Godogen is a generator that lets coding agents create complete games for Godot, Bevy, or Babylon.js from a short description. It is for people who want an agent to build, generate assets for, run, and demonstrate a game project. The catalogue add-ons are instructions and skills used by Claude Code and Codex during that game-building workflow.
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 htdt/godogen --skill asset-gengit clone --depth 1 https://github.com/htdt/godogenWrote 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/htdt/godogen/asset-gen)<a href="https://agentmods.dev/skills/htdt/godogen/asset-gen"><img src="https://agentmods.dev/badge/skills/htdt/godogen/asset-gen/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/htdt/godogen/asset-gen"><img src="https://agentmods.dev/badge/skills/htdt/godogen/asset-gen.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00108 | $0.01621 |
| Opus 5.5 | $0.00043 | $0.00648 |
| Sonnet 5.5 | $0.00022 | $0.00324 |
| Haiku 4.5 | $0.00011 | $0.00162 |
Grade A, and why
asset-gen 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- asset-gen — 92% identical, 139 lines differ
How it starts
The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Asset Generator
Assets come from godogen_assets: local generators on this machine's GPU, one command per task, free. Its checkout here is ${GODOGEN_ASSETS}, and its docs are the reference; this page is the TL;DR plus what the game needs on top. Read ${GODOGEN_ASSETS}/README.md once (conventions, a character start to finish, checking results), and a part's README up to How it works before first using its tool.
| Command | Makes | README in the checkout |
|---|---|---|
qwen-image |
PNG from text; rgba: real transparency; edit -i ref.png: image-to-image |
image/ |
gen3d |
textured GLB from an image | mesh/ |
mia-rig |
Mixamo-rigged humanoid from a GLB | rig/ |
add-moves, gen-moves |
idle/walk/run/jump onto a rig; custom moves from text prompts | motion/ |
grip-prop |
a prop made holdable; add-moves --hold puts it in a character's hand |
motion/ |
lipsync |
speaking mouth + lip-synced clip from a voice line | lipsync/ |
stable-audio |
sound effects, seamless ambience loops | sfx/ |
qwen-tts |
voice lines from a description, or cloned from a reference line | voice/ |
A character: qwen-image rgba (T-pose) → gen3d → mia-rig --fingers --anim none → add-moves, with gen-moves for custom moves and lipsync for speech. Props stop after gen3d; one a character holds goes on through grip-prop and add-moves --hold, never by an offset tuned in the engine.
- Always pass
-ointo the project; without it, results land in the godogen_assets checkout. - One GPU job at a time, minutes per call. Run GPU tools as one sequential batch with a long timeout or in the background, never as parallel calls.
- Game budget.
gen3ddefaults to ~500k triangles and 2048² textures; pass--faces/--tex(30000 / 1024 for a character). - Style families. Generate one hero asset, derive the rest with
qwen-image edit -i hero.png, prompting only what changes. - Small sprites. A 1024px image downscaled to 64px looks muddy: design display sizes ≥128px, prompt bold flat forms, or generate a kit (several objects in one image) and slice it with
python3 ${ASSET_GEN_SKILL_DIR}/tools/grid_slice.py kit.png -o out/ --grid 2x2 --names "a,b,c,d". - Direction. Generators get left/right and facing wrong; generate one direction and flip at runtime.
- Audio format. Every tool picks it from the
-oextension. Bevy's default features decode only Ogg Vorbis, so write.oggfor Bevy. - Review before building on it. Look at every PNG. You can't look at a GLB or hear a WAV: render GLBs (
${GODOGEN_ASSETS}/README.md, Checking results) and read audio as a spectrogram (${GODOGEN_ASSETS}/sfx/README.md).
Moves that drive gameplay — root-motion locomotion, attacks, state machines, anything held, ridden or aimed, characters that touch each other: read ${ASSET_GEN_SKILL_DIR}/motion.md.
What ships with it
9 files 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.
- 8d ago Changed · -70 lines · +39 tokens per session eaccfe3e0cf9
- 1mo ago Changed · +18 lines · +6 tokens per session 999aa6e21ee7
- 1mo ago First seen · 125 lines · 63 tokens per session scan A 741d1dcd49ec
asset-gen is a skill published in the GitHub repository htdt/godogen (7,205 stars, last pushed 8d ago), licensed MIT. It adds 108 tokens to every session and 1,621 once invoked, about $0.0004 per session on Opus 5.5. 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.
Other skills, from other repositories
qa-plan
Generate a QA test plan for a sprint or feature. Reads GDDs and story files, classifies stories by test type (Logic/Integration/Visual/UI), and produces a structured test plan covering automated tests required, manual test cases, smoke test scope, and playtest sign-off requirements. Run before sprint begins or when…
asset-audit
Audits game assets for compliance with naming conventions, file size budgets, format standards, and pipeline requirements. Identifies orphaned assets, missing references, and standard violations.
balance-check
Analyzes game balance data files, formulas, and configuration to identify outliers, broken progressions, degenerate strategies, and economy imbalances. Use after modifying any balance-related data or design. Use when user says 'balance report', 'check game balance', 'run a balance check'.
code-review
Performs an architectural and quality code review on a specified file or set of files. Checks for coding standard compliance, architectural pattern adherence, SOLID principles, testability, and performance concerns.
hybrid-prototype
Fast-lane prototype skill for the hybrid workflow. Builds a playable prototype in 2-3 days with minimal process overhead. Designed for discovery phase.
milestone-review
Generates a comprehensive milestone progress review including feature completeness, quality metrics, risk assessment, and go/no-go recommendation. Use at milestone checkpoints or when evaluating readiness for a milestone deadline.