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Mgmt Paper Writing

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HaonanAlex
mgmt-paper-writing

中文经济学论文写作助手。面向《经济研究》《金融研究》《管理世界》《会计研究》《管理科学学报》《数量经济技术经济研究》等顶级中文期刊，提供从选题、提纲、引言、识别策略、结果、稳健性、结论到 R&R 评审回复的全流程写作指引。当用户撰写、修改、审阅、重写、润色中文经济学论文，或需要按 GB/T 7714 引用、构造摘要、组织识别策略叙事时调用本 Skill。

Overview

PublisherHaonanAlex
RepositoryMGMT-Paper-Skills
Skill namemgmt-paper-writing
Stars
130
Forks
18
Bundled files
12
LicenseApache-2.0
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 HaonanAlex on GitHub. Read the source before you install it.

Installation

Install the Mgmt Paper Writing 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/HaonanAlex/MGMT-Paper-Skills/tree/main/mgmt-paper-writing
  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/HaonanAlex/MGMT-Paper-Skills.git /tmp/MGMT-Paper-Skills
mkdir -p .claude/skills
cp -r /tmp/MGMT-Paper-Skills/mgmt-paper-writing .claude/skills/mgmt-paper-writing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mgmt Paper Writing 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 Mgmt Paper Writing 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 Mgmt Paper Writing 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.

MGMT - Paper - Writing — 中文经济学论文写作助手

适用场景

本 Skill 服务于以中文撰写、目标投稿国内顶级经济学/金融学/管理学期刊的研究者。常见任务：

  • 帮助构思与组织一篇中文经济学论文的整体结构
  • 撰写或润色摘要、引言、文献综述、识别策略、实证结果、稳健性、结论
  • 按 GB/T 7714-2015 整理参考文献
  • 针对 DID、IV、RDD、SC、Event Study、Bartik、结构估计等识别策略，给出符合中文期刊话语习惯的写作建议
  • 起草 R&R 评审回复信

核心写作原则（中文经济学论文）

  1. 问题先行，政策导向：中文顶级期刊偏好"问题—理论—证据—政策"的叙事链条。引言第一段必须用 2-3 句话说清"中国当下的什么问题"以及"为什么值得研究"，而非直接进入文献缝隙。
  2. 政策背景厚重：相比英文期刊，中文期刊允许并鼓励较为充分的制度与政策背景描述（通常 0.5-1 页）。在 DID、政策评估类论文中尤其关键。
  3. 理论先行的传统：很多中文期刊（尤其《经济研究》《管理世界》）期望在实证之前有一段简洁的理论分析或理论假说，并提出可检验的命题/假设 H1、H2、…。
  4. 机制分析必备：不仅要识别"是否有效应"，还要分析"为什么有效应"。机制章节通常单独成节，给出 2-3 条机制并各自检验。
  5. 稳健性要做厚：包括样本替换、变量替换、估计量替换、安慰剂检验、平行趋势、剔除其他政策干扰等。中文审稿人对稳健性厚度的容忍度较高，宁多勿少。
  6. 结论"三段式"：研究发现 + 理论贡献 + 政策建议。政策建议是中文论文不可缺的一节。
  7. 语言克制、避免口语：少用"非常""很""极其"等程度副词，多用"显著""稳健""异质性"等学术术语。避免比喻和形象化表达。

章节模板（实证类论文）

中文实证论文的常见骨架：

  1. 引言（约 1500-2500 字）

    • 第 1 段：现实问题与政策背景
    • 第 2 段：本文研究问题与边际贡献（边际贡献通常列 2-3 条）
    • 第 3 段：识别策略与主要发现概述
    • 第 4 段：文献定位（区别于哪些已有研究）
    • 第 5 段：行文结构

