Systematic peer review toolkit. Evaluate methodology, statistics, design, reproducibility, ethics, figure integrity, reporting standards, for manuscript and grant review across disciplines.
npx skills add https://github.com/Microck/ordinary-claude-skills --skill peer-review
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:
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:
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:
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like \"the xlsx in my downloads\") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
Picks random winners from lists, spreadsheets, or Google Sheets for giveaways, raffles, and contests. Ensures fair, unbiased selection with transparency.
Query openFDA API for drugs, devices, adverse events, recalls, regulatory submissions (510k, PMA), substance identification (UNII), for FDA regulatory data analysis and safety research.
MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differential equations, optimization, statistics, or creating scientific visualizations. Also use when the user needs help with MATLAB syntax, functions, or wants to convert between MATLAB and Python code. Scripts can be executed with MATLAB or the open-source GNU Octave interpreter.
UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .xltx, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like \"the xlsx in my downloads\") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
Creating interactive data visualisations using d3.js. This skill should be used when creating custom charts, graphs, network diagrams, geographic visualisations, or any complex SVG-based data visualisation that requires fine-grained control over visual elements, transitions, or interactions. Use this for bespoke visualisations beyond standard charting libraries, whether in React, Vue, Svelte, vanilla JavaScript, or any other environment.
Take microck/peer-review from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.