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Fund Literature Review Writer

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HuiyuLi-2000
fund-literature-review-writer

撰写NSFC申请书的国内外研究现状及发展动态分析+文献评述。Invoke when user asks to write NSFC literature review, 国内外研究现状, 文献综述, 文献评述, or 1.2部分 of NSFC proposal.

Overview

PublisherHuiyuLi-2000
RepositoryChinese-Grant-Writer-Skills
Skill namefund-literature-review-writer
Stars
459
Forks
60
Bundled files
25
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.

  • 25 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 Literature Review 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-literature-review-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-literature-review-writer .claude/skills/fund-literature-review-writer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Fund Literature Review 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 Literature Review 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 Literature Review 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 文献综述与文献评述写作技能

核心定位

本技能不是"写文献",而是将文献转化为"NSFC研究论证结构的一部分"。

在用户已有研究构想基础上,学习NSFC成功项目中的"文献综述—文献评述"组织方式,对文献部分进行学术化重构、逻辑组织优化、批判性归纳、面向NSFC表达体系的规范化输出。

触发条件

当用户需要撰写以下内容时触发:

  • NSFC申请书的"1.2 国内外研究现状及发展动态分析"
  • NSFC申请书的"文献综述"部分
  • NSFC申请书的"文献评述"部分
  • 用户明确要求"写文献综述"、"写文献评述"、"写研究现状"

核心原则

  1. 不预设固定结构:文献综述的结构从16本NSFC成功本子中"学习出来",不是"写死出来"
  2. 不文献摘要堆叠:禁止文献摘要式输出,文献必须融入论证
  3. 不脱离NSFC语境:文献服务NSFC研究论证结构
  4. 强调结构归纳能力:从本子中归纳组织逻辑,不固化模板
  5. 强调批判性评述能力:文献评述是结构性判断,不是总结
  6. 强调文献服务研究问题能力:文献→研究问题/方法/创新的完整论证链

技能范围

本技能只负责 NSFC 申请书中立项依据的 1.2 国内外研究现状及发展动态分析 + 文献评述 部分。需读取用户研究构想以确保文献服务研究论证。

知识库引用

执行本技能前,必须读取以下知识库文件:

knowledge_base/

  1. literature_review_style_guide.md:文献综述写作风格指南

    • 文献综述的整体叙事逻辑
    • 主题划分策略(4种方式)
    • 段落组织规范(论证功能,非固定句式)
    • 文献引用格式
    • 文献间连接词使用规律
    • 表格使用规范
    • 综述→评述的过渡方式
    • 批判性表达规律
    • 字数规范
  2. literature_review_patterns.md:文献综述组织逻辑范式

    • 五种项目类型的典型文献综述组织
    • 方法型/机制型/系统型文献组织差异
    • 文献群的构建逻辑
    • 文献→研究问题/方法/创新映射模式
    • 文献评述的4种批判性判断类型
    • 文献组织的选择决策树
  3. literature_mapping_rules.md:文献→研究问题/方法/创新映射规则

    • 文献→研究问题映射规则
    • 文献→方法合理性映射规则
    • 文献→创新合理性映射规则
    • 与用户研究构想的对齐机制

references/

  1. info_form.md:用户输入信息表
  2. output_skeletons.md:输出骨架(论证功能,非固定模板)
  3. validation_menu.md:验证菜单
  4. anti_patterns.md:反模式清单
  5. literature_search_strategy.md:文献检索策略
  6. fund-search-workflow.md:完整搜索工作流(脚本调用链、降级策略)

search/(内化搜索包)

  • search/scripts/:搜索脚本(search_all.py, citation_finder.py, rank_and_filter.py, format_bibtex.py, dedup.py,另有 tier_utils/exa_search/search_google_scholar 等内部依赖,无需直接调用)
  • search/references/:搜索参考文档(search-strategy.md, api-reference.md, data-schema.md, journal-tiers.md)
  • search/data/:期刊数据(priority_journals.csv, blacklist_journals.csv)
  • search/.env.example:API 密钥模板(需复制为 .env 并填写)
  • search/requirements.txt:Python 依赖(requests, exa-py, scholarly)

工作流程

Step 1: 理解研究目标

  • 读取用户研究构想(研究主题、研究目标)
  • 确定文献综述的总体方向

Step 2: 解析研究内容

  • 读取用户研究内容(通常3-5个)
  • 确定文献综述的主题划分

Step 3: 识别关键科学问题

  • 读取用户关键科学问题(通常1-3个)
  • 确定文献评述的研究空白方向

Step 4: 检索文献

  • 读取 references/fund-search-workflow.md 获取完整搜索流程

4a. 构造主题检索查询:从研究主题/内容/方法/关键科学问题生成英文查询组

4b. 英文文献搜索(四源并行):

bash
# 设置环境变量(从 search/.env.example 复制为 search/.env 并填写)
# 对每个英文查询组执行:
python search/scripts/search_all.py --query "{英文查询}" --email "$OPENALEX_EMAIL" --output runs/cf/query_N.json
# 合并所有查询组:
python search/scripts/citation_finder.py merge runs/cf/query_*.json --output runs/cf/merged.json
# 补算期刊层级:
python search/scripts/citation_finder.py enrich-tiers --input runs/cf/merged.json --priority-csv search/data/priority_journals.csv --blacklist-csv search/data/blacklist_journals.csv --output runs/cf/enriched.json

