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Design generative art

Skill kensaurus/cursor-kenji/skills/design-generative-art

Create algorithmic art using p5.js, Canvas API, or SVG with seeded randomness and interactive parameters. Use when user requests generative art, procedural art, flow fields, particle systems, creative coding, noise patterns, mathematical visualizations, or asks for "art from code", "generate visuals", or "interactive animation".From its SKILL.md

Install
npx -y skills add kensaurus/cursor-kenji --skill design-generative-art

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SKILL.md

11.1 KB, ~3.2k tokens by cl100k_base, as published. Nobody here has run it

Algorithmic Art Skill

Create generative, procedural, and mathematical art using code. Transform algorithms into visual experiences.

CRITICAL: Check Existing First

Before creating ANY generative art, verify:

  1. Check for existing creative coding setup:
cat package.json | grep -i "p5\|three\|canvas\|pixi\|paper"
ls -la src/components/art/ src/components/generative/ 2>/dev/null
  1. Check for existing canvas/WebGL usage:
rg "Canvas|useFrame|getContext.*2d|WebGL" --type tsx -l
  1. Check for existing noise/random utilities:
rg "simplex\|perlin\|noise\|seedrandom" --type ts

Why: Don't conflict with existing rendering pipelines or duplicate utility code.

Core Principles

1. Seeded Randomness

Every piece should be reproducible with a seed:

// Deterministic random number generator
function mulberry32(seed: number) {
 return function() {
 let t = seed += 0x6D2B79F5
 t = Math.imul(t ^ t >>> 15, t | 1)
 t ^= t + Math.imul(t ^ t >>> 7, t | 61)
 return ((t ^ t >>> 14) >>> 0) / 4294967296
 }
}

// Usage
const rng = mulberry32(42) // Same seed = same output
const value = rng() // 0-1 deterministic random

2. Parameterized Generation

Make art controllable via parameters:

interface ArtParams {
 seed: number
 density: number // 0-1
 palette: string[]
 scale: number
 speed: number
 complexity: number // 0-1
}

3. Resolution Independence

Design for any canvas size:

// Normalize coordinates to 0-1 range
const nx = x / width
const ny = y / height
// Then scale to canvas
const px = nx * canvas.width
const py = ny * canvas.height

Techniques

Flow Fields

function createFlowField(cols: number, rows: number, seed: number) {
 const rng = mulberry32(seed)
 const field: number[][] = []

 for (let y = 0; y < rows; y++) {
 field[y] = []
 for (let x = 0; x < cols; x++) {
 // Perlin-like noise using layered sine waves
 const angle = Math.sin(x * 0.1) * Math.cos(y * 0.1) * Math.PI * 2
 + rng() * 0.5
 field[y][x] = angle
 }
 }
 return field
}

function drawFlowField(ctx: CanvasRenderingContext2D, field: number[][], params: ArtParams) {
 const cellW = ctx.canvas.width / field[0].length
 const cellH = ctx.canvas.height / field.length

 // Spawn particles and follow flow
 for (let i = 0; i < params.density * 1000; i++) {
 let x = rng() * ctx.canvas.width
 let y = rng() * ctx.canvas.height

 ctx.beginPath()
 ctx.moveTo(x, y)
 ctx.strokeStyle = params.palette[Math.floor(rng() * params.palette.length)]
 ctx.globalAlpha = 0.3

 for (let step = 0; step < 100; step++) {
 const col = Math.floor(x / cellW)
 const row = Math.floor(y / cellH)

 if (col < 0 || col >= field[0].length || row < 0 || row >= field.length) break

 const angle = field[row][col]
 x += Math.cos(angle) * params.scale
 y += Math.sin(angle) * params.scale
 ctx.lineTo(x, y)
 }

 ctx.stroke()
 }
}

Recursive Subdivision

function subdivide(
 ctx: CanvasRenderingContext2D,
 x: number, y: number, w: number, h: number,
 depth: number, maxDepth: number, rng: () => number,
 palette: string[]
) {
 if (depth >= maxDepth || rng() < 0.15) {
 // Draw leaf
 ctx.fillStyle = palette[Math.floor(rng() * palette.length)]
 ctx.globalAlpha = 0.6 + rng() * 0.4
 ctx.fillRect(x + 1, y + 1, w - 2, h - 2)
 return
 }

