tripartite-decompositions

Decompose problems into GF(3)-balanced MINUS/ERGODIC/PLUS triplets for parallel computation.

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

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

GF(3)-balanced structured decompositions that split problems into MINUS/ERGODIC/PLUS components with sheaf-theoretic gluing. Ideal for FPT algorithms, skill allocation, or any 3-way parallel workload.

Core Features & Use Cases

  • Structured decomposition into three labeled bags with GF(3) conservation.
  • Random walk 3-at-a-time decomposition and entropy-aware seeding.
  • Adhesions/gluing for consistent problem composition.
  • Applications in parallel computation and triplet-based scheduling.

Quick Start

Provide items with trits, run random_walk_3(seed) to produce triplets, and verify GF(3) conservation.

Frequently Asked Questions about tripartite-decompositions

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

FAQPage Schema
How do I decompose parallel workloads into balanced triplets?▼

GF(3)-balanced decomposition splits problems into three labeled components—MINUS, ERGODIC, and PLUS—using random walk seeding and trit labeling (-1, 0, +1). The Skill enforces GF(3) conservation across adhesions, ensuring the sum of trits equals 0 modulo 3 for consistent parallel computation.

What is GF(3) conservation and why does it matter for parallel computation?▼

GF(3) conservation guarantees that decomposed workloads maintain algebraic balance across all three triplet components. This constraint enables fixed-parameter tractable algorithms and ensures triadic workload allocation remains consistent through problem lifting via the D-functor and sheaf-based gluing.

Can I use this Skill for fixed-parameter tractable algorithm design?▼

Yes. The Skill applies directly to FPT algorithms by decomposing problems into GF(3)-balanced triplets with structured adhesions and sheaf-theoretic gluing, supporting both entropy-aware seeding and trit labeling across parallel workloads.

How do I verify GF(3) conservation after decomposing a problem?▼

Assign trits (-1, 0, +1) to each component in your triplet, then confirm the sum equals 0 modulo 3. The Skill's random_walk_3(seed) decomposition automatically enforces this invariant across all adhesions during composition.

What input format do I need to provide for tripartite decomposition?▼

Items must have assigned trits (-1, 0, +1) before running random_walk_3(seed). The Skill accepts entropy-aware seeding and produces three labeled bags (MINUS, ERGODIC, PLUS) with verified GF(3) conservation and sheaf-based gluing for problem lifting.