1start-mathmodel

jihe520/MathModelAgent · Agent Skill

Initiates a complete workflow for mathematical modeling competitions, determining user preferences and invoking subsequent stages.

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Overview

Publisherjihe520Community
Repositoryjihe520/MathModelAgent ↗
Skill folder1start-mathmodel
Stars4,251
Bundled files1
Licensenot specified — check with the author
Last updatedJune 18, 2026
LinksSkill source ↗ · Repository ↗

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Security
low risk · no obvious risks found — the full report shows the details
Compatibility
instructions only — works with most agents
Similar skills
51 similar skills found
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Installation

A skill is a folder with a SKILL.md file. Pick your agent and run the commands in a terminal (macOS, Linux or Git Bash on Windows) from your project root.

Copy the prompt into Claude, Codex or another assistant: it will review the skill and install it for you.

Install the “1start-mathmodel” skill from mozgi.io (https://mozgi.io/skills/1start-mathmodel/) for me.

1. Download the archive: https://mozgi.io/skills/1start-mathmodel/download
   If it fails, take the skill folder from the source: https://github.com/jihe520/MathModelAgent/tree/main/skills/1start-mathmodel
2. Read SKILL.md and the other files. Check the skill is safe: no hidden commands, no sending data elsewhere, no scripts doing something other than described. If anything looks suspicious, stop and tell me.
3. Put the “1start-mathmodel” folder into your agent's skills folder: .claude/skills/ for Claude Code, .agents/skills/ for Codex, .cursor/skills/ for Cursor, .gemini/skills/ for Gemini CLI. Inside the project if we are in one, otherwise in the home folder (~/.claude/skills/ etc.).
4. Make sure <skills folder>/1start-mathmodel/SKILL.md exists.
5. Briefly tell me what this skill does and offer to try it on my task.

If you cannot do a step yourself, tell me what to click or type.

Review the source files

1 file Download Zip

Read SKILL.md and any companion files before deciding whether to install. Click a file to preview it.

SKILL.md contents

Original author text · read-only

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。

Frequently asked questions

What does the 1start-mathmodel skill do?

Initiates a complete workflow for mathematical modeling competitions, determining user preferences and invoking subsequent stages.

How do I install 1start-mathmodel?

Open the “Installation” block on this page and pick your agent — Claude Code, Codex, Cursor or Gemini CLI — for ready-made commands that copy the skill folder to the right place. Or copy the prompt from the “Via assistant” tab and let the assistant review and install the skill.

Which AI models work with 1start-mathmodel?

Skills are plain Markdown instructions (the Agent Skills format), so 1start-mathmodel works with any agent that reads SKILL.md: Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and more. The model loads the instructions only when a task matches the skill's description.

Is 1start-mathmodel free?

The skill is published openly by jihe520. The skill itself costs nothing — you only pay your AI provider for the tokens you use. No license is specified in the repository — check the terms with the author before commercial use.

Is it safe to install skills?

A skill is a set of instructions your agent will follow, so read SKILL.md and its companion files before installing. Scripts in the skill folder only run if your agent runs them — keep an eye on what it does and do not grant unnecessary permissions.

How is a skill different from an MCP server or a plugin?

An MCP server or plugin gives the model new tools — code that runs and returns a result. A skill gives it knowledge and process: how to approach a task, which steps to follow and what good output looks like. It needs no server or API key.

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