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mj-rank

Decompose a domain into irreducible generators with ASCII skeleton diagrams.

Updated May 30, 2026
Search Tags:#critical thinking#domain analysis#knowledge work#root generator#explanatory reach#structural decomposition#Deutsch criteria
One-click install
npx skills add https://github.com/RockerMJ031/mj-claude-skills --skill mj-rank
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: mj-rank
Source: https://github.com/RockerMJ031/mj-claude-skills/tree/main/mj-rank
Command: npx skills add https://github.com/RockerMJ031/mj-claude-skills --skill mj-rank

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill solves the common pain point of being unable to identify the fundamental, irreducible drivers that hold an entire domain together, cutting through disconnected surface-level phenomena and pseudo-factors to find the minimal set of core generators that can explain all observed outcomes in the field.

Core Features & Use Cases

  • 7-step deep penetration process: Systematically drills past surface-level "key factors" to uncover root-level generators, avoiding the common failure of stopping at superficial elements.
  • Deutsch dual validation: Enforces David Deutsch's criteria of explanatory reach (ability to predict unseen real-world phenomena) and hard-to-vary (no detail can be changed without breaking predictions) to ensure found generators are true roots, not pseudo-factors.
  • Adaptive output formatting: Generates structured rank reports with ASCII skeleton diagrams tailored to the shape of the identified root rank (e.g., drilling profiles, feedback loops, coordinate systems) for maximum clarity.
  • Use case: For example, when analyzing the "startup" domain, this skill cuts through surface factors like vision, execution, and team to find the 2-3 irreducible generators that explain every observed startup success or failure pattern, and can even predict unseen market outcomes.

Quick Start

Invoke the mj-rank skill with the prompt "降秩：[your target domain, e.g., SaaS, education, personal productivity]" to receive a full decomposition of the domain's core irreducible generators and a structured, validated rank report.

Frequently Asked Questions about mj-rank

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

FAQPage Schema
How do I find the irreducible root generators that explain a knowledge domain?▼

You decompose the domain using a 7-step deep penetration process that systematically drills past superficial key factors to isolate a minimal set of irreducible generators, validating them against Deutsch's dual criteria of explanatory reach and hard-to-vary resistance.

What is structural decomposition for domain analysis?▼

Structural decomposition is a critical thinking process that breaks down a field into its minimal, independent core generators capable of explaining all observed phenomena, cutting through surface-level noise to validate fundamental drivers using hard-to-vary explanatory criteria.

How do I start decomposing a domain using critical thinking?▼

To start decomposing a domain, submit your target field via a prompt like "降秩：[domain]" to trigger a 7-step deep penetration process that drills past superficial factors and outputs a structured rank report with ASCII skeleton diagrams matched to the identified root rank.

Can I use this structural decomposition approach for research and strategy?▼

Yes, this structural decomposition approach applies directly to research, strategy, and education use cases where you must cut through surface-level noise to understand fundamental system drivers and predict unseen outcomes.

What is the difference between root generators and surface-level key factors?▼

Root generators are irreducible, independent drivers that pass Deutsch's hard-to-vary test and predict unseen phenomena, whereas surface-level key factors are superficial elements that fail explanatory reach validation and break down under structural variation.

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