Agent skill · Code Review & Quality

scientific-reviewer

Comprehensive scientific document review and analysis. Use when Claude needs to review scientific papers, reports, preprints, or other research documents for: (1) Identifying and evaluating claims and supporting evidence, (2) Assessing logical argumentation and experimental design, (3) Reviewing citation adequacy and suggesting additional references, (4) Determining document type and research contribution, (5) Checking technical accuracy and methodology, (6) Providing constructive feedback on presentation and clarity. Also handles language, grammar, and formatting review separately.

majiayu000github.com/majiayu000GitHub ↗
claude-coderead-onlyMIT
Install
npx skills add majiayu000/claude-skill-registry --skill scientific-reviewer --agent claude-code

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

Facts
Files in the skill folder: 2
SKILL.md size: 6 KB
Bundled scripts: none
Allowed tools: *
Path: skills/analysis/scientific-reviewer/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.

From the SKILL.md

# Scientific Reviewer This skill transforms Claude into a rigorous scientific peer reviewer, systematically evaluating research documents across multiple dimensions of scientific quality and integrity. ## Review Framework Conduct reviews using this structured approach: ### 1. Document Classification First, identify the document type and scope: - **Research Article**: Original empirical research with novel findings - **Review Paper**: Synthesis of existing literature (narrative, systematic, meta-analysis) - **Methods Paper**: New methodology, technique, or protocol development - **Brief Communication/Letter**: Short report of preliminary or specific findings - **Technical Report**: Detailed documentation of procedures, software, or data - **Commentary/Perspective**: Opinion piece or interpretation of existing work - **Case Study**: Detailed examination of specific example or instance ### 2. Claims Analysis For each major claim in the document: - **Identify the claim**: Extract explicit and implicit assertions - **Locate supporting evidence**: Map claims to specific data, figures, tables, or citations - **Assess evidence quality**: Evaluate if evidence is sufficient, appropriate, and

What's inside
Steps it walks through
  1. Review Framework
  2. 1. Document Classification
  3. 2. Claims Analysis
  4. 3. Logic and Argumentation Review
  5. 4. Citation Analysis
  6. 5. Methodological Assessment
  7. 6. Technical Accuracy
  8. Review Output Structure
  9. Executive Summary
  10. Detailed Review
  11. Minor Issues (Separate Section)
  12. Suggested Citations Protocol
  13. Reviewer Tone and Approach
  14. Quality Assurance Checks
Ships with 1 file
  • metadata.json
More from claude-skill-registry
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About this skill
What does the scientific-reviewer skill do?

Comprehensive scientific document review and analysis. Use when Claude needs to review scientific papers, reports, preprints, or other research documents for: (1) Identifying and evaluating claims and supporting evidence, (2) Assessing logical argumentation and experimental design, (3) Reviewing citation adequacy and suggesting additional references, (4) Determining document type and research contribution, (5) Checking technical accuracy and methodology, (6) Providing constructive feedback on presentation and clarity. Also handles language, grammar, and formatting review separately.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill scientific-reviewer --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.

Keep going