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Review Others Manuscripts

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gxCaesar
review-others-manuscripts

Use when acting as an invited referee on someone else's submission, including writing a referee report, drafting reviewer comments, assessing a revision round against the authors' response letter, running an editorial prescreen for scope and policy, or judging whether a stated claim is carried by the evidence in a manuscript under review. Use for a manuscript that is not yours and is confidential; rehearsing objections against your own unsubmitted paper is a different task.

Overview

PublishergxCaesar
Repositoryopen-research-skills
Skill namereview-others-manuscripts
Stars
63
Forks
3
Bundled files
8
LicenseApache-2.0
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.

  • 8 bundled files

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

  • Open source

    Published by gxCaesar on GitHub. Read the source before you install it.

Installation

Install the Review Others Manuscripts 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/gxCaesar/open-research-skills/tree/main/skills/review-others-manuscripts
  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/gxCaesar/open-research-skills.git /tmp/open-research-skills
mkdir -p .claude/skills
cp -r /tmp/open-research-skills/skills/review-others-manuscripts .claude/skills/review-others-manuscripts
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Review Others Manuscripts 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 Review Others Manuscripts 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 Review Others Manuscripts 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.

Review Someone Else's Manuscript

A referee report answers one question for the editor: is each claim carried by the evidence offered for it, and if not, what would carry it. Everything else in the report serves that question.

The manuscript is confidential and belongs to its authors. That constraint shapes what you may do with it before it shapes what you write.

Select one mode

ModeResponsibilityRead first
initial-reviewFirst-round report on a new submissionreferences/claim-evidence-review.md
revision-roundCheck the response letter against the actual changesreferences/revision-round.md
editorial-prescreenScope, fit and policy compliance before peer reviewreferences/prescreen.md
confidentialityEstablish what may be done with the manuscript at allreferences/confidentiality.md

Read confidentiality before opening the manuscript in any tool. It constrains the other three modes rather than following them.

Resolve the installed skill and components

Resolve SKILL_DIR as the directory containing this SKILL.md. Every runtime resource is below that directory; never resolve through a package parent.

The confidentiality boundary

A manuscript under review is unpublished, non-public work shared with you for one purpose. Do not redistribute it, do not quote it outside the report, do not use its results in your own work before publication, and do not paste it into a service that retains submissions unless the journal's own policy permits that service by name.

Declare a competing interest and decline where one exists. Reviewing a direct competitor's submission while working on the same problem is a conflict even when you intend to be fair, and the intention is not the test.

If you delegate any part of the reading, the confidentiality obligation travels with the text. Whoever reads it is bound by the same terms, and the journal's policy decides whether that delegation is permitted at all.

Structure a report the editor can act on

Separate three things and never merge them.

Claims and their support. Take each claim the authors make and find the evidence offered. Report the ones where the claim is broader than the support, naming the location of both. This section is the report.

Defects. Problems that make a reported result unsafe: a leaked split, an undefined metric, a comparator that was not given a fair budget, an independence assumption the design violates, a statistical test whose assumptions the data breaks. State the consequence, not only the deviation.

Requests. What would resolve each point. A request must be executable by the authors with material they plausibly have. "Run a larger study" is not a request; "report the per-site breakdown that the aggregate in Table 2 was computed from" is.

Calibrate the severity

SeverityTest
FatalThe result would not survive the correction
MajorThe result probably survives, but the paper cannot be judged until it is shown
MinorThe claim is unaffected; the presentation misleads
TasteYou would have done it differently and the paper is not worse for it

Taste-level points belong in a short final paragraph or nowhere. Presenting them at major severity is the most common way a report becomes unusable to an editor.

Write for two readers

The editor needs a recommendation and the two or three points it rests on, near the top. The authors need every point located and actionable. Write the report so that both are served without a private section that contradicts the public one.

Boundaries

This skill drafts a report; it does not decide acceptance and does not audit an author's raw data. It does not rehearse objections against your own manuscript, and it does not carry any individual's personal reviewing voice: the method is the transferable part.

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 Review Others Manuscripts AI skill do?

Use when acting as an invited referee on someone else's submission, including writing a referee report, drafting reviewer comments, assessing a revision round against the authors' response letter, running an editorial prescreen for scope and policy, or judging whether a stated claim is carried by the evidence in a manuscript under review. Use for a manuscript that is not yours and is confidential; rehearsing objections against your own unsubmitted paper is a different task.

Why use Review Others Manuscripts on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gxCaesar/open-research-skills/tree/main/skills/review-others-manuscripts. 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 Review Others Manuscripts?

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 Review Others Manuscripts?

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

Is the Review Others Manuscripts AI skill free?

Yes. It is published on GitHub by gxCaesar 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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