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review-python

Review Python notebooks and scripts for methodology, reproducibility, and PEP8 compliance.

5|1|Updated Feb 10, 2026
Search Tags:#research#python#style#code-review#reproducibility#notebooks
One-click install
npx skills add https://github.com/mgaldino/agents-workflow --skill review-python
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: review-python
Source: https://github.com/mgaldino/agents-workflow/tree/main/skills-docs/review-python
Command: npx skills add https://github.com/mgaldino/agents-workflow --skill review-python

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The Skill helps researchers and engineers perform a structured quality review of Python code, reducing manual review time and surfacing issues early.

Core Features & Use Cases

  • Structured review checklist: methodology correctness, code quality, reproducibility, performance, and presentation of results.
  • Language support: review Python code in notebooks (.ipynb) and scripts (.py).
  • Use Case: A researcher receives a Python notebook; use this Skill to generate a formatted review report that highlights methodological concerns, code quality gaps, and reproducibility steps.

Quick Start

Review the provided Python file or notebook and output a structured assessment.

Frequently Asked Questions about review-python

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I review Python code quality in research notebooks?▼

Reviewing Python research notebooks involves validating methodology, PEP8 style, and reproducibility. This automated process analyzes .ipynb and .py files to output a formatted assessment report highlighting methodological concerns and code quality gaps.

What is a structured Python code review for academic research?▼

A structured Python code review for academic research evaluates methodological correctness and reproducibility. It checks Python scripts and notebooks against a checklist covering performance, presentation, and coding practices to surface issues early.

How do I check reproducibility requirements in Python scripts?▼

Checking reproducibility requirements in Python scripts involves running an automated review that validates methodology and coding practices. This generates a formatted report highlighting reproducibility steps and methodological concerns for academic settings.

Does automated Python code review work with both .ipynb and .py files?▼

Automated Python code review supports both .ipynb notebooks and .py scripts. It targets academic settings to validate methodology, code style, and reproducibility across both file formats to generate a structured assessment.

What's the best way to validate methodology correctness in Python research projects?▼

Validating methodology correctness in Python research projects is best achieved using a structured review checklist. This automated approach evaluates Python notebooks and scripts to produce a formatted assessment report on methodological concerns.

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