What are GF(3) trits in this context?

Colors are mapped to a ternary system (-1, 0, +1) based on their hue (Warm, Neutral, Cold), allowing developers to link visual styles directly to mathematical logic or state machine values.

Can this skill be used for parallel computing?

Yes. Because the generation is stateless and seed-based, you can split generators for independent parallel processes while guaranteeing the results remain synchronized.

How do I integrate Gay-MCP with Claude Code?

By running the provided MCP server via Julia or Ruby, Claude can access tools like color_at and palette to automate design tasks and verify color-related logic.

What makes this color generation 'deterministic'?

It uses the SplitMix64 algorithm where a specific seed and index always produce the exact same color value, ensuring visual consistency across different machines and environments.

Deterministic Color Generation (Gay-MCP)

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

byplurigrid

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设计工具

Generates mathematically consistent color palettes and threads using deterministic hashing and GF(3) trit mapping.

Gay-MCP is a specialized skill for Claude Code that enables deterministic color generation through the SplitMix64 algorithm and golden angle spirals. By ensuring that the same seed always produces the same sequence of colors, it facilitates parallel computation, reproducible design systems, and mathematical color-to-logic mapping via GF(3) trits. This tool is ideal for developers and designers who need synchronized visual states across multiple instances or out-of-order execution without losing visual consistency, making it a powerful utility for generative art and complex state visualization.

主要功能

01Golden angle spiral algorithms for creating harmonious, non-overlapping color threads.

02Mathematical GF(3) trit mapping (Plus, Ergodic, Minus) for color-logic synchronization.

03MCP-integrated tools for on-demand palette generation and out-of-order math proofs.

04Deterministic SplitMix64-based color generation for complete reproducibility.

052 GitHub stars

06Parallel-safe generator splitting to maintain consistency across distributed systems.

使用场景

01Mapping complex system states to specific color values for intuitive visual debugging and observability.

02Synchronizing UI color schemes across distributed micro-frontends without a shared backend.

03Creating reproducible generative art where visual output is a direct function of a seed.

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