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math-help

Guide mathematical tool selection for symbolic computation, constraint solving, numerical analysis, and formal proofs.

8|1|Updated Jan 4, 2026
Search Tags:#numerical methods#proofs#calculus#z3#math#algebra#sympy
One-click install
npx skills add https://github.com/scooter-lacroix/Maestro --skill math-help
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: math-help
Source: https://github.com/scooter-lacroix/Maestro/tree/main/maestro/skills/math/math-help
Command: npx skills add https://github.com/scooter-lacroix/Maestro --skill math-help

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires sympy, z3-solver, numpy, scipy, mpmath, matplotlib, plotly, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps users select and utilize the appropriate mathematical tool for their specific computational or proof-based task, demystifying complex math operations.

Core Features & Use Cases

  • Tool Selection Guidance: Provides a clear decision tree and reference table to choose between symbolic computation (SymPy), constraint solving (Z3), numerical methods (NumPy, SciPy), formal proofs (Lean 4), and more.
  • Command Examples: Offers practical command-line examples for common operations like solving equations, integration, differentiation, matrix operations, and theorem proving.
  • Use Case: A user needs to solve a system of linear equations. They can consult this Skill to find the correct NumPy or SymPy command and its syntax, enabling them to get the solution quickly.

Quick Start

Use the math-help skill to find out how to solve equations using SymPy.

Frequently Asked Questions about math-help

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

FAQPage Schema
How do I choose between SymPy and NumPy for solving equations?▼

Choose SymPy for symbolic equation solving and exact algebraic results, while NumPy handles numerical methods and matrix operations. This Skill provides a decision tree to help you select the correct library for your specific math operations.

Can I use Z3 for formal theorem proving and constraint solving?▼

Yes, Z3 is used for constraint solving and theorem verification. This Skill guides you in applying Z3 for formal proofs, alongside tools like SymPy for calculus and algebra.

What's the best way to perform numerical optimization using SciPy?▼

The best way to perform numerical optimization is using SciPy. This Skill provides command examples and tool selection guidance to help you apply SciPy for numerical analysis and optimization tasks.

When should I use mpmath instead of SymPy for calculus operations?▼

Use mpmath for high-precision numerical computations and SymPy for symbolic calculus like integration and differentiation. This Skill helps you navigate the math cognitive stack to pick the appropriate tool.

Does this Skill provide examples for matrix operations and symbolic computation?▼

Yes, it offers practical command-line examples for common operations including matrix operations, symbolic computation, equation solving, and theorem proving using libraries like SymPy and NumPy.

How do I verify mathematical theorems using available Python libraries?▼

You can verify theorems using Z3 for constraint solving and formal proofs. This Skill facilitates theorem verification by guiding you to the correct tools and syntax for your proof-based tasks.

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