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/math-intuition-builder

Develops mathematical understanding through examples, visualization, and analogy

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vibecosystem
532200 skills138 agents7 hooks
Install
$ npx -y skills add vibeeval/vibecosystem --skill math-intuition-builder --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/math-intuition-builder

Context preview

The summary Claude sees to decide when to auto-load this skill.

Develops mathematical understanding through examples, visualization, and analogy

SKILL.md

math-intuition-builder.SKILL.md
name: math-intuition-builder
description: Develops mathematical understanding through examples, visualization, and analogy

Math Intuition Builder

When to Use

Trigger on phrases like:

  • "help me understand"
  • "build intuition for"
  • "what does this mean geometrically"
  • "why does this work"
  • "visualize this concept"
  • "concrete example of"
  • "what's the intuition behind"

Use before computation to establish understanding (Polya's "understand the problem" phase).

Process

Guide through Mason's specializing-generalizing cycle:

1. Restate in own words

**Ask:** "Can you state the problem in your own words?"

  • Forces re-processing
  • Catches misunderstandings early
  • Verifies shared understanding

2. Try concrete examples

**Ask:** "What would a concrete example look like?"

  • Specialize: try N=3, x=2, simple case
  • Ground abstract concepts in specifics
  • Use computation tools to verify examples

3. Anticipate the answer

**Ask:** "What form should the answer take?"

  • Work backwards from expected result
  • Constrain solution space
  • Check dimensional consistency

4. Visualize

**Ask:** "Can you draw a picture or diagram?"

  • Multiple representations matter
  • Algebraic <-> geometric <-> numeric
  • ASCII diagrams for quick sketches

5. Simplify

**Ask:** "What's a simpler version of this problem?"

  • Reduce dimension
  • Remove terms
  • Special cases reveal structure

6. Find analogies

**Ask:** "Does this remind you of anything you've solved before?"

  • Pattern matching across domains
  • Transfer solution strategies

Key Questions to Ask

1. What are you trying to find? (restate) 2. What happens with small numbers? (specialize) 3. What shape should the answer be? (anticipate) 4. What does this look like visually? (represent) 5. What's the simplest version? (reduce) 6. What's similar? (analogize)

Output Format

Understanding Checkpoint:

Restated Problem:
[User's words, verified]

Concrete Instance:
[Specific numerical example]

Visual Interpretation:
[Description or ASCII diagram]

Simplified Version:
[Special case that's easier]

Analogous Problems:
[Similar structures from other domains]

Intuition Summary:
[1-2 sentence "aha" insight]

Ready to Proceed:
- Next step: [specific action]
- Verify by: [sanity check]

Example Interaction

User: I'm trying to understand why eigenvalues matter for stability

Claude: Let's build intuition step by step.

Q1: Restate the problem?
> I have x' = Ax and want to know if solutions grow or shrink.

Q2: Let's try a concrete example.
A = [[0, 1], [-1, 0]]

Computing eigenvalues: +/- i (purely imaginary)

What happens to solutions?
> They neither grow nor shrink?

Exactly. Solutions are circles - oscillation without growth.

Q3: Now try A = [[-1, 0], [0, -1]]
Eigenvalues: -1, -1 (negative real)

What happens?
> Shrinks to zero.

Yes. Negative real parts = decay.

Q4: Visual pattern:

  Im
   |    x unstable
   |
---+------- Re
   |
   |    x stable

Re(lambda) < 0: stable (decay)
Re(lambda) = 0: marginal (oscillate)
Re(lambda) > 0: unstable (blow up)

Q5: Analogies:
- Springs: eigenvalues = decay rates
- Populations: growth/death rates
- Circuits: time constants

Intuition Summary:
Eigenvalues are the system's "DNA" - they encode fundamental rates.
Look at real parts for stability.

Ready to Proceed:
- Next: Analyze your specific A matrix
- Verify: trace(A) < 0 and det(A) > 0 implies stability (2x2 case)

Co-activates

Suggest alongside:

  • **math-model-selector** - if framework unclear
  • **math-mode** - for concrete computations
  • **math-progress-monitor** - during problem solving
  • **Relevant domain skill** - once intuition established
Read more
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