Can I use this across different programming languages?

Yes, Gay-MCP provides standardized implementations for Julia (Gay.jl), Ruby (SplitMixTernary), and Python, allowing for consistent color and trit generation across polyglot microservices.

What is the benefit of using OkLCH for these colors?

OkLCH is a perceptually uniform color space. Unlike RGB, it ensures that the perceived lightness and chroma are predictable, making the generated palettes more accessible and visually balanced for human users.

What makes these color palettes deterministic?

Gay-MCP utilizes the SplitMix64 PRNG algorithm combined with a constant golden angle increment. This mathematical approach ensures that a specific seed will always produce the exact same sequence of colors, regardless of when or where the code is executed.

How does the GF(3) trit mapping work?

The skill maps specific hue ranges to logical values: warm hues (0-60°, 300-360°) map to +1 (Plus), neutral hues (60-180°) map to 0 (Ergodic), and cold hues (180-300°) map to -1 (Minus).

Deterministic Color Systems (Gay-MCP)

Name: Deterministic Color Systems (Gay-MCP)
Author: plurigrid

byplurigrid

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Design Tools

Generates deterministic, reproducible color palettes and GF(3) trits using SplitMix64 and OkLCH for consistent visual branding and data representation.

Gay-MCP is a specialized skill for creating mathematically-grounded, deterministic color systems. By utilizing SplitMix64 and the golden angle, it ensures that the same seed always produces the same sequence of colors across different environments and languages including Julia, Ruby, and Python. This is particularly useful for generating visual fingerprints of data, creating consistent UI themes in parallelized systems, and mapping logical states (trits) to perceptual colors for intuitive debugging and monitoring of complex constraint systems.

Key Features

018 GitHub stars

02Perceptual rendering using OkLCH color space for human-adapted visuals

03GF(3) trit mapping to link colors directly to logical states (-1, 0, +1)

04Cross-language API support for Julia, Ruby, and Python implementations

05Deterministic color generation via SplitMix64 and golden angle algorithms

06Parallelizable generation ensuring identical outputs across forked processes

Use Cases

01Generating consistent visual signatures for binary analysis and data fingerprints

02Creating reproducible UI color schemes in distributed or parallelized frontend applications

03Mapping complex system states to human-perceptible color palettes for intuitive monitoring

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