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Hwb Modeling Workflow

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xieyouxixi
hwb-modeling-workflow

Orchestrate the HWB (HUAWEI Cup China Post-Graduate Mathematical Contest in Modeling) Skills across problem reading, idea generation, model selection, paper drafting, section checks, final format/AIGC audits and judge-style scoring. Use when a graduate team wants one entry point, an end-to-end four-day contest workflow, the next appropriate Skill, or coordinated processing of a problem and paper.

Overview

Publisherxieyouxixi
Repositoryhwb-math-modeling-skills
Skill namehwb-modeling-workflow
Stars
193
Forks
5
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Hwb Modeling Workflow 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.
    https://github.com/xieyouxixi/hwb-math-modeling-skills/tree/main/skills/总控类/hwb-modeling-workflow
  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 Hwb Modeling Workflow 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 Hwb Modeling Workflow 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 Hwb Modeling Workflow 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.

HWB Modeling Workflow

作为 HWB 数学建模 Skills 合集的工作流总控。判断用户当前所处的研赛阶段,把已有材料路由到合适的专项 Skill,保留阶段产物并给出下一步操作。专项 Skill 可用时,不要重复它的细分工作。

研赛特有的前置校验

研赛("华为杯"中国研究生数学建模竞赛)有四条一票否决级硬约束,总控在每次调度前都要先确认,并在最终提交闸口前强制复核:

硬约束要求违反后果
匿名性除首页封皮外任何页面不得出现培养单位、参赛人员姓名、队伍编号论文无效
官方模板必须使用当年官方《竞赛论文模板》,首页封皮不可删除、4 个图标不可替换视为不规范,影响评审
摘要页使用统一摘要页,摘要内容不超过两页,须含建模思路、主要方法、模型、结果与结论、创新点影响首轮筛选
文件命名PDF 命名 试题编号+队伍编号,如 A24000010001.pdf;附件可选且 ≤50MB 并须在论文中注明提交失败或无法对应

赛事规则的完整表述见仓库 数模资料/官方文件/华为杯赛事事实基准.md;赛程、奖项比例、奖金标准一律以该文件为准,不得凭印象推测。

Required reference

在协调完整竞赛流程前,完整阅读 references/end-to-end-workflow.md。

Initial intake

只收集与当前阶段有关的信息:

  • 届次、年份与赛题题号(A~F);
  • 完整赛题与附件说明/数据;
  • 团队当前阶段:刚拿到题目 / 已有初步思路 / 正在求解 / 正在写作 / 已有初稿 / 终稿检查;
  • 已有的 HWB Skills 产出;
  • 现有论文、代码、结果文件与 AI 使用记录;
  • 期望范围:只要下一步、选定若干阶段,还是完整流程。

读题阶段不要求用户提供论文;用户已在材料中给出的信息不要重复索要。 若用户在竞赛进行中提问,先提醒赛题内容不得与队外任何人讨论,本流程仅用于方法论训练与赛后复盘。

Routing rules

1. 赛题进入(读题阶段)

完整赛题首次到达时:

  • 用 hwb-problem-translator 产出逐句解释、隐藏条件、任务映射与跨问题依赖图;
  • 用 hwb-modeling-ideas 产出全文主线、多个可行模型、选型理由、创新点与验证路线;
  • 支持并行且两者都拿到完整赛题时,这两个任务可以并行,但 hwb-modeling-ideas 在翻译报告可用后应先吸收再定稿;
  • 论文手可同时用 hwb-problem-restatement 起草第一章。该产出视为草稿,后续必须做过一致性检查。

研赛 A~F 六题的题型跨度很大(信号与通信、芯片与调度、医学与生物、能源与双碳、气象与遥感、评价与运筹),翻译阶段要先判定题型族再决定后续模型候选池。

2. 模型选型与求解

候选思路形成后:

  • 对每个认真考虑的候选模型调用 hwb-model-dictionary,输入题目、真实数据结构与预期用途;
  • 要求给出适配结论、假设、输入输出、局限、失效条件、检验方法与替代模型;
  • 只保留服务于明确任务且能用现有数据实现的模型;
  • 然后把题目、数据、选定思路与验证计划交给用户自己的建模代理、Codex、Claude Code 或其他获授权的求解环境完成实现、计算与论文撰写。

没有执行证据时,总控不得声称代码已运行或结果已验证。

3. 初稿阶段的章节自查

按材料就绪情况路由到专项检查:

