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 2233admin/design-pipeline --skill particle-systemgit clone --depth 1 https://github.com/2233admin/design-pipelineWrote 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/2233admin/design-pipeline/particle-system)<a href="https://agentmods.dev/skills/2233admin/design-pipeline/particle-system"><img src="https://agentmods.dev/badge/skills/2233admin/design-pipeline/particle-system/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/2233admin/design-pipeline/particle-system"><img src="https://agentmods.dev/badge/skills/2233admin/design-pipeline/particle-system.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00100 | $0.03246 |
| Opus 5 | $0.00050 | $0.01623 |
| Sonnet 5 | $0.00020 | $0.00649 |
| Haiku 4.5 | $0.00010 | $0.00325 |
Grade A, and why
particle-system scanned grade A with 1 finding 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 7d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
description: This skill should be used when the user asks to "build a particle system", "make confetti/snow/smoke/sparks", "create a connected-dot/constellation network background", "add a flow-field or curl-noise partic This is a copy
100% identical to particle-system — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Particle System
Drive many small elements with simple per-particle rules to get emergent, organic motion. Use 2D canvas for hundreds, GPU Points for thousands.
When to use
- Particle/constellation backgrounds and ambient motion.
- Celebratory bursts: confetti, sparks. Weather: snow, rain. Volumetric: smoke.
- Flow-field / curl-noise swirls and data-driven point clouds.
- Connected-dot networks (lines between nearby particles).
Core loop: integrate per particle
Each particle holds state and is advanced every frame: accumulate forces into acceleration, integrate velocity and position, age it, respawn when dead. Scale by dt for frame-rate independence.
class Particle {
constructor() { this.reset(); }
reset() {
this.x = Math.random() * W; this.y = Math.random() * H;
this.vx = 0; this.vy = 0;
this.life = 1; this.size = 1 + Math.random() * 2;
}
step(dt, forces) {
let ax = 0, ay = 0;
for (const f of forces) { const [fx, fy] = f(this); ax += fx; ay += fy; }
this.vx += ax * dt; this.vy += ay * dt;
this.vx *= 0.99; this.vy *= 0.99; // drag
this.x += this.vx * dt; this.y += this.vy * dt;
this.life -= dt * 0.2;
if (this.life <= 0) this.reset();
}
}
Prefer semi-implicit Euler (update velocity first, then position with the new velocity, as above) — it is stable for the spring/drag forces particles use. Use a fixed or clamped dt (Math.min(dt, 1/30)) so a stalled tab does not explode the simulation.
Forces
A force is a function returning an acceleration [fx, fy]. Compose a list.
const gravity = () => [0, 400]; // constant downward
const drag = (p) => [-p.vx * 0.5, -p.vy * 0.5]; // proportional resistance
function attract(tx, ty, strength) { // pull toward a point (e.g. mouse)
return (p) => {
const dx = tx - p.x, dy = ty - p.y;
const d2 = dx*dx + dy*dy + 100; // +100 softens the singularity
const f = strength / d2;
return [dx * f, dy * f];
};
}
Repulsion is attract with negative strength. Springs toward a home position give "settle back" effects.
What ships with it
2 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.
- 7d ago First seen · 230 lines · 100 tokens per session scan A 0cb2c5559bef
particle-system is a skill published in the GitHub repository 2233admin/design-pipeline (9 stars, last pushed 8d ago), licensed MIT. It adds 100 tokens to every session and 3,246 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to particle-system, differing in 0 lines, and is treated as a copy.
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