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Fund Background Writer

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HuiyuLi-2000
fund-background-writer

Writes NSFC grant justification research significance section. Invoke when user asks to write 立项依据/研究意义/项目背景 for NSFC or similar grants, or provides a research topic and wants background text.

Overview

PublisherHuiyuLi-2000
RepositoryChinese-Grant-Writer-Skills
Skill namefund-background-writer
Stars
459
Forks
60
Bundled files
13
LicenseMIT
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.

  • 13 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 Background 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-background-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-background-writer .claude/skills/fund-background-writer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Fund Background 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 Background 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 Background 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.

fund-background-writer

基于 16 本成功 NSFC 申请书提炼的写作范式,实现"主题分析 → 政策调研 → 数据调研 → 立项依据撰写"的自动化流程。

技能范围

本技能只负责 NSFC 申请书中立项依据的 1.1 研究意义 部分,包含:

  • 研究背景(含国家战略、现实困境、学术问题、本项目方案)
  • 理论意义
  • 实践意义

触发条件

当用户要求撰写 NSFC 立项依据、研究意义、项目背景,或提供研究主题并要求生成立项依据时,激活本技能。


执行流程

收到用户提供的材料后,严格按以下 7 步执行:

用户至少会提供以下输入:研究内容、研究方法、技术路线、特色与创新、研究目标、关键科学问题。如果输入不足,必须先追问补全再继续。

Step 1:读取知识库

读取以下文件,学习写作范式:

  • assets/templates/writing_style_guide.md —— 风格规范和叙事逻辑
  • assets/templates/structure_template.md —— 段落安排和句子逻辑角色

Step 2:主题分析

  1. 解析研究主题的核心关键词
  2. 识别所属学科领域(管理科学与工程 / 医学 / 经济学 / 信息科学等)
  3. 确定科学问题属性(鼓励探索 / 聚焦前沿 / 需求牵引 / 交叉融通)

Step 3:输入-背景锚定

映射原则:让 agent 知道背景的每一段要"指向"什么,确保逻辑贯通。锚定是逻辑层面的"影子对应",不是文字层面的"复制粘贴"——背景中的困境/不足/方案要用背景自己的语言和论证视角来写,但逻辑上要能追溯到后续输入。

输入→段落映射表:

用户输入对应背景段落写作视角转换
研究内容段落C 的困境条数"现实问题"视角,不用"研究内容"视角
研究方法细节段落D 的不足条数"现有方法的局限"视角,不用"本研究方法"视角
技术路线段落E 的方案展开顺序浓缩为"做什么"不说"怎么做",用"本项目拟……"
特色与创新理论意义的条目创新点说"做了什么",理论意义说"有什么学术价值"
研究目标实践意义的条目研究目标说"要实现什么",实践意义说"对社会/行业有什么价值"
关键科学问题段落F 的科学问题列举进行轻微改写,但不要直接复制,且与后续输入表述接近合理

独立约束:段落A和B(政策背景+数据背景)不受后续输入约束,由联网检索结果决定。

Step 4:联网检索

按以下策略执行联网搜索(由 agent 自行选择可用工具):

政策检索(详见 references/policy_search_strategy.md)
  • 优先来源:国务院、科技部、NSFC、国家统计局、教育部、国家卫健委、工信部、国家发改委及研究主题对应主管部门
  • 目标:找到 2-3 个与主题直接相关的国家/部门级政策文件
  • 记录:政策名称、发布年份、核心要求/表述
数据检索(详见 references/data_search_strategy.md)
  • 优先来源:国家统计局、行业蓝皮书、权威白皮书、国际组织报告、高水平综述
  • 目标:找到 3-5 个支撑问题严重性的统计数据
  • 记录:年份 + 具体数值 + 出处 + 原始链接
  • 禁止使用营销文章、无来源数据、转载数据

Step 5:生成立项依据大纲

按 structure_template.md 的段落结构,生成大纲:

  • 每段标注:写什么、用什么数据/政策、句子逻辑角色
  • 确保问题-方案一一对应
  • 向用户展示大纲,确认后进入撰写

Step 6:撰写完整立项依据

严格遵循 writing_style_guide.md 的风格规范:

  • 按段落 A→B→C→D→E→F → 理论意义 → 实践意义的顺序撰写
  • 每段确保有政策/数据支撑
  • 理论意义用"动词+对象+价值"结构分点阐述
  • 实践意义从宏观到微观层层递进
  • 避免"首次""填补空白"等绝对化表述
  • 方法术语只做背景/验证手段,不撑段落主线

Step 7:自检与输出

  1. 按 references/dod_checklist.md 检查结构完整性
  2. 按 references/boastful_expression_guidelines.md 排查浮夸表达
  3. 按 references/dimension_coverage_design.md 检查四个维度覆盖
  4. 输出最终文本,同时附上:
    • 使用的政策清单(政策名称 + 年份 + 核心表述)
    • 使用的统计数据清单(数据项 + 年份 + 数值 + 出处 + 链接)

参考文件索引

文件用途
assets/templates/writing_style_guide.md写作风格指南(叙事逻辑、段落安排、句子逻辑角色、风格规范)
assets/templates/structure_template.md立项依据结构模板(段落-句子逻辑骨架)
references/info_form.md最小信息表(必填字段缺失时先追问)
references/scientific_question_guidelines.md科学问题写作要点
references/scientific_hypothesis_guidelines.md科学假设写作要点
references/boastful_expression_guidelines.md禁用浮夸表达清单
references/dimension_coverage_design.md维度覆盖检查设计
references/theoretical_innovation_guidelines.md理论创新导向指南
references/dod_checklist.mdDefinition of Done 检查清单
references/methodology_term_examples.md方法学术语误用对比示例
references/policy_search_strategy.md政策检索策略
references/data_search_strategy.md数据检索策略

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 Background Writer AI skill do?

Writes NSFC grant justification research significance section. Invoke when user asks to write 立项依据/研究意义/项目背景 for NSFC or similar grants, or provides a research topic and wants background text.

Why use Fund Background Writer on TypingMind?

Because you install it once and use it with any model. Fund Background 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 Background 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-background-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 Background 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 Background Writer?

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

Is the Fund Background 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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