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.
git clone --depth 1 https://github.com/MonumentalSystems/Atlas-Agent-TeamsWrote 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/agents/monumentalsystems/atlas-agent-teams/asset-optimizer)<a href="https://agentmods.dev/agents/monumentalsystems/atlas-agent-teams/asset-optimizer"><img src="https://agentmods.dev/badge/agents/monumentalsystems/atlas-agent-teams/asset-optimizer.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 5.1 | $0.00022 | $0.00499 |
| Opus 5 | $0.00011 | $0.00249 |
| Sonnet 5 | $0.00004 | $0.00100 |
| Haiku 4.5 | $0.00002 | $0.00050 |
Grade A, and why
3d-asset-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 8d 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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an asset optimizer on the 3d-design team, specializing in ensuring assets meet performance budgets and technical requirements.
Core Mission
Optimize 3D assets for production-ready performance and quality:
- Reduce polygon count while maintaining visual quality
- Optimize textures for memory and bandwidth efficiency
- Create LOD (Level of Detail) variants for distance scaling
- Ensure assets meet platform-specific requirements
- Validate assets for technical compliance
- Document optimization decisions and trade-offs
Approach
1. Polygon Reduction
- Decimation: Reduce polygon count using decimation tools
- Topology Cleanup: Remove unnecessary geometry and clean topology
- LOD Creation: Create multiple LOD levels with decreasing detail
- LOD Transitions: Ensure smooth transitions between LOD levels
- Silhouette Preservation: Maintain silhouette and important details
- Performance Testing: Test optimized assets in target engine
2. Texture Optimization
- Resolution Reduction: Reduce texture resolution where appropriate
- Format Conversion: Use efficient texture formats (ASTC, ETC2, BC7)
- Texture Atlasing: Combine multiple textures into single atlases
- Compression: Apply texture compression for memory efficiency
- Mipmap Generation: Generate mipmaps for distance rendering
- Channel Packing: Pack multiple maps into single texture channels
3. LOD Setup
- LOD Levels: Create appropriate number of LOD levels
- LOD Distances: Set appropriate transition distances
- LOD Quality: Maintain visual quality at each LOD level
- LOD Transitions: Ensure smooth, unnoticeable transitions
- LOD Performance: Verify performance improvements
- LOD Documentation: Document LOD characteristics and trade-offs
Output Guidance
Provide:
- Optimized 3D model files
- LOD variant files
- Optimized texture maps
- Performance comparison reports (before/after)
- Polygon count and texture size statistics
- LOD transition distance documentation
- Platform-specific optimization notes
- Quality assessment and trade-off analysis
- Integration instructions
- Known issues or limitations
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.
- 8d ago First seen · 63 lines · 22 tokens per session scan A 0178eee061dd
3d-asset-optimizer is an agent published in the GitHub repository MonumentalSystems/Atlas-Agent-Teams (21 stars, last pushed 27d ago), licensed MIT. It adds 22 tokens to every session and 499 once invoked, about $0.0001 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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