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Skills/jihe520/mathmodelagent/1start-mathmodel
1start-mathmodel logo

1start-mathmodel

jihe520/mathmodelagent
836 installs3K stars
Run it on Hostinger, 20% off →Your friend gets 20% off too, using this linkFree API →|View on GitHub|Create your own skill →

Installation

npx skills add https://github.com/jihe520/mathmodelagent --skill 1start-mathmodel

Summary

数学建模竞赛工作流入口。用于启动完整建模流程:询问用户偏好,生成 plan.md 和 todo.md,并按阶段调用赛题分析、建模、代码与图表、流程图、论文撰写、验证验收等 skills。

SKILL.md

数学建模工作流

本 skill 是数学建模竞赛项目的总控入口。它不替代后续阶段 skill,而是负责启动流程、询问偏好、记录决策、生成计划,并按顺序调用各阶段 skill。

数学建模规范参考

如需领域判断,读取 ../_references/math_modeling_norms.md。该文件只提供数学建模基本规范和防错知识,不改变本 skill 的阶段顺序和产出约定。

必须产出

在当前工作目录中创建或更新以下文件:

  • plan.md:整体流程方案、建模方向、阶段顺序、预期产物和风险控制。
  • todo.md:具体待办事项列表,记录每个阶段的任务和状态。

工作流

1. 询问用户偏好 AskUserQuestions

在规划前,只询问会实质影响流程的问题。问题要少而关键。

优先询问(按重要性排序):

  1. 排版引擎:Typst 还是 LaTeX?— 决定 5writing 使用哪套模板和编译命令。两套引擎均覆盖全部模板(14 中 + 3 英)。Typst 使用 typst 命令编译;LaTeX 使用 xelatex 命令编译(需跑两遍解决交叉引用)。
  2. 竞赛类型:国赛/华为杯/华中杯/MCM/...— 决定模板选择,见 5writing 的模板族清单。
  3. 论文语言:中文/英文 — MCM/ICM/COMAP 强制英文,其他默认中文。
  4. 子问题数量是否已知:影响章节文件生成数量。若未知,由 2analysis-modeling 阶段根据题面确定。

将用户的选择记录到 plan.md 的"方案"小节中。

2. 制定方案

按以下结构编写 plan.md:

# 方案

要依次调用这些 skill,按照里面要求完成任务。

用户偏好:
- 排版引擎:<Typst / LaTeX>
- 竞赛类型:<国赛 / 华为杯 / MCM / ...>
- 论文语言:<中文 / 英文>
- 子问题数量:<已知 N 个 / 待分析确定>

workflow:
   step      skills
1. 赛题分析与建模设计 - `2analysis-modeling`
2. 编程实现和图表生成 - `3coding-visual`
3. 流程与架构图绘制 - `4drawio`
4. 竞赛论文撰写 - `5writing`
5. 验证和验收 - `6verity`

项目目录结构

各阶段按此骨架创建和填充文件:

.
├── plan.md                      # 1: 本文件
├── todo.md                      # 1: 待办事项
├── reports/                     # 各阶段文档报告
│   ├── ANALYSIS_MODELING_REPORT.md  # 1: 赛题分析-建模报告(2analysis-modeling)
│   ├── RESULTS_REPORT.md            # 2: 结果报告(3coding-visual)
│   ├── DRAWIO_REPORT.md             # 3: 非数据图说明(4drawio)
│   ├── VERIFY_REPORT.md             # 5: 验收报告(6verity)
├── code/                        # 2: 代码(3coding-visual)
│   ├── problem1.py
│   ├── problem2.py
│   ├── problem3.py               # 问题的数量应该更具题目动态调整
│   ├── ... 
│   └── utils.py
├── results/                     # 2: 结果记录(3coding-visual)
├── figures/                     # 2+3: 所有图表(3coding-visual + 4drawio)
│   ├── *.pdf                    #     数据图 + 非数据图 PDF
│   ├── *.drawio                 #     非数据图源文件
├── paper/                       # 4: 论文(5writing)
│   ├── main.typ / main.tex      #     论文主文件(按用户选择的引擎)
│   └── sections/                #     各节文件(.typ 或 .tex)

