math-reasoning
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.
How do I install this agent skill?
npx skills add https://github.com/lingzhi227/agent-research-skills --skill math-reasoningIs this agent skill safe to install?
- Gen Agent Trust Hubpass
The math-reasoning skill is a safe, template-based tool for formatting mathematical proofs and derivations in LaTeX. It contains no executable scripts, network requests, or sensitive data access.
- Socketpass
No alerts
- Snykpass
Risk: LOW · No issues
- Runlayerpass
3 files scanned · No issues
- ZeroLeakspass
Score: 93/100 · 2 sections analyzed
What does this agent skill do?
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
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/lingzhi227/agent-research-skills/math-reasoning">View math-reasoning on skillZs</a>