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-precipitation-surfacesgit 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-precipitation-surfaces)<a href="https://agentmods.dev/skills/scottstts/threejs-awesome-graphics-agent-skills/threejs-precipitation-surfaces"><img src="https://agentmods.dev/badge/skills/scottstts/threejs-awesome-graphics-agent-skills/threejs-precipitation-surfaces/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-precipitation-surfaces"><img src="https://agentmods.dev/badge/skills/scottstts/threejs-awesome-graphics-agent-skills/threejs-precipitation-surfaces.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 | $0.00060 | $0.00648 |
| Opus 5 | $0.00030 | $0.00324 |
| Sonnet 5 | $0.00012 | $0.00130 |
| Haiku 4.5 | $0.00006 | $0.00065 |
Grade A, and why
threejs-precipitation-surfaces 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 12d 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Precipitation Surfaces
Treat weather as a coupled event, particle, and surface-response system. Do not add rain or snow particles that are visually disconnected from the ground.
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 order
weather envelope
-> falling precipitation volume
-> world/object surface mask
-> displaced or optical surface response
-> impact residue and splashes
-> shared lighting/post presentation
Read references/precipitation-surface-systems.md for snow accumulation, object capping, wrapped precipitation volumes, wet puddle masks, procedural ripple normals, splash placement, debug outputs, and licensing boundaries.
Read the snow accumulation implementation for camera-wrapped snowfall, shared wind/time uniforms, world-space snow masks, single-source snow height and normals, model snow capping, and optional ice surface composition.
Read the wet puddle rain implementation for rain-progress wetness, asphalt puddle masks, procedural ripple normals, instanced rain streaks, upward-surface splash sampling, and flipbook splashes. This example includes GPL-licensed source material; preserve its license boundary when copying or publishing it.
Required controls
- precipitation density and speed;
- wind direction and strength;
- shared weather progress or coverage;
- wetness, snow, or puddle mask threshold and softness;
- ripple or drift normal strength;
- surface roughness response;
- particle/splash opacity;
- debug modes for masks, normals, particles, and event progress.
Failure conditions
- falling precipitation ignores the wind or timing used by surface response;
- snow height and snow normals come from different fields;
- model snow sticks to vertical faces without an upward-facing filter;
- puddles only lower roughness without a mask, normal response, or ripples;
- splashes appear on downward or hidden faces;
- rain streaks allocate per drop or fail to wrap around the camera;
- temporal wetness is faked with unrelated time noise;
- the license boundary for GPL-derived rain code is removed or obscured.
What ships with it
10 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 408 B
- assets/wet-puddle-rain/GPL-3.0.txt 34 KB
- assets/wet-puddle-rain/road/aerial_asphalt_01_ao_2k.jpg 1885 KB
- assets/wet-puddle-rain/road/aerial_asphalt_01_diff_2k.jpg 2736 KB
- assets/wet-puddle-rain/road/aerial_asphalt_01_nor_gl_2k.jpg 2687 KB
- assets/wet-puddle-rain/road/aerial_asphalt_01_rough_2k.jpg 1360 KB
- assets/wet-puddle-rain/Splash.png 58 KB
- examples/snow-accumulation/snow-system.js 21 KB runs code
- examples/wet-puddle-rain/rain-puddle-system.js 18 KB runs code
- references/precipitation-surface-systems.md 6.3 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.
- 12d ago First seen · 73 lines · 60 tokens per session scan A 57850a92c9ef
threejs-precipitation-surfaces is a skill published in the GitHub repository scottstts/Threejs-Awesome-Graphics-Agent-Skills (800 stars, last pushed yesterday), licensed MIT. It adds 60 tokens to every session and 648 once invoked, about $0.0003 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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