What problem it solves

AI agents currently lack rigorous mathematical reasoning capabilities — they may guess, skip steps, or produce unverified answers, especially for multi-step or advanced problems. Math.skill gives agents a disciplined workflow: every problem is classified, parsed with full domain awareness, solved step-by-step with theorem citations, and verified through multiple independent methods before output.

Real-world use case

This workflow is used daily by students, educators, researchers, and engineers who need reliable mathematical reasoning from AI agents — solving equations, checking proofs, performing calculus operations, working with linear algebra, or generating verified practice problems.

What this PR adds

• math-skill/SKILL.md — A concise skill file following the repo template (frontmatter, when to use, what it does, how to use, example, tips, use cases)
• README.md update — Entry added to Development & Code Tools section in alphabetical order

Installation

npx skills add Wholiver/Math.Skill

The full skill repository (11,000+ lines) includes 9 supporting modules covering classification, verification, error prevention, and domain-specific protocols across 30+ mathematical domains.

Inspired by: Structured mathematical reasoning workflows used in competition mathematics and academic tutoring