asset-optimization

asset-optimization is a skill for Claude Code from MonumentalSystems/Atlas-Agent-Teams. It costs 18 tokens per session (1,995 once invoked), scanned A, original, MIT.

Guidance for making 3D assets smaller and faster to display. It covers reducing mesh polygons, creating level-of-detail versions, and compressing textures.

In plain words
What is it for?
Optimizing models and textures for real-time applications such as games, simulations, and interactive 3D scenes.
Why use it?
It helps reduce rendering workload and memory use while keeping important visual detail. It also gives ways to check that optimized assets still look acceptable.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the 3d-design plugin — 9 skills, 2 commands, 7 agents, 1 hook, 7 MCP servers shipped together

Good fit Optimizing models and textures for real-time applications such as games, simulations, and interactive 3D scenes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/monumentalsystems/atlas-agent-teams/asset-optimization
Install

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.

Any agent
npx skills add MonumentalSystems/Atlas-Agent-Teams --skill asset-optimization
Clone the repo
git clone --depth 1 https://github.com/MonumentalSystems/Atlas-Agent-Teams

Made for: Claude Code.

Or install 3d-design, the plugin that ships this one along with the rest of its 9 skills, 2 commands, 7 agents, 1 hook, 7 MCP servers.

Wrote 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.

agentmods badge for asset-optimization

README.md
[![agentmods](https://agentmods.dev/badge/skills/monumentalsystems/atlas-agent-teams/asset-optimization/github.svg)](https://agentmods.dev/skills/monumentalsystems/atlas-agent-teams/asset-optimization)
Your own site
<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.

agentmods 80×15 button for asset-optimization

Your own site · 80×15
<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>
Per session 18 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,995 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 9d ago against content hash b614b4afa0cd, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

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.

teams/3d-design/skills/asset-optimization/SKILL.md · 204 lines

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

Read the full file on GitHub · 204 lines

Changes

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.

  1. 9d ago First seen · 204 lines · 18 tokens per session scan A b614b4afa0cd

Subscribe to this mod's changes

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.