What is GF(3) conservation in this skill?

GF(3) conservation ensures that for every triplet of items interleaved from the three source streams, the sum of their 'trit' values (-1, 0, +1) equals zero (mod 3), maintaining mathematical balance across the schedule.

How does the seed chaining integration work?

It derives the next seed in a sequence by accumulating trits from the generated schedule, allowing for a continuous, reproducible chain of data generation suitable for complex simulations.

Can I use this for non-visual data scheduling?

Yes. Although the default implementation outputs OkLCH color data, the underlying logic is a general-purpose interleaver for any three deterministic streams requiring balanced distribution.

What are the available scheduling policies?

The skill supports 'Round Robin' for simple sequential interleaving and 'GF3 Balanced' which reorders items within a triplet to strictly enforce trit conservation.

Triad Interleave Scheduler

Name: Triad Interleave Scheduler
Author: plurigrid

byplurigrid

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Design Tools

Interleaves three deterministic color streams into balanced schedules using GF(3) conservation for algorithmic consistency.

About

Triad Interleave is a specialized utility for weaving three independent data or color streams—categorized as Minus, Ergodic, and Plus—into a single, balanced execution schedule. By enforcing a GF(3) sum = 0 invariant per triplet, the skill ensures deterministic results and relative order preservation within each stream. It is particularly useful for developers working on generative design systems, topological simulations, or complex UI styling where mathematical harmony and reproducible scheduling are required.

Key Features

Automated OkLCH color space generation with Hex conversion
Seed chaining integration for continuous topological derivational sequences
GF(3) = 0 conservation enforcement for balanced triplet distribution
Support for Round Robin and GF3 Balanced scheduling policies
Deterministic three-stream interleaving based on SplitMix64 seeding
2 GitHub stars

Use Cases

Generating mathematically balanced color palettes for generative art projects
Scheduling parallel execution tasks with deterministic and reproducible output
Implementing topological 'chemputer' logic within AI-driven codebases

About

Key Features

Automated OkLCH color space generation with Hex conversion
Seed chaining integration for continuous topological derivational sequences
GF(3) = 0 conservation enforcement for balanced triplet distribution
Support for Round Robin and GF3 Balanced scheduling policies
Deterministic three-stream interleaving based on SplitMix64 seeding
2 GitHub stars

Use Cases

Generating mathematically balanced color palettes for generative art projects
Scheduling parallel execution tasks with deterministic and reproducible output
Implementing topological 'chemputer' logic within AI-driven codebases