Agent skill

Peer Review Guide

by wentorai in wentorai/research-plugins

Conduct thorough, constructive peer reviews and evaluate research papers

MITAuto-check passedResearch & Science

Install Peer Review Guide

skills CLI
$ npx skills add wentorai/research-plugins --skill peer-review-guide -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install wentorai/research-plugins peer-review-guide --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/research/paper-review/peer-review-guide .claude/skills/peer-review-guide && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
peer-review-guide
GitHub stars
298
Used in
1 other repo
Token cost
~2k tokens
SKILL.md length
203 words
Files
1
Skills in repo
405
Repo updated
First seen
Licence
MIT

At a glance

Conduct thorough, constructive peer reviews and evaluate research papers

  • Tasks that involve Peer review
  • SKILL.md covers Review Process Overview, Evaluation Framework, Writing the Review Report and Common Red Flags to Check, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Peer Review Guide is an agent skill from wentorai/research-plugins. Conduct thorough, constructive peer reviews and evaluate research papers

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science, covering Peer review. The repository describes itself as: 350+ academic research skills, MCP configs, and plugins for Research-Claw and AI agents. The licence is MIT.

When your agent uses it

  • Tasks that involve Peer review

Example prompts

  • “/peer-review-guide”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit bf44b3c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Peer Review Guide loads about 2k tokens when it runs. Until then it costs about 23 tokens; SKILL.md has 203 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~23
When it runs · the whole SKILL.md, loaded when a task matches
~2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from wentorai/research-plugins at commit bf44b3c, republished under its MIT licence (© wentorai). 203 words, ~1,952 tokens.

Download SKILL.mdSave it as .claude/skills/peer-review-guide/SKILL.md (or your agent's skills folder).
name
peer-review-guide
description
Conduct thorough, constructive peer reviews and evaluate research papers

Peer Review Guide

A skill for conducting thorough, fair, and constructive peer reviews of academic manuscripts. Covers systematic evaluation frameworks, writing effective reviewer reports, and common evaluation criteria across disciplines.

Review Process Overview

Systematic Reading Strategy
First Pass (30 min): Skim for overall assessment
  - Read title, abstract, introduction, conclusion
  - Scan figures and tables
  - Assess: Is this paper in scope? Is the question important?

Second Pass (60-90 min): Detailed critical reading
  - Read the full paper carefully
  - Annotate unclear points, potential errors, missing references
  - Check methodology, statistical analyses, interpretation

Third Pass (30-60 min): Constructive feedback
  - Formulate your major and minor comments
  - Identify strengths to highlight
  - Draft your review report

Evaluation Framework

Core Assessment Dimensions
python
def evaluate_manuscript(assessments: dict) -> dict:
    """
    Structured manuscript evaluation across key dimensions.

    Args:
        assessments: Dict mapping dimension to score (1-5) and comments
    """
    dimensions = {
        'novelty': {
            'weight': 0.20,
            'questions': [
                'Does this paper present new findings, methods, or perspectives?',
                'How does it advance beyond existing work?',
                'Is the contribution incremental or substantial?'
            ]
        },
        'significance': {
            'weight': 0.20,
            'questions': [
                'Is the research question important to the field?',
                'Will this work influence future research or practice?',
                'Is the scope appropriate for this journal?'
            ]
        },
        'methodology': {
            'weight': 0.25,
            'questions': [
                'Is the study design appropriate for the research question?',
                'Are methods described in sufficient detail to reproduce?',
                'Are statistical analyses appropriate and correctly applied?',
                'Are there threats to validity that are not addressed?'
            ]
        },
        'presentation': {
            'weight': 0.15,
            'questions': [
                'Is the paper clearly written and well organized?',
                'Are figures and tables informative and properly labeled?',
                'Is the paper an appropriate length?'
            ]
        },
        'literature': {
            'weight': 0.10,
            'questions': [
                'Is the related work section comprehensive?',
                'Are key prior studies cited and discussed?',
                'Is the paper properly positioned within the literature?'
            ]
        },
        'reproducibility': {
            'weight': 0.10,
            'questions': [
                'Are data and code available or described sufficiently?',
                'Could another researcher replicate this study?',
                'Are all materials, procedures, and analyses documented?'
            ]
        }
    }

    overall_score = 0
    evaluation = {}
    for dim, info in dimensions.items():
        score = assessments.get(dim, {}).get('score', 3)
        comment = assessments.get(dim, {}).get('comment', '')
        overall_score += score * info['weight']
        evaluation[dim] = {
            'score': score,
            'weight': info['weight'],
            'weighted_score': score * info['weight'],
            'comment': comment
        }

    evaluation['overall_score'] = round(overall_score, 2)
    evaluation['recommendation'] = (
        'Accept' if overall_score >= 4.0
        else 'Minor Revision' if overall_score >= 3.5
        else 'Major Revision' if overall_score >= 2.5
        else 'Reject'
    )

    return evaluation

Writing the Review Report

Structure Template
SUMMARY (2-3 sentences)
Briefly describe what the paper does and its main contribution.
This shows the authors you read and understood their work.

STRENGTHS (3-5 bullet points)
- Specific positive aspects
- "The experimental design is rigorous, with appropriate controls..."
- "The visualization in Figure 3 effectively communicates..."

