peer-review

What it does

It provides a framework for systematically evaluating scientific manuscripts and grant proposals across disciplines, focusing on methodology, statistics, design, reproducibility, ethics, figure integrity, and reporting standards. It guides the reviewer through staged assessment, from initial assessment to detailed section-by-section review, methodological and statistical rigor, reproducibility, figure quality, ethical considerations, and writing clarity. It also prescribes structuring peer review reports with a summary, major and minor comments, and optional line-by-line comments, plus special guidance for incorporating visual schematics when appropriate.

How it works

The skill outlines a staged peer-review workflow with specific focus areas:

• Stage 1: Initial Assessment to generate a brief 2-3 sentence summary of scope and quality.
• Stage 2: Detailed Section-by-Section Review covering Abstract/Title, Introduction, Methods (reproducibility, rigor, ethics, statistics, validation), Results, Discussion, References, and common issues to flag.
• Stage 3: Methodological and Statistical Rigor, including statistical assumptions, effect sizes, multiple testing, power analysis, and experimental design controls.
• Stage 4: Reproducibility and Transparency, addressing data availability, code/materials, and adherence to reporting standards.
• Stage 5: Figure and Data Presentation, evaluating quality and integrity of visualizations.
• Stage 6: Ethical Considerations, covering human/animal subjects, consent, conflicts of interest, and data integrity.
• Stage 7: Writing Quality and Clarity, assessing structure, language, and accessibility. It also instructs on structuring peer review reports with a Summary Statement, Major and Minor Comments, and optional Specific Line-by-Line Comments and Questions for Authors. It includes guidance on adding scientific schematics to enhance communication and describes a schematic generation workflow if diagrams are not present. Commands and script references include a recommended schematic generation invocation and references to the scientific-schematics workflow.

When to use it

Use when evaluating manuscripts for journals, assessing grant proposals, and reviewing methodology, design, statistics, reproducibility, ethics, and reporting standards. Also applies to providing constructive feedback on scientific writing and ensuring alignment with reporting guidelines (CONSORT, STROBE, PRISMA).

What it can touch

The skill references the allowed tools Read, Write, Edit, Bash and includes commands such as a Python script invocation for schematic generation:

• python scripts/generate_schematic.py "your diagram description" -o figures/output.png It implies interaction with figure outputs stored in a figures/ directory.

Caveats

The material provides a comprehensive review framework but does not guarantee publication outcomes; it emphasizes constructive, evidence-based feedback and adherence to reporting standards. It notes the use of external schematic generation, accessibility considerations (colorblind-friendly, high contrast), and the need to tailor depth based on manuscript type and discipline.