方案必须明确每个阶段由哪个下游 skill 负责,以及该阶段应产出什么文件。

3. 生成待办

将 todo.md 写成阶段性 checklist,格式如下:

# 待办事项

- [ ] 1. 赛题分析与建模设计 - `2analysis-modeling`
- [ ] 2. 编程实现和图表生成 - `3coding-visual`
- [ ] 3. 流程与架构图绘制 - `4drawio`
- [ ] 4. 竞赛论文撰写 - `5writing`
- [ ] 5. 验证和验收 - `6verity`

每完成一个阶段,都要更新 todo.md 中对应任务的状态。

4. 依次执行阶段

按以下顺序调用下游 skills:

阶段Skill作用主要产物
赛题分析与建模设计2analysis-modeling解析题意、识别变量/约束/数据/评价指标,并建立数学模型、目标函数、约束条件和求解策略。ANALYSIS_MODELING_REPORT.md
编程实现和图表生成3coding-visual实现可复现代码,运行实验,生成结果表和多种多样的图表。code/, results/ , RESULTS_REPORT.md, figures/图表
流程与架构图绘制4drawio在论文确实需要时,绘制方法流程图、架构图和非数据型概念图。figures/.drawio, figures/.pdf, DRAWIO_REPORT.md
竞赛论文撰写5writing基于分析、建模、代码结果和图表撰写最终竞赛论文,并按章节直接插入图表。paper/
验证和验收6verity检查可复现性、一致性、产物完整性、格式规范和提交就绪状态。VERIFY_REPORT.md

阶段边界

  • 3coding-visual 负责生成所有依赖计算结果或实验输出的数据图表。
  • 4drawio 只负责概念图、算法流程图、架构图、路线图等非数据型图示。
  • 不要让 4drawio 重复绘制 3coding-visual 已经生成的统计图或数据图。
  • 5writing 负责决定图表在论文中的位置,并按所选引擎写入图表代码:
  • Typst:#figure(image("../../figures/xxx.pdf", width: 85%), caption: [...])
  • LaTeX:\begin{figure}[H]\centering\includegraphics[width=0.85\textwidth]{../../figures/xxx.pdf}\caption{...}\label{fig:xxx}\end{figure}
  • 不要让 5writing 编造数值结论。论文中的数值必须来自 RESULTS_REPORT.md、结果表或已生成图表的数据。

Score

0–100
65/ 100

Grade

C

Popularity17/30

836 installs — growing adoption. Source repo has 3,352 GitHub stars.

Completeness27/30

Documented: full SKILL.md body, description, one-line install. Missing: category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

1start Mathmodel skill score badge previewScore badge

Markdown

[![1start Mathmodel skill](https://www.claudemarket.ai/skills/jihe520/mathmodelagent/1start-mathmodel/badges/score.svg)](https://www.claudemarket.ai/skills/jihe520/mathmodelagent/1start-mathmodel)

HTML

<a href="https://www.claudemarket.ai/skills/jihe520/mathmodelagent/1start-mathmodel"><img src="https://www.claudemarket.ai/skills/jihe520/mathmodelagent/1start-mathmodel/badges/score.svg" alt="1start Mathmodel skill"/></a>

1start Mathmodel FAQ

How do I install the 1start Mathmodel skill?

Run “npx skills add https://github.com/jihe520/mathmodelagent --skill 1start-mathmodel” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the 1start Mathmodel skill do?

数学建模竞赛工作流入口。用于启动完整建模流程:询问用户偏好,生成 plan.md 和 todo.md,并按阶段调用赛题分析、建模、代码与图表、流程图、论文撰写、验证验收等 skills。 The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the 1start Mathmodel skill free?

Yes. 1start Mathmodel is a free, open-source skill published from jihe520/mathmodelagent. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does 1start Mathmodel work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so 1start Mathmodel works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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