 // Random split direction and position
 const horizontal = rng() > 0.5
 const split = 0.3 + rng() * 0.4 // 30-70% split

 if (horizontal) {
 const splitY = y + h * split
 subdivide(ctx, x, y, w, splitY - y, depth + 1, maxDepth, rng, palette)
 subdivide(ctx, x, splitY, w, y + h - splitY, depth + 1, maxDepth, rng, palette)
 } else {
 const splitX = x + w * split
 subdivide(ctx, x, y, splitX - x, h, depth + 1, maxDepth, rng, palette)
 subdivide(ctx, splitX, y, x + w - splitX, h, depth + 1, maxDepth, rng, palette)
 }
}

Circle Packing

interface Circle {
 x: number; y: number; r: number; color: string
}

function circlePacking(
 width: number, height: number,
 maxCircles: number, maxRadius: number,
 rng: () => number, palette: string[]
): Circle[] {
 const circles: Circle[] = []
 let attempts = 0
 const maxAttempts = maxCircles * 50

 while (circles.length < maxCircles && attempts < maxAttempts) {
 attempts++
 const candidate = {
 x: rng() * width,
 y: rng() * height,
 r: 2,
 color: palette[Math.floor(rng() * palette.length)]
 }

 // Grow until collision
 let valid = true
 while (valid && candidate.r < maxRadius) {
 candidate.r += 1
 for (const other of circles) {
 const dist = Math.hypot(candidate.x - other.x, candidate.y - other.y)
 if (dist < candidate.r + other.r + 2) {
 candidate.r -= 1
 valid = false
 break
 }
 }
 // Check bounds
 if (candidate.x - candidate.r < 0 || candidate.x + candidate.r > width ||
 candidate.y - candidate.r < 0 || candidate.y + candidate.r > height) {
 candidate.r -= 1
 valid = false
 }
 }

 if (candidate.r > 2) circles.push(candidate)
 }
 return circles
}

L-Systems (Fractal Trees/Plants)

interface LSystem {
 axiom: string
 rules: Record<string, string>
 angle: number
 length: number
 iterations: number
}

const fractalTree: LSystem = {
 axiom: 'F',
 rules: { 'F': 'FF+[+F-F-F]-[-F+F+F]' },
 angle: 25,
 length: 4,
 iterations: 4,
}

function generateLSystem(system: LSystem): string {
 let current = system.axiom
 for (let i = 0; i < system.iterations; i++) {
 current = current.split('').map(c => system.rules[c] || c).join('')
 }
 return current
}

function drawLSystem(ctx: CanvasRenderingContext2D, system: LSystem, startX: number, startY: number) {
 const instructions = generateLSystem(system)
 const stack: { x: number; y: number; angle: number }[] = []
 let x = startX, y = startY, angle = -90 // Start pointing up

 ctx.beginPath()
 ctx.moveTo(x, y)

 for (const char of instructions) {
 switch (char) {
 case 'F':
 const nx = x + Math.cos(angle * Math.PI / 180) * system.length
 const ny = y + Math.sin(angle * Math.PI / 180) * system.length
 ctx.lineTo(nx, ny)
 x = nx; y = ny
 break
 case '+': angle += system.angle; break
 case '-': angle -= system.angle; break
 case '[': stack.push({ x, y, angle }); break
 case ']':
 const state = stack.pop()!
 x = state.x; y = state.y; angle = state.angle
 ctx.moveTo(x, y)
 break
 }
 }
 ctx.stroke()
}

React Component Pattern

'use client'
import { useEffect, useRef, useState, useCallback } from 'react'

interface GenerativeArtProps {
 seed?: number
 width?: number
 height?: number
 palette?: string[]
 className?: string
}

export function GenerativeArt({
 seed = Date.now(),
 width = 800,
 height = 600,
 palette = ['#264653', '#2a9d8f', '#e9c46a', '#f4a261', '#e76f51'],
 className,
}: GenerativeArtProps) {
 const canvasRef = useRef<HTMLCanvasElement>(null)
 const [currentSeed, setCurrentSeed] = useState(seed)

 const render = useCallback(() => {
 const canvas = canvasRef.current
 if (!canvas) return
 const ctx = canvas.getContext('2d')!
 const rng = mulberry32(currentSeed)

 // Clear
 ctx.fillStyle = '#1a1a2e'
 ctx.fillRect(0, 0, width, height)

