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Fund Technical Route Writer

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HuiyuLi-2000
fund-technical-route-writer

NSFC申请书研究方法、技术路线与创新特色写作助手。在用户已有研究构想基础上，对研究方法、技术路线和创新特色进行学术化表达、逻辑优化与规范化呈现。当用户需要撰写NSFC申请书的研究方法、技术路线、创新和特色时触发。

Overview

PublisherHuiyuLi-2000
RepositoryChinese-Grant-Writer-Skills
Skill namefund-technical-route-writer
Stars
459
Forks
60
Bundled files
12
LicenseMIT
Links
Skill sourceRepository
  • 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.

  • 12 bundled files

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

  • Open source

    Published by HuiyuLi-2000 on GitHub. Read the source before you install it.

Installation

Install the Fund Technical Route Writer 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/HuiyuLi-2000/Chinese-Grant-Writer-Skills/tree/main/skills/fund-technical-route-writer
  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.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/HuiyuLi-2000/Chinese-Grant-Writer-Skills.git /tmp/Chinese-Grant-Writer-Skills
mkdir -p .claude/skills
cp -r /tmp/Chinese-Grant-Writer-Skills/skills/fund-technical-route-writer .claude/skills/fund-technical-route-writer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Fund Technical Route Writer 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 Fund Technical Route Writer 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 Fund Technical Route Writer 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.

NSFC「研究方法—技术路线—创新和特色」写作技能

核心定位

本技能不是创造新的研究方案，而是在用户已有研究构想基础上，对研究方法、技术路线和创新特色进行学术化表达、逻辑优化与规范化呈现。

技能范围

本技能只负责 NSFC 申请书中的研究方法、技术路线与创新特色部分。

核心原则

  1. 不创造研究方案：在用户已有研究构想基础上进行学术化表达
  2. 逻辑优先：优先保证研究逻辑的严谨性，而非追求复杂表述或华丽措辞
  3. 闭环设计：研究内容→关键科学问题→研究方法→技术路线→创新特色必须形成完整闭环
  4. 用户优先：优先保留用户提供的材料、方法和框架
  5. 禁止迁移：不将历史本子的具体研究内容、研究对象、数据来源和结论迁移到新项目

知识库引用

本技能依赖以下知识库文件，写作时必须严格遵循：

研究方法

  • knowledge_base/methodology_style_guide.md：研究方法写作风格指南
  • knowledge_base/methodology_patterns.md：研究方法组织逻辑范式

技术路线

  • knowledge_base/technical_route_style_guide.md：技术路线写作风格指南
  • knowledge_base/technical_route_patterns.md：技术路线组织逻辑范式

创新特色

  • knowledge_base/innovation_style_guide.md：创新和特色写作风格指南
  • knowledge_base/innovation_patterns.md：创新和特色凝练逻辑范式

参考文件

  • references/info_form.md：用户输入信息表
  • references/output_skeletons.md：输出骨架模板
  • references/validation_menu.md：验证菜单
  • references/anti_patterns.md：反模式清单
  • references/terminology_sheet.md：术语表

工作流程

Step 1：阅读用户输入

阅读用户提供的研究目标、研究内容、关键科学问题及所有附加材料。

必填：研究目标、研究内容、关键科学问题 选填：指定研究方法、已有草稿、参考代码、算法框架、方法设计文档、流程图草稿等

Step 2：分析研究逻辑

分析研究目标→研究内容→关键科学问题的逻辑链，识别：

  • 研究内容之间的逻辑关系（递进/并列/支撑）
  • 项目类型（数据驱动/优化决策/方法研究/实证研究/机制研究）
  • 需要哪些类型的方法

Step 3：设计或优化研究方法

根据 methodology_style_guide.md 和 methodology_patterns.md：

情况1：用户仅提供研究目标、研究内容和关键科学问题 → 自行设计研究方法，按方法选择决策树和项目类型选择方法组合

情况2：用户已提供研究方法 → 优先理解和继承用户的方法设计，检查方法与研究内容的映射是否完整

情况3：用户已提供部分研究方法和部分技术路线 → 重点优化其逻辑衔接，优先保留用户已有设计

输出：研究方法部分（含方法列举、用途说明、与研究内容的映射）

Step 4：构建技术路线

根据 technical_route_style_guide.md 和 technical_route_patterns.md：

  1. 确定展开层级（默认细粒度）：
    • 细粒度（默认）：按子研究→孙研究展开，与研究内容三级结构对齐
    • 粗粒度：仅在用户显式指定时使用
  2. 设计总体技术路线（1段总体研究思路 + 1张总体路线图）
  3. 设计分内容技术路线：
    • 细粒度：每个子研究写帽段+路线图+孙研究独立段落（6步语义顺序）
    • 粗粒度：每个子研究写1段合并方案+1张图
  4. 确保方法嵌入路线、形成闭环

输出：技术路线文字描述 + 技术路线图设计方案

Step 5：设计技术路线图

提供技术路线图的 Mermaid 代码或设计建议：

  • 总体路线图：体现全局逻辑
  • 分内容路线图：体现具体操作
  • 标注研究方法
  • 体现闭环设计

Step 6：提炼创新和特色

根据 innovation_style_guide.md 和 innovation_patterns.md：

  1. 从研究内容中识别突破点
  2. 从关键科学问题中识别创新对应
  3. 从研究方法中识别方法创新
  4. 按创新类型（方法/视角/理论/应用/框架/集成）组织创新点
  5. 确保创新点与研究内容、关键科学问题呼应

输出：创新和特色部分

Step 7：闭环验证

根据 validation_menu.md 和 anti_patterns.md：

  1. 检查研究内容→研究方法→技术路线→创新特色闭环
  2. 检查方法与内容一致性
  3. 检查技术路线与正文一致性
  4. 检查创新点与内容一致性
  5. 检查反模式
  6. 检查格式规范

适配机制

用户仅提供基本信息

自行设计研究方法与技术路线，按知识库中的范式组织。

用户已提供研究方法

优先理解和继承用户的方法设计。如有遗漏，补充建议而非替换。

用户已提供部分材料

重点优化逻辑衔接，不推翻重建。优先使用用户指定的方法和框架。

输出格式

输出包含以下部分：

  1. 研究方法：按知识库风格撰写的方法部分
  2. 技术路线文字描述：总体思路 + 分内容详细方案
  3. 技术路线图设计方案：Mermaid代码或设计建议
  4. 创新和特色：按知识库风格撰写的创新特色部分

语言约束

  • 输出语言与用户输入语言一致
  • 学术化表达，避免口语化
  • 优先保证逻辑严谨性，而非追求复杂表述
  • 方法名称使用中英文对照（首次出现时）

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 Fund Technical Route Writer AI skill do?

NSFC申请书研究方法、技术路线与创新特色写作助手。在用户已有研究构想基础上，对研究方法、技术路线和创新特色进行学术化表达、逻辑优化与规范化呈现。当用户需要撰写NSFC申请书的研究方法、技术路线、创新和特色时触发。

Why use Fund Technical Route Writer on TypingMind?

Because you install it once and use it with any model. Fund Technical Route Writer 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 Fund Technical Route Writer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/HuiyuLi-2000/Chinese-Grant-Writer-Skills/tree/main/skills/fund-technical-route-writer. 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 Fund Technical Route Writer?

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 Fund Technical Route Writer?

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

Is the Fund Technical Route Writer AI skill free?

Yes. It is published on GitHub by HuiyuLi-2000 under the MIT license. 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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