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 MonumentalSystems/Atlas-Agent-Teams --skill asset-optimizationgit 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/skills/monumentalsystems/atlas-agent-teams/asset-optimization)<a href="https://agentmods.dev/skills/monumentalsystems/atlas-agent-teams/asset-optimization"><img src="https://agentmods.dev/badge/skills/monumentalsystems/atlas-agent-teams/asset-optimization/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/monumentalsystems/atlas-agent-teams/asset-optimization"><img src="https://agentmods.dev/badge/skills/monumentalsystems/atlas-agent-teams/asset-optimization.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00018 | $0.01995 |
| Opus 5 | $0.00009 | $0.00997 |
| Sonnet 5 | $0.00004 | $0.00399 |
| Haiku 4.5 | $0.00002 | $0.00199 |
Grade A, and why
asset-optimization 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 9d 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 — 204 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Asset Optimization
Polygon Reduction Techniques
Decimation
- Decimation Algorithms: Reduce polygon count while preserving shape
- Decimation Tools: Use decimation modifiers or tools
- Decimation Ratio: Set appropriate decimation ratio
- Silhouette Preservation: Maintain silhouette and important details
- Topology Cleanup: Clean topology after decimation
- Quality Assessment: Assess visual quality after decimation
Retopology
- Retopology Tools: Use retopology tools for clean topology
- Manual Retopology: Manual retopology for quality control
- Automatic Retopology: Automatic retopology for speed
- Quad-Based Topology: Maintain quad-based topology
- Edge Flow: Maintain proper edge flow for deformation
- Topology Optimization: Optimize topology for performance
Polygon Reduction Best Practices
- Prioritize Important Areas: Keep detail in visible areas
- Reduce in Less Visible Areas: Reduce polygons in less visible areas
- Maintain Silhouette: Preserve silhouette and important shapes
- Clean Topology: Maintain clean, optimized topology
- Test in Engine: Test optimized assets in target engine
- Iterative Process: Iterate and refine as needed
LOD (Level of Detail) Creation
LOD Levels
- LOD0: Highest detail, closest distance
- LOD1: Medium detail, medium distance
- LOD2: Low detail, far distance
- LOD3+: Very low detail, very far distance
- LOD Count: Determine appropriate LOD count based on asset importance
- LOD Distances: Set appropriate transition distances
LOD Creation Techniques
- Manual LOD Creation: Manually create LOD levels
- Automatic LOD Generation: Automatically generate LOD levels
- Decimation: Use decimation for LOD generation
- Retopology: Use retopology for LOD generation
- Material Reduction: Reduce material complexity for LODs
- Texture Reduction: Reduce texture resolution for LODs
LOD Transitions
- Transition Distance: Set appropriate transition distances
- Smooth Transitions: Ensure smooth transitions between LODs
- Dithering: Use dithering for smoother transitions
- Hysteresis: Use hysteresis to prevent flickering
- Testing: Test LOD transitions in target engine
- Performance: Verify performance improvements
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.
- 9d ago First seen · 204 lines · 18 tokens per session scan A b614b4afa0cd
asset-optimization is a skill published in the GitHub repository MonumentalSystems/Atlas-Agent-Teams (21 stars, last pushed 29d ago), licensed MIT. It adds 18 tokens to every session and 1,995 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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