
math-intuition-builder
by parcadei
Context management for Claude Code. Hooks maintain state via ledgers and handoffs. MCP execution without context pollution. Agent orchestration with isolated context windows.
Use Cases
MCP Server Integration
AI tool integration using Model Context Protocol. Using math-intuition-builder.
API Integration
Easily build API integrations with external services.
Data Synchronization
Automatically sync data between multiple systems.
Webhook Setup
Enable event-driven integrations with webhooks.
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
- What are you trying to find? (restate)
- What happens with small numbers? (specialize)
- What shape should the answer be? (anticipate)
- What does this look like visually? (represent)
- What's the simplest version? (reduce)
- 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
Score
Total Score
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Reviews
Reviews coming soon