  2. 文献综述与理论分析（合并或分开均可）

    • 简要回顾国内外相关文献
    • 给出 2-4 条理论假说

  3. 制度背景与政策梳理（DID/政策评估类必备）

  4. 研究设计

    • 数据来源与样本（务必交代清洗规则）
    • 变量定义（建议附变量定义表）
    • 计量模型（写出完整方程并解释每个下标与误差项设定）

  5. 实证结果

    • 描述性统计
    • 基准回归
    • 稳健性检验
    • 异质性分析
    • 机制检验

  6. 结论与政策建议

摘要写法（中文 200-300 字）

中文摘要建议四要素结构：研究问题 → 数据与方法 → 主要发现 → 含义/贡献。

参考模板：

本文基于 [数据来源，时间区间] 的 [样本范围]，运用 [识别策略] 考察了 [核心问题]。研究发现：第一，…；第二，…；第三，…。机制分析表明，[机制]。本文的研究为 [理论/政策含义] 提供了新的经验证据，对 [应用场景] 具有参考价值。

详见 references/abstract-templates.md。

引用规范

参考文献请按 GB/T 7714-2015（信息与文献 参考文献著录规则）整理，详见 references/citation-gbt7714.md。中文文献作者姓名全写，英文文献按"姓, 名首字母."格式。

识别策略写作

不同识别策略在中文期刊中的话语习惯有所不同（例如 DID 在政策评估论文中需先讲清楚"政策的外生性"），详见 references/identification-strategies.md。

期刊定位

不同期刊的口味差异较大（《经济研究》偏宏观与公共政策、《金融研究》偏金融实证、《管理世界》偏管理与公共治理、《会计研究》偏会计议题、《管理科学学报》偏方法论严谨、《数量经济技术经济研究》偏方法与计量），详见 references/journals.md。

常见误区

中国学者中文写作常见的若干误区（口语化、过度堆砌文献、政策建议空泛、摘要中堆数字、过度自夸边际贡献等）见 references/common-mistakes.md。

工作模式

根据用户需求，本 Skill 可以以下列模式工作：

  • drafting（起草）：给定研究问题与数据，从零起草章节
  • polishing（润色）：在不改变原意前提下提升语言学术性
  • restructuring（重构）：重新组织段落顺序与逻辑
  • auditing（审稿）：以中文审稿人视角给出修改意见
  • referee-response（评审回复）：起草 R&R 回复信

各模式的具体提示词见 prompts/ 目录。

关键参考文件

  • references/journals.md — 六大顶级中文期刊定位与投稿信息
  • references/citation-gbt7714.md — GB/T 7714-2015 引用规范示例
  • references/abstract-templates.md — 中英文摘要模板
  • references/identification-strategies.md — 各识别策略的中文写作指引
  • references/common-mistakes.md — 常见写作误区
  • prompts/outline.md — 提纲生成提示词
  • prompts/intro.md — 引言写作提示词
  • prompts/results.md — 实证结果写作提示词
  • prompts/referee-response.md — 评审回复提示词

使用建议

  • 让 Claude 先读 references/journals.md 来定位目标期刊后，再开始具体章节写作
  • 写引言前先读 prompts/intro.md，能避免"上来就写文献综述"的常见失误
  • 草稿写完后，让 Claude 按 references/common-mistakes.md 自审一遍

注意事项

  • 期刊投稿网址、字数限制、最新格式要求会变化，本 Skill 给出的是公开信息中较稳定的部分；最终请以期刊官网最新通知为准。
  • 本 Skill 不替代真实的同行评议；其建议为辅助参考。
  • 政策建议部分须基于研究发现，避免"超出实证范围的政策推断"。

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 Mgmt Paper Writing AI skill do?

中文经济学论文写作助手。面向《经济研究》《金融研究》《管理世界》《会计研究》《管理科学学报》《数量经济技术经济研究》等顶级中文期刊，提供从选题、提纲、引言、识别策略、结果、稳健性、结论到 R&R 评审回复的全流程写作指引。当用户撰写、修改、审阅、重写、润色中文经济学论文，或需要按 GB/T 7714 引用、构造摘要、组织识别策略叙事时调用本 Skill。

Why use Mgmt Paper Writing on TypingMind?

Because you install it once and use it with any model. Mgmt Paper Writing 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 Mgmt Paper Writing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/HaonanAlex/MGMT-Paper-Skills/tree/main/mgmt-paper-writing. 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 Mgmt Paper Writing?

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 Mgmt Paper Writing?

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

Is the Mgmt Paper Writing AI skill free?

Yes. It is published on GitHub by HaonanAlex under the Apache-2.0 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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