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 kyh/vibedgames --skill regenerate-3dgit clone --depth 1 https://github.com/kyh/vibedgamesWrote 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/kyh/vibedgames/regenerate-3d)<a href="https://agentmods.dev/skills/kyh/vibedgames/regenerate-3d"><img src="https://agentmods.dev/badge/skills/kyh/vibedgames/regenerate-3d/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/kyh/vibedgames/regenerate-3d"><img src="https://agentmods.dev/badge/skills/kyh/vibedgames/regenerate-3d.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 | $0.00092 | $0.02002 |
| Opus 5 | $0.00046 | $0.01001 |
| Sonnet 5 | $0.00018 | $0.00400 |
| Haiku 4.5 | $0.00009 | $0.00200 |
Grade A, and why
regenerate-3d 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 10d 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
regenerate-3d Skill
Runtime: Asset generation steps use the
vg generateCLI (FLUX.2 / GPT-Image-2 / Meshy v6 / Seedance / etc.); the final deliverable is a static HTML page with Three.js and the generated assets bundled in. Install withnpm install -g vibedgames(orpnpm dogfoodin this repo). The generation credentials live on the vibedgames server, so there is no per-machine setup. See thegenerateskill for the command reference.
End-to-end recipe to ship a polished, multi-character 3D web experience using generative models. This is the recipe that powers a cyberpunk character selector with 10 unique operatives, each with a matching companion creature, environment-themed floor texture, animated background and color palette.
What it builds
For each character you get:
- A stylized 3D character GLB (rigged + animated, baked into the file)
- A companion creature GLB (small static, themed to match the character)
- A per-character PBR floor (basecolor / normal / roughness / metalness, all generated)
- A looped video background keyed to the biome
- A 3-color palette that drives the whole UI (CSS custom properties)
- A portrait crop for the roster card
All packaged into a single static HTML page with a Three.js scene. ~25–35 MB of GLBs total after compression.
Pipeline
1. GPT-Image-2 → 1024x1536 character full-body T-pose (per character)
2. Meshy v6 → image-to-3d, enable_rigging=true, animation_action_id={chosen}
→ animated GLB (idle, dance, alert, etc.)
3. GPT-Image-2/edit → companion creature image, color-locked to character palette
4. Meshy v6 → image-to-3d, enable_rigging=false → static creature GLB
5. PATINA → fal-ai/patina/material/extract on the character image,
returns basecolor + normal + roughness + metalness for the floor
6. Seedance 2.0 → fal-ai/bytedance/seedance-2.0/fast/image-to-video, 8s loop
7. gltf-transform CLI → resize 1024 → webp q80 → draco
(typically 95–96% size reduction, ~400–800 KB final)
8. Three.js scene → MeshStandardMaterial floor with alphaMap circular cutout,
mirrored reflection (refl.y = root.y, scale.y = -1),
breathing animation on companions,
per-character palette via CSS custom properties (--c1/--c2/--c3),
per-character floor texture swap on character click,
transition lines + radial flash on swap
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.
- 10d ago First seen · 135 lines · 92 tokens per session scan A f2fbd687d490
regenerate-3d is a skill published in the GitHub repository kyh/vibedgames (55 stars, last pushed today), licensed MIT. It adds 92 tokens to every session and 2,002 once invoked, about $0.0005 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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