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/dev-gom/claude-code-marketplace/unity-scene-optimizernpx skills add Dev-GOM/claude-code-marketplace --skill unity-scene-optimizergit clone --depth 1 https://github.com/Dev-GOM/claude-code-marketplaceWhat 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 | $0.00033 | $0.00773 |
| Opus 5 | $0.00016 | $0.00387 |
| Sonnet 5 | $0.00007 | $0.00155 |
| Haiku 4.5 | $0.00003 | $0.00077 |
Grade A, and why
Unity Scene Optimizer 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 2d 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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Unity Scene Optimizer
Analyzes Unity scenes and provides performance optimization recommendations for rendering, physics, memory, and platform-specific concerns.
What This Skill Analyzes
1. Rendering Performance
Analyzes draw calls (target: <100 mobile, <2000 desktop), identifies batching opportunities, recommends material consolidation and static batching.
2. Texture Optimization
Reviews compression formats (BC7/ASTC), mipmap usage, texture atlasing, and platform-specific import settings.
3. GameObject Hierarchy
Targets: <500 GameObjects mobile, <2000 desktop. Identifies deep nesting, recommends object pooling and LOD groups.
4. Lighting and Shadows
Recommends baked lighting over realtime (1-2 lights mobile, 3-4 desktop), minimal shadow-casting lights.
5. Physics Optimization
Analyzes Rigidbody count, collider complexity, collision matrix configuration. Recommends simple colliders over Mesh colliders.
6. Mobile-Specific
Platform targets: 60 FPS iOS (iPhone 12+), 30-60 FPS Android. See mobile-checklist.md for complete requirements.
Optimization Workflow
- Measure: Frame Debugger, Stats, Profiler metrics
- Identify: GPU/CPU/Memory/Physics bottlenecks
- Apply: Quick wins (static batching, compression) → Medium (atlases, pooling, LOD) → Major (hierarchy refactor, culling)
- Validate: Compare before/after metrics
See optimization-workflow.md for detailed steps and timelines.
Platform-Specific Targets
| Platform | Draw Calls | Triangles | Texture Memory | Lights |
|---|---|---|---|---|
| Mobile Low | <50 | <20k | <100MB | 1 |
| Mobile Mid | <100 | <50k | <250MB | 1-2 |
| Mobile High | <150 | <100k | <500MB | 2-3 |
| PC Low | <500 | <200k | <1GB | 3-4 |
| PC Mid | <1000 | <500k | <2GB | 4-6 |
| PC High | <2000 | <1M | <4GB | 6-8 |
| Console | <1000 | <800k | <3GB | 4-6 |
Tools Reference
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.
- 2d ago First seen · 74 lines · 33 tokens per session scan A 69b8a6951150
Unity Scene Optimizer is a skill published in the GitHub repository Dev-GOM/claude-code-marketplace (97 stars, last pushed 7mo ago), licensed Apache-2.0. It adds 33 tokens to every session and 773 once invoked, about $0.0002 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 2026-08-30.
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