mo-test-1

Web & Frontend Development
v1.0.0
Benign

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration.

504 downloads504 installsby @moyu0032

Setup & Installation

Install command

clawhub install moyu0032/mo-test-1

If the CLI is not installed:

Install command

npx clawhub@latest install moyu0032/mo-test-1

Or install with OpenClaw CLI:

Install command

openclaw skills install moyu0032/mo-test-1

or paste the repo link into your assistant's chat

Install command

https://github.com/openclaw/skills/tree/main/skills/moyu0032/mo-test-1

What This Skill Does

Generates algorithmic generative art through a two-step process: first drafting a computational philosophy as a .md file, then expressing it as an interactive p5.js sketch in a self-contained HTML file. Each output uses seeded randomness so the same seed always reproduces the same artwork. Parameters are exposed as sidebar sliders for real-time exploration without rewriting code.

Pairing a written algorithmic philosophy with reproducible seeded randomness lets the same conceptual intent be explored across hundreds of variations while keeping each output consistent and recreatable.

When to Use It

  • Generating a seeded particle system visualization to use as a digital print
  • Exploring flow field aesthetics with adjustable noise scale and particle count
  • Creating a shareable browser-based generative art piece with no dependencies
  • Producing a series of algorithmic variations by cycling through seed values
  • Turning a vague aesthetic concept into a runnable p5.js interactive sketch

Example Workflow

Here's how your AI assistant might use this skill in practice.

INPUT

User asks: Generating a seeded particle system visualization to use as a digital print

AGENT
  1. 1Generating a seeded particle system visualization to use as a digital print
  2. 2Exploring flow field aesthetics with adjustable noise scale and particle count
  3. 3Creating a shareable browser-based generative art piece with no dependencies
  4. 4Producing a series of algorithmic variations by cycling through seed values
  5. 5Turning a vague aesthetic concept into a runnable p5.js interactive sketch
OUTPUT
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration.

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Details

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Last updatedFeb 25, 2026