Agent skill · Code Review & Quality

peer-review

Structured manuscript/grant review with checklist-based evaluation. Use when writing formal peer reviews with specific criteria methodology assessment, statistical validity, reporting standards compliance (CONSORT/STROBE), and constructive feedback. Best for actual review writing, manuscript revision. For evaluating claims/evidence quality use scientific-critical-thinking; for quantitative scoring frameworks use scholar-evaluation.

majiayu000github.com/majiayu000GitHub ↗
claude-codecan modify filesMIT
Install
npx skills add majiayu000/claude-skill-registry --skill scientific-peer-review-blurjp-imageprepmcp-2 --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 23 KB
Bundled scripts: none
Allowed tools: ReadWriteEditBash
Path: skills/analysis/scientific-peer-review-blurjp-imageprepmcp-2/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

Review
written from the skill's own SKILL.md · Aug 5, 2026

What it does

It instructs the agent to perform a structured manuscript or grant review using a checklist-based evaluation. It emphasizes assessing methodology, statistical validity, reporting standards (CONSORT, STROBE, PRISMA), reproducibility, data availability, ethics, and providing constructive feedback. It also covers integrating visual schematics when needed and following a staged workflow from initial assessment through detailed section reviews, methodological rigor, reproducibility, and writing quality. It prescribes how to organize the peer review report with a summary statement, major/minor comments, and optional line-by-line comments or questions for authors.

How it works

The agent should:

  1. Conduct an initial assessment to determine scope, novelty, and quality, and generate a brief 2-3 sentence output capturing the manuscript’s essence and initial impression.
  2. Perform a Detailed Section-by-Section Review, evaluating Abstract/Title, Introduction, Methods, Results, Discussion, and References with explicit criteria (accuracy, clarity, completeness, accessibility; context, rationale, novelty, literature, objectives; reproducibility, rigor, detail, ethics, statistics, validation; presentation, figures/tables, statistics, objectivity, completeness, reproducibility; interpretation, limitations, context, speculation, significance, future directions; completeness and accuracy of references).
  3. Assess Methodological and Statistical Rigor with attention to statistical assumptions, effect sizes, multiple testing corrections, confidence intervals, power analysis, test selection, handling of missing data, experimental design controls, replication, randomization, blinding, and computational/bioinformatics clarity and reproducibility.
  4. Evaluate Reproducibility and Transparency, including data availability, code/materials sharing, and adherence to reporting standards (CONSORT, PRISMA, ARRIVE, MIAME, MINSEQE).
  5. Review Figure and Data Presentation for quality and integrity, including labeling, error bars, and accessibility.
  6. Check Ethical Considerations covering human/animal subjects, disclosure of conflicts, funding, and integrity concerns.
  7. Assess Writing Quality and Clarity for structure, readability, terminology, grammar, and accessibility to non-specialists.
  8. Structure feedback using the provided template: Summary Statement, Major Comments, Minor Comments, Optional Line-by-Line Comments, and Questions for Authors.
  9. Maintain a constructive and professional tone, prioritize rigor and reproducibility, and avoid unsupported conclusions or speculation.

When to use it

Use when conducting peer reviews of scientific manuscripts or evaluating grant proposals, particularly to assess methodology rigor, experimental design, statistics, reporting standards, reproducibility, and to provide actionable feedback for revision.

What it can touch

Guided by allowed-tools: Read, Write, Edit, Bash. It entails reviewing text, extracting key criteria, and composing a structured review document. It also optionally references generating schematics via the dedicated schematics workflow and including them in the review if relevant.

Caveats

The skill emphasizes following reporting guidelines (CONSORT, STROBE, PRISMA) and ensuring reproducibility, but it does not guarantee publication outcomes. It relies on the user to supply manuscript content for evaluation and to adapt recommendations to disciplinary norms.

From the SKILL.md

# Scientific Critical Evaluation and Peer Review ## Overview Peer review is a systematic process for evaluating scientific manuscripts. Assess methodology, statistics, design, reproducibility, ethics, and reporting standards. Apply this skill for manuscript and grant review across disciplines with constructive, rigorous evaluation. ## When to Use This Skill This skill should be used when: - Conducting peer review of scientific manuscripts for journals - Evaluating grant proposals and research applications - Assessing methodology and experimental design rigor - Reviewing statistical analyses and reporting standards - Evaluating reproducibility and data availability - Checking compliance with reporting guidelines (CONSORT, STROBE, PRISMA) - Providing constructive feedback on scientific writing ## Visual Enhancement with Scientific Schematics **When creating documents with this skill, always consider adding scientific diagrams and schematics to enhance visual communication.** If your document does not already contain schematics or diagrams: - Use the **scientific-schematics** skill to generate AI-powered publication-quality diagrams - Simply describe your desired diagram in natural la

What's inside
Steps it walks through
  1. Overview
  2. When to Use This Skill
  3. Visual Enhancement with Scientific Schematics
  4. Peer Review Workflow
  5. Stage 1: Initial Assessment
  6. Stage 2: Detailed Section-by-Section Review
  7. Stage 3: Methodological and Statistical Rigor
  8. Stage 4: Reproducibility and Transparency
  9. Stage 5: Figure and Data Presentation
  10. Stage 6: Ethical Considerations
  11. Stage 7: Writing Quality and Clarity
  12. Structuring Peer Review Reports
  13. Summary Statement
  14. Major Comments
Ships with 1 file
  • metadata.json
Commands it runs
python scripts/generate_schematic.py "your diagram description" -o figures/output.png
python skills/scientific-slides/scripts/pdf_to_images.py presentation.pdf review/slide --dpi 150
More from claude-skill-registry
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About this skill
What does the peer-review skill do?

Structured manuscript/grant review with checklist-based evaluation. Use when writing formal peer reviews with specific criteria methodology assessment, statistical validity, reporting standards compliance (CONSORT/STROBE), and constructive feedback. Best for actual review writing, manuscript revision. For evaluating claims/evidence quality use scientific-critical-thinking; for quantitative scoring frameworks use scholar-evaluation.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill scientific-peer-review-blurjp-imageprepmcp-2 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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