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SKILL verified MIT Self-run

Creative Coding

skill-npbuilds-skill-library-creative-coding · by npbuilds

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Install

$ agentstack add skill-npbuilds-skill-library-creative-coding

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
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17d ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

Creative Coding — The Algorithm Palette

Algorithms are brushes. Noise is paint. The canvas is a computational space where simple rules produce infinite variety. This skill provides the technical vocabulary for building artifacts that generate, simulate, or compute their visual output.

Core Concepts

Noise — The Foundation of Organic Computation

Noise functions produce pseudo-random values that vary smoothly across space and time. They are the primary tool for creating organic, natural-feeling procedural output.

Perlin noise:

  • noise(x) — 1D: smooth random values along a line
  • noise(x, y) — 2D: smooth random values across a surface (terrain, textures)
  • noise(x, y, t) — 3D: animated 2D noise (add time as third dimension)
  • Scale controls frequency: small input range = smooth; large range = detailed
  • Always returns values in a consistent range (0-1 in p5.js, -1 to 1 in raw implementations)

Fractal Brownian Motion (fBm): Layer multiple octaves of noise for natural-looking detail:

value = 0
amplitude = 1
frequency = 1
for each octave:
  value += amplitude * noise(x * frequency, y * frequency)
  amplitude *= 0.5 (persistence)
  frequency *= 2 (lacunarity)

More octaves = more detail. 4-8 octaves is typical.

Domain warping: Feed noise output back as input coordinates for surreal, organic effects:

warpedX = x + noise(x, y) * warpStrength
warpedY = y + noise(x + 5.2, y + 1.3) * warpStrength
finalValue = noise(warpedX, warpedY)

Multiple layers of warping produce increasingly psychedelic results.

Randomness — Controlled vs. Chaotic

Seeded randomness:

  • Use a seed value to make randomness reproducible
  • Same seed = same output every time
  • Different seed = different output, same character
  • Essential for generative art: allows curation of output

Distributions:

  • Uniform — Equal probability everywhere (raw random)
  • Gaussian/normal — Clustered around center (use for natural variation)
  • Power law — Few large values, many small (use for organic size variation)
  • Poisson disk — Random but evenly spaced (use for point placement without clumping)

The Animation Loop

All creative coding artifacts share a core structure:

setup():
  Initialize state (once)
  Create canvas/renderer
  Set initial parameters

draw() / update():
  Update simulation state (physics, rules, time)
  Render current state to canvas
  requestAnimationFrame(draw)

Frame independence: Use deltaTime to make animations frame-rate independent:

position += velocity * deltaTime

Algorithm Families

Read references/algorithm-catalog.md for detailed algorithm specifications and implementation patterns.

Quick reference:

| Algorithm | Complexity | Visual output | Interactivity potential | |-----------|-----------|---------------|----------------------| | Flow field | Low | Streaming organic curves | High — noise parameters | | Particle system | Low-Medium | Explosive, atmospheric, flowing | High — forces, emitters | | Boids/flocking | Medium | Swarming, natural motion | Medium — obstacles, attractors | | L-system | Low | Botanical, fractal, branching | Low — rule parameters | | Reaction-diffusion | Medium-High | Organic patterns (spots, stripes) | Medium — feed/kill rates | | Physarum | Medium | Network structures, organic growth | Medium — agent parameters | | Cellular automata | Low | Geometric, evolving | High — rule editing, painting | | Verlet physics | Medium | Cloth, ropes, soft bodies | High — direct manipulation | | Rigid body physics | Medium-High | Stacking, collision | High — throwing, building | | Ray marching | High | 3D SDF scenes | Low-Medium — camera, parameters |

Rendering Technology Selection

Read references/performance-guide.md for detailed performance optimization.

Decision tree:

Is it 3D?
  YES → Three.js (WebGL). Consider WebGPU for compute-heavy.
  NO ↓

Is it pixel-level computation (shaders, reaction-diffusion)?
  YES → WebGL fragment shaders or Canvas ImageData
  NO ↓

How many moving elements?
   100K   → WebGPU compute

Shader Basics (GLSL)

Shaders run per-pixel on the GPU. Key concepts:

Fragment shader structure:

uniform vec2 u_resolution;  // Canvas size
uniform float u_time;       // Elapsed time
uniform vec2 u_mouse;       // Mouse position

void main() {
  vec2 uv = gl_FragCoord.xy / u_resolution;  // Normalize to 0-1
  // ... compute color for this pixel ...
  gl_FragColor = vec4(r, g, b, 1.0);
}

Key GLSL techniques:

  • SDFs (Signed Distance Fields): Define shapes as distance functions, combine with min/max/smooth operations
  • Ray marching: Step through 3D space using SDFs to render scenes
  • Domain repetition: mod(position, cellSize) repeats shapes infinitely
  • Noise in GLSL: Implement Perlin/simplex noise for procedural textures
  • Smooth blending: smoothstep() and mix() for gradual transitions

When to Consult This Skill

The Master Artificer or Simulation Smith should consult this skill when:

  • Selecting an algorithm for a generative or simulation artifact
  • Choosing between rendering technologies
  • Implementing noise-based effects
  • Designing shader-based visual effects
  • Optimizing computationally intensive artifacts
  • Understanding parameter spaces for algorithmic art

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.