Math Reasoning
Handles the formal mathematical work you need for research papers: deriving equations step by step, writing proofs using templates for different techniques (direct, contradiction, induction), formalizing informal problem descriptions into proper mathematical frameworks, and selecting appropriate statistical tests. It also generates LaTeX notation tables and verifies dimensional consistency across your work. The skill enforces good practices like defining all symbols before use and numbering equations you'll reference later. If you're writing a machine learning or statistics paper and need to move from rough ideas to publication-ready math with proper justification for each step, this does that translation work. Pairs naturally with research planning upstream and paper writing downstream.
- skills.sh installs
- 2.2K
- GitHub stars
- 459
- last updated
- Aug 21, 2026
Install
$ npx -y skills add lingzhi227/agent-research-skills --skill math-reasoning --agent claude-codeInstalls into .claude/skills of the current project.
Files
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.
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- Repository
- github.com/lingzhi227/agent-research-skills
- Categories
- AI & Agent Building, Data Science & ML
- First seen
- Jun 3, 2026
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