cumcm-step-review README

The project's README from github.com/yuanchen-home/cumcm-step-review. As one markdown file: README.md.

cumcm-step-review | 数学建模国赛 · 逐步审核版

cumcm-step-review logo

面向全国大学生数学建模竞赛(CUMCM)的完整建模论文分步审核工作流技能,兼容 Codex、Claude Code 等支持 Agent Skills 规范的 Agent。

本仓库本身就是技能:SKILL.md 位于仓库根目录,克隆或复制整个文件夹到 Agent 的 skills 目录即可使用,无需额外安装步骤。

主要特性

目录结构

SKILL.md                   技能入口(Agent 据此识别)
references/                国赛写法指南、语料分析、阶段流程、绘图参考、摘要写作方法论、AI使用报告
scripts/                   绘图风格、图表审计、论文门禁、复现清单等脚本
tools/                     drawio / docx / latex / pdf / xlsx / paper_search 工具链
assets/                    算法说明库、期刊配色、论文模板
agents/                    Subagent 调度配置
manifest.sha256.json       文件清单与版本(v1.8)

安装

Windows

git clone https://github.com/<你的用户名>/cumcm-step-review.git "$env:USERPROFILE\.codex\skills\cumcm-step-review"

或直接把整个文件夹复制到 C:\Users\<你的用户名>\.codex\skills\ 下。

macOS / Linux

git clone https://github.com/<你的用户名>/cumcm-step-review.git ~/.codex/skills/cumcm-step-review

安装后重启 Agent 即可在技能列表看到 cumcm-step-review。

使用

对 Agent 说"用 cumcm-step-review 做这道国赛题",或直接给出赛题与附件,按提示逐部分推进。论文结构与格式以目标赛题当届官方规则和官方模板为准。

许可证与致谢

学习与来源声明

本技能在开发过程中学习并融合了以下既有技能与公开资料,谨此声明并致谢;完整明细与落位见 CREDITS.md。

来源 融入内容 说明
math-modeling 基础建模流程、建模手/编程手/论文手分工、工具链与算法库骨架 作者自建技能
math-modeling-review 分步审核工作流与“分析→审核→代码→写稿→再审→冻结”协议 作者自建技能
math-contest-assistant 论文各部分的组织与写作经验 作者自建技能
math-modeling-paper-review 论文审阅与写法经验 作者自建技能
cumcm-abstract-writing-skill 摘要写作方法论与摘要语料分析(references/摘要写作/) 开源技能(GitHub: jjh666888/cumcm-abstract-writing-skill)
drawio-skill v2.1.0 tools/drawio/ 非数据图工具链 MIT,Agents365-ai
scipilot-figure-skill references/绘图参考/ 科研绘图知识库 MIT,Haojae
mathmodel-figure-templates assets/figure-templates/ 科研绘图模板 内置自包含
历届国赛优秀论文(公开资料) 93 篇优秀摘要语料、写作指南、语料分析报告 公开资料,仅供学习研究

cumcm-step-review (yuanchen-home/cumcm-step-review)

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What is this?This is an Agent Skill that provides a complete step-by-step review workflow for writing a CUMCM (China Undergraduate Mathematical Contest in Modeling) paper, compatible with Codex, Claude Code and other agents that support the Agent Skills spec.
Is this a standalone app or just a skill file?It literally is the skill: the repository root contains SKILL.md, and you just clone or copy the whole folder into your agent's skills directory - there is no separate build or install step.
How do I get it running with my agent?On Windows, copy the whole folder into the agent's skills directory (e.g. C:\Users\ \.codex\skills\); on macOS/Linux copy it to the equivalent skills path and restart the agent so it shows up in the skill list. Then just tell the agent to use 'cumcm-step-review' on your contest problem, or paste the problem and attachments directly.
Which coding agents actually support this skill?Any agent implementing the Agent Skills specification can load it; the README explicitly confirms Codex and Claude Code as compatible hosts.
Does it enforce a fixed official paper template?No - the actual paper structure and formatting still follow whatever the current year's official contest rules and template say. The skill only drives the review process and must have core modeling and problem analysis led and manually checked by the actual contest team for compliance.
What does the step-by-step review actually cover?It walks through every section of a modeling paper in order - problem restatement, data preprocessing, per-question modeling and solving, model analysis and testing, evaluation and extension, references, appendix, assumptions, notation, a two-phase abstract, and a final AI usage report - requiring user approval at each step before moving on.
How does it keep the figures publication-quality?It enforces hard chart rules: no in-figure titles, captions below the figure, analysis text right after each one, max 3 figures of the same type, print-ready font sizes, a single 300 DPI PNG output, and 7 journal color palettes like Nature, Science, Cell and IEEE.
How are flowcharts and technical diagrams generated?For non-data diagrams such as technical roadmaps and model structure charts, it bundles drawio-skill v2.1.0, which auto-generates them and exports to PDF/PNG.
What happens during final acceptance checks?Before the paper is considered done it runs a text gate, real document compilation, page-spec checks, figure/table numbering checks, bidirectional citation verification, and a five-way consistency check between the AI usage log, the AI declaration and the AI usage report.
Size
3.7 MB
Stars
317
Updated
CommitSep 04
Age
2mo
Commits · 90 Days