How does the GF(3) mapping work?

Colors are mapped to a trit value (-1, 0, or +1) based on their hue: warm colors are +1 (PLUS), neutral are 0 (ERGODIC), and cold are -1 (MINUS). This allows developers to use color to represent ternary logic.

What is the benefit of the 'Out-of-Order' proof?

The skill includes a proof that color math can be calculated out of sequence (shuffled or reversed) while maintaining consistency, which is vital for distributed systems and asynchronous rendering.

Can I use this for parallel processing?

Yes, the generator supports splitting. You can fork generators into independent child instances that produce the same deterministic results, making it ideal for parallel computation.

What is the SPI guarantee in Gay-MCP?

SPI stands for Same Seed → Same Output. It ensures that color generation is purely a function of the seed and index, allowing for perfect reproducibility across different machines or sessions.

Deterministic Color & Palette Systems

Name: Deterministic Color & Palette Systems
Author: plurigrid

byplurigrid

•

デザインツール

Generates mathematically deterministic colors and palettes using SplitMix64 and golden angle algorithms for reproducible design.

Gay-MCP is a specialized color generation skill that provides a mathematical guarantee of reproducibility across parallel systems. By utilizing SplitMix64 and the golden angle, it ensures that the same seed always produces identical color sequences and GF(3) trit mappings. This skill is ideal for developers building complex UI systems, procedural game environments, or cryptographic visualizations where color consistency across distributed nodes or reloads is critical. It bridges the gap between topological mathematics and practical frontend design, offering tools for creating harmonious, out-of-order verifiable color palettes through Julia and Ruby implementations.

主な機能

01Parallel computation support with independent child generator splitting

02GF(3) trit mapping for mathematical state representation (-1, 0, +1)

03Multi-language support for Julia (Gay.jl) and Ruby (SplitMixTernary) environments

04Deterministic generation (Same seed → Same output) via SPI guarantee

05Golden angle spiral generation for harmonious color distribution

062 GitHub stars

ユースケース

01Generating consistent brand palettes across distributed frontend applications or micro-frontends

02Procedural asset generation in game development requiring seed-based repeatability for textures

03Visualizing mathematical states or topological data through color-coded ternary logic

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add plurigrid/asi gay-mcp

For use in Claude.ai and ChatGPT

Download Skill