intuitmath

Guides users from intuitive to rigorous mathematical reasoning across domains.

4|Updated Jun 1, 2026
One-click install
npx skills add https://github.com/Chi-Shan0707/IntuitMath.skill --skill intuitmath
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: intuitmath
Source: https://github.com/Chi-Shan0707/IntuitMath.skill/tree/main
Command: npx skills add https://github.com/Chi-Shan0707/IntuitMath.skill --skill intuitmath

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

IntuitMath provides a thinking framework for mathematical problem solving that emphasizes discovering the problem's original motivation, reconstructing the available toolkit, and guiding users from intuitive, pre-rigorous reasoning to rigorous justification, with cross-domain connections and historical context.

Core Features & Use Cases

  • Motivation-first problem solving: reconstructs the question's origin, era, and toolkit to reveal why a solution is needed.
  • Cross-domain explanations and historical motivation: ties math concepts to physics, CS, economics, and biology for deeper understanding.
  • Multi-agent workflow support and polished outputs: enables historians, intuition builders, formalizers, skeptics, connectors, and synthesizers; HTML/KaTeX notes; OCR-friendly inputs; and a reusable problem library.
  • Output artifacts: templates for HTML notes, KaTeX rendering, and problem-collection scaffolding.

Quick Start

Provide a math question and ask for an intuition-first exploration, with optional cross-domain insights, or request a rigorous derivation.

Frequently Asked Questions about intuitmath

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

FAQPage Schema
How do I build mathematical intuition before starting a rigorous proof?

To build mathematical intuition, this Skill reconstructs the historical motivation and original toolkit of a problem, guiding you from pre-rigorous intuition to rigorous mathematical justification.

Can I get cross-domain explanations for linear algebra and calculus concepts?

Yes, you can get cross-domain explanations for linear algebra and calculus. It applies the Bernstein principle to seek cross-domain simplifications, tying math concepts to physics, CS, economics, and biology.

What is the best way to generate KaTeX-rendered HTML notes from a math problem?

The best way to generate KaTeX-rendered HTML notes is to provide a math question and request an intuition-first exploration, which triggers multi-agent workflows to output polished, OCR-friendly HTML notes.

Does this approach work for probability, optimization, and PDE questions?

Yes, this approach works for probability, optimization, and PDE questions. It applies across multiple mathematical domains, supporting cross-domain connections and historical motivation for rigorous derivations.

How do I use a multi-agent workflow for mathematical problem solving?

To use a multi-agent workflow for mathematical problem solving, provide a math question and ask for an intuition-first exploration, which activates historian, intuition builder, formalizer, skeptic, and synthesizer agents.