math-researcher-teacher

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Advanced, research-oriented mathematics expert system. Provides rigorous symbolic computation, numerical simulation, and proof assistance across four major pillars: Analysis & PDE, Algebra & Geometry, Stochastics, and Discrete Math.

Develata By Develata schedule Updated 4/11/2026

name: math-researcher-teacher description: "Advanced, research-oriented mathematics expert system. Provides rigorous symbolic computation, numerical simulation, and proof assistance across four major pillars: Analysis & PDE, Algebra & Geometry, Stochastics, and Discrete Math."

Math Researcher Teacher

A comprehensive, research-oriented AI assistant for advanced mathematics. It acts as a meta-skill, routing queries to specialized sub-domains for rigorous analysis and simulation.

Target Audience: Undergraduate/Graduate Mathematics Students, Researchers.

🏛️ Domain Architecture (The Four Pillars)

This skill is organized into four major departments. The Agent should determine the user's mathematical field and route to the appropriate subdirectory.

1. Analysis & Differential Equations (domains/analysis-pde/)

  • Calculus & Analysis: Limits, series, integrals, metric spaces.
  • Real & Complex Analysis: Measure theory, residues, conformal mappings.
  • Differential Equations: ODEs (stability, phase portraits), PDEs (heat, wave, laplace).
  • Functional Analysis: Banach/Hilbert spaces, operators.

2. Algebra & Geometry (domains/algebra-geometry/)

  • Linear Algebra: Vector spaces, eigenvalues, matrix decompositions, spectral theory.
  • Abstract Algebra: Groups, rings, fields, Galois theory.
  • Geometry & Topology: Differential geometry, manifolds, curvature, homotopy/homology.
  • Number Theory: Primes, congruences, elliptic curves.

3. Stochastics (domains/stochastics/)

  • Basic Probability: Distributions, expectations, limit theorems.
  • Stochastic Processes: Markov chains, Brownian motion, martingales.
  • Advanced Stochastics: Random matrices, large deviations, random graphs (Erdős-Rényi).

4. Discrete & Combinatorial (domains/discrete/)

  • Combinatorics: Counting, generating functions, partitions.
  • Graph Theory: Connectivity, coloring, flows, spectral graph theory.

🚀 How to Use

Step 1: Identify the Domain Read the user's request and map it to one of the four domains above.

Step 2: Navigate & Load Navigate to the domain's folder and read its SKILL.md for specific instructions on using its specialized agents and Python scripts.

Example Routing:

  • "Simulate the eigenvalue distribution of a Wigner matrix" -> Go to domains/stochastics/ (Advanced Stochastics).
  • "Calculate the curvature of a surface" -> Go to domains/algebra-geometry/ (Geometry).
  • "Solve this Heat Equation numerically" -> Go to domains/analysis-pde/ (Differential Equations).

🛠️ Common Tools

All domains share access to the common/ library for standard operations:

  • symbolic_engine.py (SymPy wrappers)
  • numeric_engine.py (NumPy/SciPy wrappers)
  • plot_engine.py (Visualization tools)
Install via CLI
npx skills add https://github.com/Develata/Deve-Skills --skill math-researcher-teacher
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