Peer Review

CommunityPopular

Norman-bury

peer-review

Use before submission or when reviewing papers - provides evaluation checklists, bias detection, and self-review templates

Overview

Publisher	Norman-bury
Repository	`research-writing-skill`
Skill name	`peer-review`
Stars	3.2K
Forks	214
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

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.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by Norman-bury on GitHub. Read the source before you install it.

Installation

Install the Peer Review AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
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.

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/Norman-bury/research-writing-skill.git /tmp/research-writing-skill
mkdir -p .claude/skills
cp -r /tmp/research-writing-skill/skills/peer-review .claude/skills/peer-review

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Peer Review 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 Peer Review 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 Peer Review 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.

同行评审与自审

本技能提供论文评审、自我审视和批判性分析的完整指南。

Checklist

一、同行评审工作流程

阶段1：初步评估

关键问题：

核心研究问题或假设是什么？
主要发现和结论是什么？
工作是否科学合理且有意义？
是否适合目标期刊/会议？
是否存在明显的重大缺陷？

输出：2-3句话的简要总结。

阶段2：逐节详细审查

摘要与标题

摘要是否准确反映研究内容和结论？
标题是否具体、准确、信息丰富？

引言

背景信息是否充分且最新？
研究问题是否有明确的动机和理由？
相关先前研究是否被适当引用？

方法

其他研究者能否根据描述复现研究？
方法是否适合解决研究问题？
统计方法是否适当？

结果

结果是否逻辑清晰地呈现？
图表是否适当、清晰且正确标注？
是否包含所有相关结果？

讨论

结论是否有数据支持？
研究局限性是否被承认和讨论？
推测是否与数据支持的结论明确区分？

阶段3：方法论和统计严谨性

统计评估：

统计假设是否满足？
是否报告效应量和p值？
是否适当应用多重检验校正？
样本量是否有功效分析支持？

实验设计：

对照是否适当和充分？
重复是否足够？
潜在混杂因素是否被控制？

二、审稿报告结构

总结陈述

markdown
## 总体评估

**研究概述**：[1-2句话概括]

**总体建议**：[接受/小修/大修/拒稿]

**关键优点**：
1. [优点1]
2. [优点2]

**关键缺点**：
1. [缺点1]
2. [缺点2]

主要意见

显著影响论文有效性的关键问题：

基本方法论缺陷
不适当的统计分析
不支持或过度陈述的结论
缺少关键对照或实验

次要意见

改善清晰度和完整性的问题：

图表标签或图例不清晰
缺少方法细节
排版或语法错误

三、批判性思维框架

偏倚检测

偏倚类型	检查要点
确认偏倚	是否只强调支持性发现？
选择偏倚	样本是否代表目标人群？
发表偏倚	是否缺少阴性结果？
P-hacking	是否多次分析直到显著？

逻辑谬误识别

谬误类型	表现
事后归因	"B跟在A后面，所以A导致了B"
相关=因果	混淆关联与因果
草率泛化	从小样本得出广泛结论
挑选数据	只选择支持性证据

四、自我审稿提示词

投稿前自查

markdown
# Role
你是一位严苛的资深学术审稿人。

# Task
请深入阅读并分析我的论文，撰写严厉但建设性的审稿报告。

# 审查维度
1. **原创性**：实质性突破还是边际增量？
2. **严谨性**：推导是否有跳跃？实验对比是否公平？
3. **一致性**：声称的贡献是否得到验证？

# Output
- Part 1 [Review Report]：Summary, Strengths, Weaknesses, Rating
- Part 2 [Strategic Advice]：具体改进建议

# Input
投稿目标：[期刊/会议名]
论文内容：[粘贴]

快速质量检查

markdown
# Task
快速检查论文是否存在以下问题：

1. 逻辑一致性：引言的声明是否在实验中得到验证？
2. 术语一致性：核心概念是否保持一致命名？
3. 数据支持：所有结论是否有数据支持？
4. 对照完整性：是否与足够的baseline比较？
5. 消融充分性：是否验证了每个关键模块？

# Output
- 无问题：[检测通过]
- 有问题：分点列出位置和具体问题

五、审稿语气

最佳实践

建设性：将批评框架为改进机会
具体：提供具体例子和可操作建议
平衡：承认优点和缺点
尊重：记住作者投入了大量努力
客观：关注科学，而非科学家

避免事项

人身攻击或轻蔑语言
没有具体例子的模糊批评
要求超出范围的不必要实验
在双盲评审中暴露身份

六、审稿检查清单

总结陈述清楚传达整体评估
主要问题被清楚识别和论证
建议的修改具体且可操作
统计方法已被评估
可重复性和数据可用性已评估
图表已评估质量和完整性
全文语气建设性且专业

Frequently asked questions

What does the Peer Review AI skill do?

Use before submission or when reviewing papers - provides evaluation checklists, bias detection, and self-review templates

Why use Peer Review on TypingMind?

Because you install it once and use it with any model. Peer Review 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 Peer Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Norman-bury/research-writing-skill/tree/main/skills/peer-review. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Peer Review?

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 Peer Review?

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

Is the Peer Review AI skill free?

Yes. It is published on GitHub by Norman-bury 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

同行评审与自审

Checklist

一、同行评审工作流程

阶段1：初步评估

阶段2：逐节详细审查

摘要与标题

引言

方法

结果

讨论

阶段3：方法论和统计严谨性

二、审稿报告结构

总结陈述

主要意见

次要意见

三、批判性思维框架

偏倚检测

逻辑谬误识别

四、自我审稿提示词

投稿前自查

快速质量检查

五、审稿语气

最佳实践

避免事项

六、审稿检查清单

Frequently asked questions

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