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Skill Detail

Run gated math modeling contest workflows with MathModeling Skills

Use MathModeling Skills when Claude Code or Codex should guide a math modeling contest project through staged parsing, method selection, code generation, review, frozen-number tracking, paper drafting, and submission packaging.

Templates & WorkflowsMulti-Framework
Templates & Workflows Multi-Framework Security Reviewed
⭐ 1.1k GitHub stars
COPY SKILL INSTRUCTIONS (OPTIONAL)
npx skills add agentskillexchange/skills --skill run-gated-math-modeling-contest-workflows-with-mathmodeling-skills Copy
Uses the third-party skills CLI, not an ASE-owned installer. Check your agent’s compatibility. This copies instructions; complete the upstream tool setup below separately.
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At a glance
Tools required
Claude Code or Codex/ChatGPT plugin support, git, Python/MATLAB or compatible contest tooling as needed by the selected modeling path
Install & setup
Clone the repository, run ./install.sh, and start a new Claude Code or Codex session. Use ./install.sh --target claude, ./install.sh --target codex, or ./install.sh --dry-run for a narrower or previewed install.
Author
zhnnky329
Publisher
Open Source
Last updated
Sep 25, 2026
Quick brief

MathModeling Skills is an installable Claude Code and Codex skill/plugin set for human-in-the-loop mathematical modeling contests. Use it when an operator wants an agent to enforce a staged modeling workflow: parse and classify the problem, analyze related methods, build and review Python or MATLAB code, freeze reported numbers, audit paper consistency, and package a submission from reproducible artifacts. Invoke this instead of using a general chat session when contest work needs explicit gates, stale-result detection, decision logs, and final auditors while the human keeps ownership of modeling judgment. The scope boundary is the gated contest-assistant workflow and its packaged skills, not a generic mathematics library, course, or autopilot submission service.

How it works

What this skill actually does

Inputs and prerequisites: Claude Code or Codex/ChatGPT plugin support, git, Python/MATLAB or compatible contest tooling as needed by the selected modeling path.

Setup notes: Clone the repository, run ./install.sh , and start a new Claude Code or Codex session. Use ./install.sh –target claude , ./install.sh –target codex , or ./install.sh –dry-run for a narrower or previewed install.

Source and verification boundary: use https://github.com/zhnnky329/MathModeling-skills as the canonical reference before running the workflow; keep commands, API calls, CLI usage, and generated outputs reviewable against that upstream source.

Framework fit: publish this as a Multi-Framework workflow only when the operator can invoke the documented toolchain directly, rather than treating the upstream project as a generic product listing.