### Peer Review
Works with
name: "peer-review"
description: "Structured manuscript/grant review with checklist-based evaluation. Use when writing formal peer reviews with specific criteria methodology assessment, statistical validity, reporting standards compli..."
allowed-tools: "Read Write Edit Bash"
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionpeer-reviewExecute the skills CLI command in your project's root directory to begin installation:
Fetches peer-review from K-Dense-AI/scientific-agent-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate peer-review. Access via /peer-review in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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| name | peer-review |
| description | 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. |
| allowed-tools | Read Write Edit Bash |
| license | MIT license |
| metadata | version: "1.0" skill-author: K-Dense Inc. |
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.
This skill should be used when:
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:
For new documents: Scientific schematics should be generated by default to visually represent key concepts, workflows, architectures, or relationships described in the text.
How to generate schematics:
python scripts/generate_schematic.py "your diagram description" -o figures/output.png
The AI will automatically:
When to add schematics:
For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.
Conduct peer review systematically through the following stages, adapting depth and focus based on the manuscript type and discipline.
Begin with a high-level evaluation to determine the manuscript's scope, novelty, and overall quality.
Key Questions:
Output: Brief summary (2-3 sentences) capturing the manuscript's essence and initial impression.
Conduct a thorough evaluation of each manuscript section, documenting specific concerns and strengths.
Critical elements to verify:
Common issues to identify:
Red flags:
Evaluate the technical quality and rigor of the research with particular attention to common pitfalls.
Statistical Assessment:
Experimental Design:
Computational/Bioinformatics:
Assess whether the research meets modern standards for reproducibility and open science.
Data Availability:
Code and Materials:
Reporting Standards:
references/reporting_standards.md for common guidelinesEvaluate the quality, clarity, and integrity of data visualization.
Quality Checks:
Integrity Checks:
Clarity:
Verify that the research meets ethical standards and guidelines.
Human Subjects:
Animal Research:
Research Integrity:
Assess the manuscript's clarity, organization, and accessibility.
Structure and Organization:
Writing Quality:
Accessibility:
Organize feedback in a hierarchical structure that prioritizes issues and provides actionable guidance.
Provide a concise overall assessment (1-2 paragraphs):
List critical issues that significantly impact the manuscript's validity, interpretability, or significance. Number these sequentially for easy reference.
Major comments typically include:
For each major comment:
List less critical issues that would improve clarity, completeness, or presentation. Number these sequentially.
Minor comments typically include:
For each minor comment:
For manuscripts requiring detailed feedback, provide section-specific or line-by-line comments:
List specific questions that need clarification:
Maintain a constructive, professional, and collegial tone throughout the review.
Best Practices:
Avoid:
⚠️ CRITICAL: For presentations, NEVER read the PDF directly. ALWAYS convert to images first.
When reviewing scientific presentations (PowerPoint, Beamer, slide decks):
NEVER attempt to read presentation PDFs directly - this causes buffer overflow errors and doesn't show visual formatting issues.
Required Process:
python skills/scientific-slides/scripts/pdf_to_images.py presentation.pdf review/slide --dpi 150
# Creates: review/slide-001.jpg, review/slide-002.jpg, etc.
Print when starting review:
[HH:MM:SS] PEER REVIEW: Presentation detected - converting to images for review
[HH:MM:SS] PDF REVIEW: NEVER reading PDF directly - using image-based inspection
Visual Design and Readability:
Layout and Formatting (Check EVERY Slide Image):
Content Quality:
Structure and Flow:
Scientific Content:
Common Presentation Issues to Flag:
Critical Issues (Must Fix):
Major Issues (Should Fix):
Minor Issues (Suggestions for Improvement):
Summary Statement:
Layout and Formatting Issues (By Slide Number):
Slide 3: Text overflow - bullet point 4 extends beyond right margin
Slide 7: Element overlap - figure overlaps with caption text
Slide 12: Font size - axis labels too small to read from distance
Slide 18: Alignment - title not centered
Content and Structure Feedback:
Design and Accessibility:
Timing and Scope:
[14:30:00] PEER REVIEW: Starting review of presentation
[14:30:05] PEER REVIEW: Presentation detected - converting to images
[14:30:10] PDF REVIEW: Running pdf_to_images.py on presentation.pdf
[14:30:15] PDF REVIEW: Converted 25 slides to images in review/ directory
[14:30:20] PDF REVIEW: Inspecting slide 1/25 - title slide
[14:30:25] PDF REVIEW: Inspecting slide 2/25 - introduction
...
[14:35:40] PDF REVIEW: Inspecting slide 25/25 - acknowledgments
[14:35:45] PDF REVIEW: Completed image-based review
[14:35:50] PEER REVIEW: Found 8 layout issues, 3 content issues
[14:35:55] PEER REVIEW: Generating structured feedback by slide number
Remember: For presentations, the visual inspection via images is MANDATORY. Never attempt to read presentation PDFs as text - it will fail and miss all visual formatting issues.
This skill includes reference materials to support comprehensive peer review:
Guidelines for major reporting standards across disciplines (CONSORT, PRISMA, ARRIVE, MIAME, STROBE, etc.) to evaluate completeness of methods and results reporting.
Catalog of frequent methodological and statistical issues encountered in peer review, with guidance on identifying and addressing them.
Before finalizing the review, verify:
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
K-Dense-AI/scientific-agent-skills
K-Dense-AI/scientific-agent-skills
google-deepmind/science-skills
google-deepmind/science-skills
google-deepmind/science-skills
BuilderIO/skills
Registry listing for peer-review matched our evaluation — installs cleanly and behaves as described in the markdown.
peer-review has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in peer-review — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: peer-review is focused, and the summary matches what you get after install.
We added peer-review from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
We added peer-review from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
peer-review reduced setup friction for our internal harness; good balance of opinion and flexibility.
Useful defaults in peer-review — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
peer-review has been reliable in day-to-day use. Documentation quality is above average for community skills.
peer-review is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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