ljg-rank

Identify minimal independent generators underlying a domain and validate four criteria.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/lightxue/dotfiles --skill ljg-rank
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ljg-rank
Source: https://github.com/lightxue/dotfiles/tree/main/agent/skills/ljg-rank
Command: npx skills add https://github.com/lightxue/dotfiles --skill ljg-rank

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill helps identify the minimal, independent generators that underlie a domain and demonstrates how to reconstruct all observed phenomena from them, enabling clear explanations and efficient communication.

Core Features & Use Cases

  • Identifies the core, independent generators that sustain a domain.
  • Validates the four criteria (generativity, minimality, independence, and predictive power) within an accessible narrative.
  • Applies to diverse fields to simplify complex domains and guide teaching or research.

Quick Start

Provide a concise description of a domain and request the engine to determine its rank using the four criteria.

Frequently Asked Questions about ljg-rank

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

FAQPage Schema
What is domain decomposition to irreducible generators?

Domain decomposition identifies the minimal set of independent generators underlying a field and demonstrates they can reproduce all observed phenomena. It reduces complex systems to their core elements for clearer analysis and explanation.

How do I analyze a domain to find its minimal independent generators?

To analyze a domain, propose a set of generators and explicitly test them against four criteria: generativity, minimality, independence, and predictive power. This validates that the set can reproduce all observed phenomena.

What's the best way to explain complex domains using generator rank analysis?

Generator rank analysis explains complex domains by validating the four criteria within an accessible narrative. This proves the minimal generator set reproduces all phenomena, communicating findings efficiently across diverse fields.

Can I apply domain decomposition to any research or teaching field?

Yes, you can apply domain decomposition across diverse disciplines to simplify complex domains and guide teaching or research. It requires explicit methods for proposing generators and testing their predictive power.

How do I start determining the rank of a domain using the four criteria?

To determine a domain's rank, provide a concise description of the domain and request the engine to evaluate it. The engine will test proposed generators for generativity, minimality, independence, and predictive power.

What are the limitations of using minimal generators for domain analysis?

The approach requires explicit methods for proposing generators and rigorously testing their independence and predictive power. Complex domains may resist reduction if observed phenomena cannot be cleanly reconstructed from a minimal set.