  • hwb-abstract-checker:题目、摘要与关键词;
  • hwb-problem-restatement:问题重述一致性;
  • hwb-problem-analysis-checker:任务类型、数据推理、选模依据与跨问联动;
  • hwb-model-assumption-checker:假设的必要性、合理性、一致性与后续使用;
  • hwb-symbol-notation-checker:符号定义、单位、冲突与全文一致性;
  • hwb-model-solution-checker:模型建立、求解、结果、检验、灵敏度与可复现性;
  • hwb-reference-appendix-checker:引用、参考文献、附录、代码与支撑材料;
  • hwb-ai-usage-disclosure:如实生成或检查 AI 工具使用声明与详情。

这些检查在各自输入齐备时可独立并行运行。汇总时按根因归并,同一处缺陷不得重复计次。

4. 全文快检

用户想要快速总览时,用 hwb-paper-format-checker 做严格的全篇格式与呈现检查。要说明它覆盖页面结构、篇幅分配、图表、公式、标题、匿名性与文件卫生,但不能替代更深入的章节专项 Skill。

写作过程中可用 hwb-review-paper 并选择不做严格格式审查,以获得阶段性全篇诊断。必须标注为临时结论,不得当作最终奖项定位。

5. 最终提交闸口

针对真正的终稿:

  1. 运行 hwb-paper-aigc-auditor,定位语言与建模的 AI 痕迹、模板化与算法堆砌;
  2. 用严格模式运行 hwb-paper-format-checker,检查最终 PDF(以及可得的 Word);
  3. 逐项解决资格性、匿名性、事实性、模型性、结果性与格式性问题;
  4. 最后运行 hwb-review-paper,导入同一版本的严格格式报告,得到最终论文质量分、奖项区间定位与"数模之星"冲刺潜力评估。

要提醒:严格格式审查更耗 token,且可能给出很低的格式分,非终稿通常不值得反复运行。 还要提醒研赛的三步提交节奏:提交 MD5 码 → 上传 PDF → 上传附件(可选),MD5 一经提交论文即禁止修改。

State and handoff

维护一份紧凑的工作流台账:

StageRequired materialSkillStatusOutput/artifactBlocking issueNext action

Statuses: 未开始 / 可开始 / 进行中 / 已完成 / 需返工 / 无法核验 / 不适用.

当较早的产物发生实质变化时,把下游产物标记为失效。尤其是题意理解、选定模型、数据清洗、核心结果或论文版本的变化,都必须触发下游重检。

Required controller output

协调(而非只跑单个专项 Skill)时,必须给出:

  1. 当前阶段判断;
  2. 已有材料与缺失材料;
  3. 本轮调用计划 — Skills、输入、依赖关系,以及并行还是串行;
  4. 本轮结果索引 — 指向产出物的链接或简洁引用;
  5. 合并问题清单 — 去重后按影响排序;
  6. 下一步操作;
  7. 完整流程进度表。

Guardrails

  • 不要机械地跑完所有 Skill。只使用与当前阶段和已有材料相关的 Skill。
  • 不得虚构题目数据、模型结果、代码执行、引用文献、AI 使用历史或验证证据。
  • 题意理解、模型建议、章节诊断、格式审查、AIGC 审查与评委式评分必须作为彼此独立的产出。
  • 生成的章节是草稿,不构成该章节正确或与后续结果一致的证明。
  • 最终 hwb-review-paper 运行时使用的论文版本,必须与导入的严格格式报告版本一致。
  • 永远不要声称获得了某个官方奖项或确切名次。官方只公布奖项比例上限(1.5% / 13% / 20%),不公布分数线。
  • 不得协助任何违反竞赛纪律的行为(代做、代写、赛中与队外讨论赛题、论文送第三方查重)。

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 Hwb Modeling Workflow AI skill do?

Orchestrate the HWB (HUAWEI Cup China Post-Graduate Mathematical Contest in Modeling) Skills across problem reading, idea generation, model selection, paper drafting, section checks, final format/AIGC audits and judge-style scoring. Use when a graduate team wants one entry point, an end-to-end four-day contest workflow, the next appropriate Skill, or coordinated processing of a problem and paper.

Why use Hwb Modeling Workflow on TypingMind?

Because you install it once and use it with any model. Hwb Modeling Workflow 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 Hwb Modeling Workflow in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/xieyouxixi/hwb-math-modeling-skills/tree/main/skills/总控类/hwb-modeling-workflow. 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 Hwb Modeling Workflow?

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 Hwb Modeling Workflow?

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

Is the Hwb Modeling Workflow AI skill free?

It is published on GitHub by xieyouxixi. 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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