lingzhi227/claude-research-skills · Archived

math-reasoning

Formal mathematical reasoning for research papers — derive equations, write proofs, formalize problem settings, select statistical tests, and generate LaTeX math notation.

First seen Apr 21, 2026

Installation

$ npx skills add lingzhi227/claude-research-skills --skill math-reasoning

Summary

  • 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.

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 29
Default branch main
Open issues 3
Status Archived

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents claude-code

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,573 B
  • docs SUMMARY.md 317 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1 installs

SKILL.md

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](../research-planning/)
  • Downstream: [algorithm-design](../algorithm-design/), [paper-writing-section](../paper-writing-section/)
  • See also: [symbolic-equation](../symbolic-equation/), [data-analysis](../data-analysis/)