julia-gay

Compute deterministic colors from a seed and index using SplitMix64 RNG.

60|13|Updated Dec 22, 2025
One-click install
npx skills add https://github.com/plurigrid/asi --skill julia-gay
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: julia-gay
Source: https://github.com/plurigrid/asi/tree/main/skills/julia-gay
Command: npx skills add https://github.com/plurigrid/asi --skill julia-gay

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Deterministic color generation using Gay.jl with SplitMix64 RNG and SPI-compliant fingerprints to power repeatable visuals.

Core Features & Use Cases

  • Palette generation and per-index color computation
  • GF(3) trit classification for parallel fingerprinting
  • SPI-compliant data integrity in color-based pipelines

Quick Start

Import Gay and call color_at(seed, index) to get a color, or Gay.palette(seed, n) for a palette.

Frequently Asked Questions about julia-gay

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate deterministic colors from a seed in Julia?

Deterministic color generation uses a seed value with SplitMix64 RNG to produce repeatable colors across Julia workflows. Call color_at(seed, index) to compute a single color or Gay.palette(seed, n) to generate a full palette from any numeric seed.

What is SPI-compliant fingerprinting for color palettes?

SPI-compliant fingerprints use GF(3) trit classification to embed data integrity into color-based pipelines. This approach ensures fingerprints remain consistent across wide-gamut color spaces and parallel processing workflows.

Can I use deterministic color generation for palette indexing across wide-gamut color spaces?

Yes. Gay.jl supports per-index color computation and wide-gamut color space output, enabling consistent palette generation whether you need sRGB, Display P3, or other extended gamuts from a single seed.

Do I need a specific RNG implementation for deterministic color workflows?

SplitMix64 RNG is required for deterministic color generation in this Skill. It ensures reproducible output across different Julia environments and processing runs with identical seed values.

How does trit classification support fingerprint generation?

GF(3) trit classification partitions seed data into ternary states, enabling parallel fingerprint computation that integrates directly into color pipelines while maintaining SPI compliance and data integrity.