |
| Haiku 4.5 | $0.00026 | $0.00694 |
Grade A, and why
threejs-perf-loading 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.
How it starts
The opening of the file, as written. The whole thing — 566 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Three.js Performance & Loading Patterns
Patterns drawn from studying modern Three.js/WebGPU production sites built by top-notch studios and developers, each solving a different piece of "make a heavy real-time scene feel instant and never stutter." This file distills the transferable patterns, organized by what problem they solve.
Don't treat any of this as an au-courant checklist to apply wholesale — each technique below traded something (code complexity, a stubbed physical behavior, a hard cutoff) for its win. Read the "cost" note on each one before copying it.
1. Loading & warmup — hide compile/decode cost behind the spinner
The classic symptom this section solves: loading bar hits 100%, then a 1-2 second freeze before the scene appears. That freeze is (almost always) the GPU driver compiling shader pipelines on first use — WebGL/WebGPU compile lazily, per unique material/uniform combination, the first time it's drawn. If your loading screen only waits for asset fetch, you've hidden network latency but not compile latency.
Fix: force every pipeline to compile while the loading UI is still up, by
actually rendering through it once. (Source: ivress-brand-site-teardown.md)
// Simplified from the ivress renderer's warmup phase.
class WarmupRenderer {
async runWarmupFrame(camera) {
// 1. Activate the section/state whose materials you're about to warm.
this._activateSection(this.warmupSectionIndex);
// 2. Disable frustum culling for this pass — you need EVERY mesh to
// actually draw, including ones off-screen from this camera, or its
// pipeline never compiles.
const culled = [];
scene.traverse((o) => {
if (o.isMesh && o.frustumCulled) { o.frustumCulled = false; culled.push(o); }
});
// 3. Render a handful of real frames through the FULL post-processing
// chain (bloom, grade, everything) — not a stripped-down warm pass.
// Uncompiled post nodes will still stall on first real use otherwise.
this.scenePass.camera = camera;
await this.postProcessing.render();
culled.forEach((o) => { o.frustumCulled = true; });
// 4. Advance to the next section/state and repeat until every
// section's material set has drawn at least once.
}
completeWarmup() {
this._restoreOriginalState();
// Wait 2 RAFs + a microtask — let the compositor fully settle —
// THEN fire the event your loading UI listens for to fade out.
requestAnimationFrame(() => requestAnimationFrame(() => queueMicrotask(() => {
emit('compileEnd'); // safe to also start loading non-critical assets now
emit('reveal', { isIn: true });
})));
}
}
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 · 566 lines · 262 tokens per session scan A fb58f1f850a0
threejs-perf-loading is a skill published in the GitHub repository vladmdgolam/agent-skills (9 stars, last pushed 23d ago), licensed MIT. It adds 262 tokens to every session and 6,945 once invoked, about $0.0010 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-perf-loading compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| threejs-perf-loadingvladmdgolam/agent-skills | Skill | 9 | 23d ago | MIT | A | 262 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | today | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | today | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 314k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 103 | Claude Code |