 // Your generative algorithm here
 drawFlowField(ctx, createFlowField(40, 30, currentSeed), {
 seed: currentSeed,
 density: 0.8,
 palette,
 scale: 2,
 speed: 1,
 complexity: 0.7,
 })
 }, [currentSeed, width, height, palette])

 useEffect(() => { render() }, [render])

 return (
 <div className={className}>
 <canvas
 ref={canvasRef}
 width={width}
 height={height}
 className="rounded-lg"
 style={{ maxWidth: '100%', height: 'auto' }}
 />
 <div className="flex gap-2 mt-4">
 <button
 onClick={() => setCurrentSeed(Date.now())}
 className="px-4 py-2 bg-primary text-primary-foreground rounded-lg"
 >
 Regenerate
 </button>
 <input
 type="number"
 value={currentSeed}
 onChange={(e) => setCurrentSeed(Number(e.target.value))}
 className="px-3 py-2 border rounded-lg w-32"
 aria-label="Seed value"
 />
 </div>
 </div>
 )
}

Color Palettes

// Curated palettes for generative art
const PALETTES = {
 // Warm
 sunset: ['#ff6b6b', '#feca57', '#ff9ff3', '#54a0ff', '#5f27cd'],
 autumn: ['#d35400', '#e67e22', '#f39c12', '#2c3e50', '#ecf0f1'],

 // Cool
 ocean: ['#0c2461', '#1e3799', '#4a69bd', '#6a89cc', '#82ccdd'],
 forest: ['#1b4332', '#2d6a4f', '#40916c', '#52b788', '#74c69d'],

 // Monochrome
 ink: ['#000000', '#1a1a1a', '#333333', '#4d4d4d', '#666666'],
 paper: ['#f5f0e8', '#ede4d4', '#e5d9c0', '#ddc9a3', '#d4ba87'],

 // Vibrant
 neon: ['#ff00ff', '#00ffff', '#ff0066', '#66ff00', '#ffff00'],
 candy: ['#ff6f91', '#ff9671', '#ffc75f', '#f9f871', '#d4fc79'],

 // Japanese-inspired
 wabi: ['#2c1810', '#5c3a2e', '#b5651d', '#daa06d', '#f5deb3'],
 sakura: ['#ffb7c5', '#ff69b4', '#c71585', '#8b008b', '#4a0028'],
}

Animation Loop

function animatedArt(canvas: HTMLCanvasElement, params: ArtParams) {
 const ctx = canvas.getContext('2d')!
 let frame = 0
 let animationId: number

 function loop() {
 frame++
 const t = frame * params.speed * 0.01

 // Semi-transparent overlay for trails
 ctx.fillStyle = 'rgba(0, 0, 0, 0.02)'
 ctx.fillRect(0, 0, canvas.width, canvas.height)

 // Animated elements
 for (let i = 0; i < 50; i++) {
 const x = canvas.width / 2 + Math.cos(t + i * 0.5) * 200
 const y = canvas.height / 2 + Math.sin(t * 0.7 + i * 0.3) * 200
 const r = 2 + Math.sin(t + i) * 1

 ctx.beginPath()
 ctx.arc(x, y, r, 0, Math.PI * 2)
 ctx.fillStyle = params.palette[i % params.palette.length]
 ctx.globalAlpha = 0.8
 ctx.fill()
 }

 animationId = requestAnimationFrame(loop)
 }

 loop()
 return () => cancelAnimationFrame(animationId)
}

Export & Sharing

// Export canvas as PNG
function exportPNG(canvas: HTMLCanvasElement, filename: string) {
 const link = document.createElement('a')
 link.download = `${filename}-${Date.now()}.png`
 link.href = canvas.toDataURL('image/png')
 link.click()
}

// Export as SVG (for vector output)
function exportSVG(svgElement: SVGSVGElement, filename: string) {
 const serializer = new XMLSerializer()
 const svgString = serializer.serializeToString(svgElement)
 const blob = new Blob([svgString], { type: 'image/svg+xml' })
 const link = document.createElement('a')
 link.download = `${filename}-${Date.now()}.svg`
 link.href = URL.createObjectURL(blob)
 link.click()
}

Related Skills

  • enhance-web-web3d — WebGL, Three.js, shaders for 3D generative art
  • design-motion — Animation patterns for interactive pieces
  • design-canvas — Print-quality visual design philosophy
  • data-visualization — Data-driven generative compositions

Validation

After creating algorithmic art:

  1. Reproducibility → Same seed produces identical output
  2. Performance → 60fps for animated pieces
  3. Resolution → Looks good at target export size
  4. Palette → Colors work together harmoniously
  5. Parameters → Controls produce meaningful visual changes
  6. Export → PNG/SVG export works correctly
  7. Accessibility → Animated art respects prefers-reduced-motion

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