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 scottstts/Threejs-Awesome-Graphics-Agent-Skills --skill threejs-procedural-vegetationgit clone --depth 1 https://github.com/scottstts/Threejs-Awesome-Graphics-Agent-SkillsWrote 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/scottstts/threejs-awesome-graphics-agent-skills/threejs-procedural-vegetation)<a href="https://agentmods.dev/skills/scottstts/threejs-awesome-graphics-agent-skills/threejs-procedural-vegetation"><img src="https://agentmods.dev/badge/skills/scottstts/threejs-awesome-graphics-agent-skills/threejs-procedural-vegetation/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/scottstts/threejs-awesome-graphics-agent-skills/threejs-procedural-vegetation"><img src="https://agentmods.dev/badge/skills/scottstts/threejs-awesome-graphics-agent-skills/threejs-procedural-vegetation.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 | $0.00093 | $0.01077 |
| Opus 5 | $0.00046 | $0.00539 |
| Sonnet 5 | $0.00019 | $0.00215 |
| Haiku 4.5 | $0.00009 | $0.00108 |
Grade A, and why
threejs-procedural-vegetation 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 11d 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Procedural Vegetation
Represent a plant as a growth hierarchy plus rendering adaptations. Do not model it as randomly scattered cylinders.
This skill contains exemplary examples and assets beyond descriptive guidance, they're worth studying, referencing, or even copying. Use them sufficiently when relevant and do NOT blindly skip them.
Build sequence
- Define a per-level species table: length, radius, taper, child count, emergence range, angle, twist, gnarliness, sections, radial segments.
- Grow branches iteratively from a queue so recursion depth and budgets remain inspectable.
- Emit each branch as oriented rings with an intentional UV seam.
- Update section orientation from:
- inherited direction;
- stochastic curvature;
- tropism or external force;
- optional attraction constraints.
- Spawn children with stratified longitudinal slots and independently permuted angular slots.
- Generate leaves only after branch topology is stable.
- Build foliage normals from both card orientation and local crown volume.
- Choose wind scope explicitly. Leaf-root deformation, branch hierarchy deformation, and whole-tree sway are separate systems.
Read references/structured-ash-growth-system.md and preserve its preset, continuation, child-placement, leaf, material, wind, and composition contracts before tuning.
Read the Ash Growth System implementation with its authored preset for a contract-accurate implementation and its diagnostic attributes.
Read the stylized meadow grass implementation for authored blade-cluster geometry with a procedural fallback, image-driven path masking, per-instance origin/facing attributes, circular-arc rooted wind, gust fronts, tip flutter, color clumps, macro variation, translucency, and rim diagnostics.
Read the GPU-computed grass implementation for MRT blade-parameter generation, deterministic terrain-conforming placement, Voronoi clumps, Bezier blade folding, wind-facing yaw, distance LOD/culling, normal/color fading, translucency, and field diagnostics.
What ships with it
26 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.
- agents/openai.yaml 344 B
- assets/gpu-culled-flower-field/flower-petal-variants.png 2448 KB
- assets/gpu-culled-flower-field/painted-grass-atlas.png 2420 KB
- assets/gpu-culled-flower-field/THIRD_PARTY_LICENSES.md 380 B
- assets/structured-ash-growth/ash.png 177 KB
- assets/structured-ash-growth/bark-color.jpg 812 KB
- assets/structured-ash-growth/bark-normal.jpg 1241 KB
- assets/structured-ash-growth/bark-roughness.jpg 388 KB
- assets/structured-ash-growth/THIRD_PARTY_LICENSES.md 1.3 KB
- assets/stylized-meadow-grass/grass-blades-up.glb 4.4 KB
- assets/stylized-meadow-grass/path.webp 13 KB
- assets/stylized-meadow-grass/perlin.webp 22 KB
- examples/gpu-computed-grass/gpu-grass-system.js 36 KB runs code
- examples/gpu-culled-flower-field/gpu-culled-flower-field.js 157 B runs code
- examples/gpu-culled-flower-field/source/gpu-culled-flower-field.ts 74 KB runs code
- examples/procedural-surface-ivy/ivy-effect.js 186 B runs code
- examples/procedural-surface-ivy/source/bvh.ts 1.5 KB runs code
- examples/procedural-surface-ivy/source/flowers.ts 6.1 KB runs code
- examples/procedural-surface-ivy/source/ivy.ts 27 KB runs code
- examples/procedural-surface-ivy/source/leafTexture.ts 5.5 KB runs code
- examples/procedural-surface-ivy/source/wind.ts 1.1 KB runs code
- examples/structured-ash-growth/ash-preset.js 663 B runs code
- examples/structured-ash-growth/tree-system.js 14 KB runs code
- examples/stylized-meadow-grass/grass-system.js 15 KB runs code
- references/gpu-culled-flower-field.md 7.0 KB
- references/structured-ash-growth-system.md 9.0 KB
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.
- 11d ago First seen · 93 lines · 93 tokens per session scan A ba601624c21d
threejs-procedural-vegetation is a skill published in the GitHub repository scottstts/Threejs-Awesome-Graphics-Agent-Skills (800 stars, last pushed today), licensed MIT. It adds 93 tokens to every session and 1,077 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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