connect-what-i-know

Guide learners through an eight-phase reasoning workflow to identify structural connections across domains.

6|Updated Jan 21, 2026
One-click install
npx skills add https://github.com/ricardogomes/learning-skills --skill connect-what-i-know
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: connect-what-i-know
Source: https://github.com/ricardogomes/learning-skills/tree/main/skills/connect-what-i-know
Command: npx skills add https://github.com/ricardogomes/learning-skills --skill connect-what-i-know

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

The Connect What I Know Skill guides learners to discover structural patterns across domains, preventing premature conclusions and enabling transferable thinking through a rigorous eight-phase process.

Core Features & Use Cases

  • Systematic, stage-by-stage exploration from intuition to generalization
  • Rigorous testing framework (Breakdown, Mechanism, Constraint) to determine structural vs. superficial connections
  • Cross-domain applicability (CS and non-CS domains) to build true transfer learning
  • Socratic hint system to keep learners engaged without revealing answers

Quick Start

Start from a pair of related concepts you know well. State what reminds you of what, then follow the eight phases: Pattern recognition, evidence collection, pattern extraction, testing (breakdown/mechanism/constraint), articulation, prediction, generalization, and reflection.

Frequently Asked Questions about connect-what-i-know

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

FAQPage Schema
How do I identify deep structural connections between different knowledge domains?

To identify deep structural connections between domains, you apply a rigorous eight-phase reasoning workflow that guides you from initial pattern recognition through testing to final generalization. This process prevents premature conclusions by systematically validating transferable patterns.

What is the best way to test if a cross-domain analogy is structurally valid or superficial?

Testing cross-domain analogy validity requires a rigorous testing framework applying Breakdown, Mechanism, and Constraint phases. This mechanism determines whether connections are structurally deep or superficial during the pattern extraction workflow.

How do I start discovering universal patterns across CS and non-CS domains?

Start discovering universal patterns by selecting a pair of related concepts you know well and stating your initial intuitive connection. You then follow an eight-phase process including evidence collection, pattern extraction, and articulation to validate the cross-domain transfer learning.

Can I use a Socratic approach to learn transferable thinking without being given direct answers?

Yes, you can learn transferable thinking using a Socratic hint system that keeps you engaged without revealing answers directly. This approach forces you to actively navigate the eight-phase reasoning workflow to discover generalizations yourself.

What are the limitations of using analogy and pattern recognition for transfer learning?

The limitation of using analogy for transfer learning is the risk of premature conclusions from superficial similarities. The Skill mitigates this by enforcing an eight-phase workflow with rigorous Breakdown, Mechanism, and Constraint testing before allowing predictions or generalization.