MAJOR COMMENTS (numbered, typically 2-5)
Issues that must be addressed before the paper can be accepted.
These concern correctness, validity, or significant gaps.

1. [Specific concern with reference to section/page]
   "In Section 3.2, the assumption that X holds is questionable
    because [reason]. The authors should either provide evidence
    for this assumption or discuss what happens if it is relaxed."

2. [Another major concern]

MINOR COMMENTS (numbered, typically 3-10)
Suggestions for improvement that are not critical but would
strengthen the paper.

1. "On page 5, line 23: consider citing Smith et al. (2023)
    who address a similar phenomenon."

TYPOS AND FORMATTING (optional, brief list)
- Page 3, line 14: "effect" should be "affect"
- Table 2: column headers are cut off

CONFIDENTIAL COMMENTS TO THE EDITOR (separate section)
Overall assessment, conflicts of interest, ethical concerns.
This is NOT shared with the authors.
Writing Effective Comments
python
def format_review_comment(comment_type: str, section: str,
                           issue: str, suggestion: str) -> str:
    """
    Format a review comment following best practices.

    Args:
        comment_type: 'major' or 'minor'
        section: Where in the paper (e.g., 'Section 3.2, page 7')
        issue: What the problem is
        suggestion: How to address it
    """
    return (
        f"[{comment_type.upper()}] {section}\n"
        f"Issue: {issue}\n"
        f"Suggestion: {suggestion}\n"
    )

# Good review comment (specific, actionable, constructive):
print(format_review_comment(
    'major',
    'Section 4.1, Table 3',
    'The comparison with baseline methods uses different evaluation metrics '
    '(accuracy for the proposed method, F1 for baselines), making the '
    'comparison unfair.',
    'Please report the same set of metrics (precision, recall, F1, accuracy) '
    'for all methods, including the proposed approach, to enable fair comparison.'
))

Common Red Flags to Check

Statistical Issues
  • p-hacking: Multiple comparisons without correction
  • Selective reporting: Only positive results shown
  • Inappropriate tests: Parametric tests on non-normal data
  • Missing effect sizes: Only p-values reported
  • Small sample with large claims: Low power, inflated effects
Methodological Issues
  • Lack of control group or baseline
  • Data leakage in ML (test data used during training/validation)
  • Confounding variables not addressed
  • Circular reasoning in analysis
Writing Issues
  • Claims not supported by the data presented
  • Overclaiming in the title or abstract
  • Missing limitations section
  • Insufficient detail for reproducibility

Ethical Responsibilities of Reviewers

  • Declare conflicts of interest promptly
  • Maintain confidentiality -- do not share the manuscript or discuss it
  • Complete reviews within the agreed timeline (typically 2-4 weeks)
  • Be constructive -- the goal is to improve the paper, not to display superiority
  • Do not use ideas from the manuscript under review in your own work
  • If you suspect misconduct (fabrication, falsification, plagiarism), report to the editor confidentially

© wentorai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/research/paper-review/peer-review-guide of wentorai/research-plugins.

Open the folder on GitHubat commit bf44b3c

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in wentorai/research-plugins, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Peer Review Guide next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Questions about Peer Review Guide

What does Peer Review Guide do?

Conduct thorough, constructive peer reviews and evaluate research papers. Peer Review Guide is an agent skill from wentorai/research-plugins.

When should I use Peer Review Guide?

Peer Review Guide fits situations like: tasks that involve Peer review.

How do I install Peer Review Guide in Claude Code?

Run `npx skills add wentorai/research-plugins --skill peer-review-guide -a claude-code`. Or copy the skill folder (skills/research/paper-review/peer-review-guide in wentorai/research-plugins) into .claude/skills/peer-review-guide in your project. Claude Code loads it when a task matches its description.

How do I install Peer Review Guide in Codex?

Run `npx skills add wentorai/research-plugins --skill peer-review-guide -a codex`. Or copy the skill folder (skills/research/paper-review/peer-review-guide in wentorai/research-plugins) into .agents/skills/peer-review-guide in your project. Codex loads it when a task matches its description.

Can I use Peer Review Guide in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add wentorai/research-plugins --skill peer-review-guide -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/peer-review-guide, .gemini/skills/peer-review-guide, .github/skills/peer-review-guide and .opencode/skills/peer-review-guide in your project.

What does Peer Review Guide need to run?

SKILL.md names no scripts, command-line tools or credentials: Peer Review Guide is instructions for the agent only. Our summary lists: Python 3.

Does Peer Review Guide access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Peer Review Guide safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Peer Review Guide use?

Peer Review Guide is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Peer Review Guide use?

About 2k tokens (SKILL.md is roughly 7.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Peer Review Guide?

Skills that share tags, products or a category with Peer Review Guide: Peer Review (spacering-net/codeg, 3.9k stars), Scholar Evaluation (spacering-net/codeg, 3.9k stars), Academic Paper Writing Pipeline (Imbad0202/academic-research-skills, 51k stars) and Academic Paper Reviewer (Imbad0202/academic-research-skills, 51k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Peer Review Guide?

wentorai (a GitHub user) maintains it in wentorai/research-plugins, which has 298 GitHub stars. The repository holds 405 skills in this directory. The repository was last updated on June 19, 2026.

Source: wentorai/research-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.