Math Reasoning

by lingzhi2279e6c085d65e3No license386 starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated 7 months ago

Formal mathematical reasoning for research papers — derive equations, write proofs, formalize problem settings, select statistical tests, and generate LaTeX math notation. Use when the user needs mathematical derivations, theorem proofs, notation tables, or statistical analysis formalization.

AI-generated overview

Performs formal mathematical reasoning for research papers, producing derivations, proofs, notation tables and LaTeX output.

What it does
This skill carries out rigorous mathematical work for research papers: step-by-step equation derivations, formal theorem proofs, formalization of informal problem settings, statistical test selection, notation tables, and correctness verification. It produces publication-quality LaTeX, including boxed final results, numbered and labelled equations, and table environments. It relies on bundled reference material for standard machine-learning notation, statistical test decision trees, and proof templates.
When to use it
Use it when a user needs mathematical derivations, theorem proofs, a formalized problem setting, help choosing statistical tests, a notation table, or a check of mathematical correctness. It is aimed at research-paper contexts where LaTeX output is expected.
Requirements
No scripts; instructions and two bundled reference documents only. It expects LaTeX output conventions and reads its reference files from a local skills path.

Mathematical Reasoning

Perform rigorous mathematical reasoning and produce publication-quality LaTeX output.

Input

  • $0 — Task type: derive, prove, formalize, stats, notation, verify
  • $1 — Context: equation, theorem statement, problem description, or data description

Tasks

derive — Step-by-step equation derivation

Show every intermediate step. Justify each with the rule applied. Box final result with \boxed{}. Number important equations with \label{eq:name}.

prove — Formal theorem proof

Use appropriate technique: direct, contradiction, induction, construction, or cases. See references/proof-templates.md for LaTeX templates.

formalize — Problem setting formalization

Convert informal description into formal mathematical framework with: variable definitions, domain/range specifications, assumptions, objective function.

stats — Statistical test selection

Use the decision tree in references/notation-guide.md to select appropriate tests. Report p-values, effect sizes, confidence intervals.

notation — Generate notation table

Create a \begin{table} with all symbols used in the paper. Use standard ML notation from references/notation-guide.md.

verify — Check mathematical correctness

Verify: dimensional consistency, boundary cases, gradient computations, notation consistency across sections.

References

  • Standard ML notation + statistical tests: ~/.claude/skills/math-reasoning/references/notation-guide.md
  • Proof templates and theorem environments: ~/.claude/skills/math-reasoning/references/proof-templates.md

Rules

  • Define ALL symbols before first use: "Let $\mathcal{X}$ denote..."
  • Use consistent notation throughout the paper
  • Number equations that are referenced later
  • Use \tag{reason} for key derivation steps
  • State assumptions explicitly
  • Cite lemmas and prior results used in proofs

Related Skills

  • Upstream: research-planning
  • Downstream: algorithm-design, paper-writing-section
  • See also: symbolic-equation, data-analysis

Source and attribution

Source:lingzhi227/agent-research-skillsinskills/math-reasoningat commit9e6c085

License: No license

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