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by sweetcornna · Claude Skill · ★ 95
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Mathodology 数模竞赛 Skills 简体中文 · English Mathodology 是一套专为数学建模竞赛设计的数模 Agent Skills，面向 Claude Code、Codex 等兼容 Agent Skills 的 AI 编程工具。它把获奖级数模方法论——问题拆解、模型构建、可复现实验、获奖级论文写作、提交包组装——沉淀为可直接加载的项目 skills、subagents 和 workflow 模板。 覆盖的竞赛类型： MCM/ICM（美赛）：面向 Outstanding/Finalist 级产出 CUMCM（全国大学生数学建模竞赛）：面向国家一等奖级产出 华数杯、M3、HiMCM/MidMCM、IMMC/IM2C leaderboard/数据科学型、运筹/政策/商业案例型、短时冲刺型竞赛 本仓库是 skills-only 分支：刻意不包含原可运行应用源码，只保留项目级 skills、skill 元数据、轻量文档、备份脚本和许可证。 仓库内容 中的 Claude Code 项目 skills 中的 9 个 Claude Code 项目 subagents（建模、编码、论文、评审、盲评判审等分工角色） 中的 Claude Code 竞赛 workflow 模板 每个 skill 自带 ，方便 Codex 风格工具展示和调用 根目录 ，给不会自动发现 project skills 的工具使用 下的 skills 和 workflow 文档 skill 中的 skills-only 备份脚本 这个分支不保留应用源码、CI workflow、部署文件、生成的 contracts、包锁文件、数据集、构建产物或安装器资源。 一键安装与更新 推荐：在目标项目根目录运行一条命令，把全部内容（8 个 skills + 9 个 Claude Code subagents + 2 个 workflow 模板）只部署到当前文件夹，作为项目级 skill，不影响其他项目： bash npx -y skills@latest add sweetcornna/mathodology --copy --yes --skill '' --agent
| Stars | 95 |
| Forks | 9 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 61.4188142643872/100 |
| Open Issues | 1 |
| Last Updated | 2026-08-01 |
| Created | 2026-04-20 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~15k |
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mathodology is 专为数学建模竞赛设计的数模 Agent Skills：MCM/ICM 美赛、CUMCM 国赛、华数杯、M3、HiMCM 等，面向 Claude Code 与 Codex 的获奖级建模工作流。Math modeling contest skills for Claude Code & Codex.. It is categorized as a Claude Skill with 95 GitHub stars.
mathodology is primarily written in Python. It covers topics such as agent-skills, ai-coding, claude-code.
You can find installation instructions and usage details in the mathodology GitHub repository at github.com/sweetcornna/mathodology. The project has 95 stars and 9 forks, indicating an active community.
mathodology is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to mathodology on Agent Skills Hub include ai-skills, ask-user-questions-mcp, agent-designer. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.