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/frabcd/codex-ai-game-studio/material-texture-generatenpx skills add frabcd/codex-ai-game-studio --skill material-texture-generategit clone --depth 1 https://github.com/frabcd/codex-ai-game-studioWrote 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/frabcd/codex-ai-game-studio/material-texture-generate)<a href="https://agentmods.dev/skills/frabcd/codex-ai-game-studio/material-texture-generate"><img src="https://agentmods.dev/badge/skills/frabcd/codex-ai-game-studio/material-texture-generate.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 | $0.00029 | $0.00447 |
| Opus 5 | $0.00015 | $0.00224 |
| Sonnet 5 | $0.00006 | $0.00089 |
| Haiku 4.5 | $0.00003 | $0.00045 |
Grade A, and why
material-texture-generate 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 5d 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Material Texture Generate
Outcome
Create coherent material maps whose physical interpretation survives engine import.
Required inputs
- surface brief and rights-cleared references
- target shader workflow
- resolution, texel density, tiling scale, and compression budget
Ask for missing information only when it changes the route materially. Otherwise state conservative assumptions and proceed with read-only analysis.
Workflow
- Define material class, real-world scale, lighting assumptions, map channels, color spaces, and packing convention.
- Choose a licensed generation route compatible with available hardware.
- Generate source maps without replacing existing project textures.
- Validate seamless tiling, albedo range, roughness response, normal orientation, height continuity, and channel packing.
- Preview on representative geometry under neutral and production lighting, then test engine import and compression.
Expected artifacts
- material specification
- source and packed maps
- sphere and plane previews
- engine material instance
- provenance record
Workflow-specific gates
- Treat base color as color data and linear maps as non-color data.
- Never infer legal reuse from a reference image being publicly visible.
- Flag baked lighting, inconsistent scale, edge seams, clipping, and implausible metallic values.
Production completion gate
Before recommending production use, complete and report all seven gates:
- Rights, consent, code/model/dataset/output license, and generation-provenance checks.
- Technical format, naming, scale, color, metadata, and target-import validation.
- Visual and temporal consistency review across representative views and states.
- Runtime memory, frame-time, draw-call, streaming, and asset-budget checks.
- Playability and interaction smoke tests in the target runtime.
- Screenshot, capture, diff, or artifact-regression evidence with reproducible settings.
- Human approval before replacing source assets or promoting generated output.
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.
- 5d ago First seen · 58 lines · 29 tokens per session scan A 6d6880c3ad33
material-texture-generate is a skill published in the GitHub repository frabcd/codex-ai-game-studio (9 stars, last pushed 5d ago), licensed MIT. It adds 29 tokens to every session and 447 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 2026-08-31.
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game-build
Build a risk-matched whitebox or the approved production game for its target runtime. Turn GAMEDESIGN, and ARTDIRECTION when production begins, into a minimal BUILDBRIEF and a runnable candidate that can be iterated with replayable evidence. Use for prototype the riskiest design question, implement the approved game…
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game-qa
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