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mshafei721

algorithmic-art

by mshafei721

Multi-agent AI coding platform powered by Vercel Sandbox and AI Gateway - Phase 3: Skills & MCP Integration Complete

0🍴 0📅 Jan 15, 2026

SKILL.md


name: algorithmic-art description: Create algorithmic and generative art using p5.js, canvas APIs, and computational aesthetics. Use when users want to create generative art, procedural graphics, creative coding visualizations, or interactive art pieces with seeded randomness for reproducibility.

Algorithmic Art

Overview

Create museum-quality generative art using computational techniques. This skill focuses on p5.js for browser-based creative coding with emphasis on seeded randomness, interactive parameters, and self-contained HTML artifacts.

Core Capabilities

  1. Generative Aesthetics: Develop unique visual philosophies expressed through code
  2. p5.js Integration: Create interactive sketches with parameter controls
  3. Seeded Randomness: Reproducible outputs for consistent artistic results
  4. Canvas Optimization: Performance-focused rendering for smooth animations

Quick Start

// Basic p5.js generative pattern
function setup() {
  createCanvas(800, 800);
  randomSeed(42); // Reproducible randomness
  noLoop();
}

function draw() {
  background(20);
  for (let i = 0; i < 100; i++) {
    let x = random(width);
    let y = random(height);
    let size = random(10, 50);
    fill(random(255), random(255), random(255), 150);
    ellipse(x, y, size);
  }
}

Design Principles

  • Seeded Randomness: Always use randomSeed() for reproducible outputs
  • Parameter Controls: Expose key variables for interactive exploration
  • Performance: Use noLoop() for static pieces, optimize for animations
  • Self-Contained: Bundle as single HTML artifacts for easy sharing

Workflow

  1. Define aesthetic concept and visual philosophy
  2. Implement core algorithm with configurable parameters
  3. Add interactivity (mouse, keyboard, sliders)
  4. Optimize performance for target framerate
  5. Bundle as self-contained HTML artifact

Score

Total Score

60/100

Based on repository quality metrics

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0/15
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0/5
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+5
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0/5

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