4c. Zotero MCP / 本地文件搜索(可选):按 fund-search-workflow.md Step 4/5 执行

4d. 全源合并去重排序:

bash
python search/scripts/dedup.py --input runs/all_merged.json --output runs/deduped.json
python search/scripts/rank_and_filter.py --input runs/deduped.json --weights relevance=0.4,journal_tier=0.3,citation_count=0.2,recency=0.1 --output runs/final.json
python search/scripts/format_bibtex.py --input runs/final.json --output runs/nsfc_references.bib

Step 5: 确认文献集合

  • 直接使用 Step 4d 输出的 runs/final.json(已去重、排序、筛选)
  • 如需调整筛选权重或优先级,参见 references/literature_search_strategy.md

Step 6: 自动归纳文献组织方式

  • 根据 literature_review_patterns.md 选择文献组织方式
  • 根据项目类型选择典型组织模式
  • 根据研究内容划分文献主题
  • 根据研究方法确定方法介绍侧重点

Step 7: 生成文献综述

  • 按 literature_review_style_guide.md 和 output_skeletons.md 生成文献综述
  • 主题划分策略(4种方式,根据研究内容选择)
  • 段落组织(论证功能:引入→举例→对比→转折→总结)
  • 文献引用格式(作者-年份制优先)
  • 表格使用(方法研究型默认使用)
  • 嵌入式评述(每个主题段末)

Step 8: 生成文献评述(独立模块)

  • 按 output_skeletons.md 生成文献评述
  • 评述方式(嵌入式/独立式,根据项目类型选择)
  • 批判性判断(方法性/数据适用性/模型解释能力/研究边界)
  • 引出本项目研究方向

Step 9: 校验与用户研究构想一致性

  • 按 validation_menu.md 逐项验证
  • 文献综述与研究内容的一致性检查
  • 文献评述与研究问题的对应检查
  • 文献→方法→创新的闭环检查
  • 引用格式一致性检查
  • 字数检查
  • 文献质量检查
  • 反模式检查(按 anti_patterns.md)

适配机制

用户已有文献

  • 优先使用用户已有文献
  • 补充检索缺失的文献
  • 验证用户文献的质量和相关性

用户无文献

  • 完全依赖自动检索
  • 按 literature_search_strategy.md 执行检索
  • 生成完整的BibTeX引用库

用户部分文献

  • 以用户已有文献为基础
  • 补充检索缺失的文献
  • 确保文献覆盖所有研究内容

输出格式

输出1:文献综述主体 + 文献评述(MD文件)

markdown
# 1.2 国内外研究现状及发展动态分析

## 1.2.1 主题1(对应研究内容1)
[引入段]
[子主题1.1 文献群]
[子主题1.2 文献群]
[主题评述段(嵌入式评述)]

## 1.2.2 主题2(对应研究内容2)
[引入段]
[子主题2.1 文献群]
[子主题2.2 文献群]
[主题评述段(嵌入式评述)]

## 1.2.3 主题3(对应研究内容3)
[引入段]
[子主题3.1 文献群]
[子主题3.2 文献群]
[主题评述段(嵌入式评述)]

## 1.2.X 文献评述(独立评述小节,可选)
[开头段]
[主题评述段1]
[主题评述段2]
[主题评述段3]
[总结段]

## 参考文献
[参考文献列表]

输出2:BibTeX格式引用库

bibtex
% NSFC申请书文献综述引用库
% 生成时间:YYYY-MM-DD
% 项目主题:XXX

@article{key1,
  title = {文献标题},
  author = {作者},
  journal = {期刊},
  year = {年份},
  doi = {DOI}
}

引文格式要求

正文引用

  • 作者-年份制(优先):作者等(年份) 或 Author et al.(年份)
  • 编号制(按用户需求自适应):[1]、[2]

参考文献输出(唯一格式)

  • BibTeX格式(强制)
  • 必须完整字段(title/author/journal/year)
  • 尽可能存留DOI
  • 不允许缺失关键信息(如未知需标注)
  • 用于 Zotero / BibTeX 直接导入

语言约束

  • 除了必要的术语、文件名、标题等,使用中文
  • 中英文混合引用(中文文献用"姓名等(年份)",英文文献用"Author等(年份)")

禁止行为

  1. ❌ 禁止文献摘要式输出
  2. ❌ 禁止简单罗列论文
  3. ❌ 禁止时间线式综述
  4. ❌ 禁止固定模板化写作(段落/句子模板不允许预设)
  5. ❌ 禁止文献与研究主题脱节组织
  6. ❌ 禁止文献独立成体系
  7. ❌ 禁止文献评述只是总结,无批判性判断
  8. ❌ 禁止调用子agent
  9. ❌ 禁止使用 PubMed 和 arXiv 检索
  10. ❌ 禁止营销类文章、无来源内容、二次转载数据、非学术总结性材料
  11. ❌ 禁止使用 claim_extractor.py 和 support_llm.py(逐条声明评估,非本技能用途)
  12. ❌ 禁止下载全文(CNKI/ScienceDirect 仅收集元数据,不点 Download/View PDF)

最终原则

文献综述的结构,应当从NSFC成功本子中"学习出来",而不是"写死出来"。

文献不是独立成体系,而是服务用户研究构想。每篇文献都应在"文献→研究问题/方法/创新"的论证链中找到位置。

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 Literature Review Writer AI skill do?

撰写NSFC申请书的国内外研究现状及发展动态分析+文献评述。Invoke when user asks to write NSFC literature review, 国内外研究现状, 文献综述, 文献评述, or 1.2部分 of NSFC proposal.

Why use Fund Literature Review Writer on TypingMind?

Because you install it once and use it with any model. Fund Literature Review 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 Literature Review 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-literature-review-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 Literature Review 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 Literature Review Writer?

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

Is the Fund Literature Review 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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