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 agentmods add skills/devinilabs/pro-skill/optimize-threejs-gamesnpx skills add devinilabs/pro-skill --skill optimize-threejs-gamesgit clone --depth 1 https://github.com/devinilabs/pro-skillWrote 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/devinilabs/pro-skill/optimize-threejs-games)<a href="https://agentmods.dev/skills/devinilabs/pro-skill/optimize-threejs-games"><img src="https://agentmods.dev/badge/skills/devinilabs/pro-skill/optimize-threejs-games.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00057 | $0.00313 |
| Opus 5 | $0.00028 | $0.00156 |
| Sonnet 5 | $0.00011 | $0.00063 |
| Haiku 4.5 | $0.00006 | $0.00031 |
Grade A, and why
optimize-threejs-games 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 4d 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.
This is a copy
100% identical to optimize-threejs-games — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Optimize Three.js Games
Measure before changing behavior, then validate the same gameplay path after every optimization.
Establish a repeatable scene
Choose a deterministic representative encounter and record device, viewport, quality level, player position, enemies, active effects, frame-time sample, draw calls, triangles, texture count, and warnings. Compare like with like.
Diagnose the limiting side
- Suspect CPU when simulation, allocations, React work, pathfinding, or per-frame scans grow with actors.
- Suspect GPU when resolution, overdraw, shadows, transparent particles, post-processing, draw calls, geometry, or texture bandwidth dominate.
- Inspect before optimizing; do not lower quality blindly.
Apply low-risk fixes first
Reuse geometry/materials, pool transient effects, cull inactive/offscreen work, throttle noncritical UI updates, cap particle counts, avoid per-frame allocation, and update only changed transforms. Keep render quality settings explicit and reversible. Degrade decorative effects before combat readability or controls.
Guard the result
Re-run the original encounter and verify frame time, visual correctness, collision/contact behavior, memory stability, mobile controls, reduced motion, and console health. Close temporary servers, benchmarks, and browser tabs once they are no longer needed.
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.
- 4d ago First seen · 27 lines · 57 tokens per session scan A d50e8c26ae81
optimize-threejs-games is a skill published in the GitHub repository devinilabs/pro-skill (20 stars, last pushed 21d ago), licensed MIT. It adds 57 tokens to every session and 313 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to optimize-threejs-games, differing in 0 lines, and is treated as a copy.
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