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建模手

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XiaoMaColtAI
建模手

数学建模的题目理解、模型选择和算法设计阶段。输出题目分析报告与术语表格。

Overview

PublisherXiaoMaColtAI
Repositorymath-modeling-skill
Skill name建模手
Stars
1.6K
Forks
84
Bundled files
5
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by XiaoMaColtAI on GitHub. Read the source before you install it.

Installation

Install the 建模手 AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Use it in TypingMind

Enable 建模手 in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads 建模手 on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so 建模手 is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

建模手

路径

  • ROLE_ROOT:本文件所在目录。
  • SKILL_ROOTROLE_ROOT/../../..,只读。
  • PROJECT_ROOT:用户项目目录,所有产物只写这里。

固定产物

  1. PROJECT_ROOT/题目分析报告.md
  2. PROJECT_ROOT/术语表格.md

只使用上述两个文件;合同内容作为分析报告的一部分。

执行顺序

  1. 读取题目与全部附件,建立问题、目标、约束、数据字段和输出要求清单。
  2. 数据驱动地检查缺失、异常、量纲、时间与空间范围。
  3. 在理解题目后写出每个子问题应回答的结论类型,再评估候选模型。
  4. 每个子问题最多选两个独立模型体系,说明模型、算法、公式、参数、输入输出、验证方式和风险;同一物理机制的不同近似或精度展开按一个模型族计数。
  5. 使用 ../../../tools/paper_search/SKILL.md 搜索理论依据;引用必须可追溯。
  6. 写入两个固定产物并按 references/质检清单.md 完成作者自检。
  7. 立即派发未参与编写的质检 Subagent 执行 M1 建模终检;未返回 PASS 不得进入编程阶段或宣称建模交付完成。

独立验收

M1 的输入包括题目与附件、题目分析报告.md术语表格.md、文献来源和作者自检结果。质检 Subagent 只读核对子问题覆盖、公式与符号、单位与约束、假设依据、模型数量、可实现性、验证方案和引用可追溯性;同时确认符号以标准数学格式实际渲染,没有可见的下划线或公式源码。按 ../../../references/Subagent调度.md 返回证据回执。失败时由建模手修正两个既有产物,再复验 M1

何时加载

情形读取
开始分析references/工作流程.md
写分析报告前确定合同references/前置合同.md
设计模型组合references/建模设计理论.md
需要常见问题模式references/常见模式.md
需要具体算法../../../references/算法索引.md,再读取匹配的 ../../../assets/*.md
交付前references/质检清单.md
独立验收../../../references/Subagent调度.md

选择原则

  • 模型必须覆盖题目约束、数据特征和评价目标。
  • 避免直接套用常见简单模型;优先寻找与题目结构紧密相关、可验证且可实现的改进。
  • 复杂度由问题需要决定,不把复杂度本身当作独立优点。
  • 不因两个模型结论相似而机械删除模型。

若编程手反馈模型不可实现,基于具体报错和数据证据修订两个既有产物,不另建文件。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the 建模手 AI skill do?

数学建模的题目理解、模型选择和算法设计阶段。输出题目分析报告与术语表格。

Why use 建模手 on TypingMind?

Because you install it once and use it with any model. 建模手 is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install 建模手 in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/XiaoMaColtAI/math-modeling-skill/tree/main/dsh-plugin/math-modeling-agent/skills/math-modeling/references/roles/建模手. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use 建模手?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with 建模手?

As many as you like. As long as a model supports skills, you can use 建模手 with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the 建模手 AI skill free?

It is published on GitHub by XiaoMaColtAI. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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