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python-code-review

Evaluate Python code for style, type annotations, tests, and performance.

2|Updated Mar 27, 2026
Search Tags:#testing#code review#linting#best practices#python#type checking#ruff
One-click install
npx skills add https://github.com/zengbin93/python_coding_skills --skill python-code-review-zengbin93
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: python-code-review
Source: https://github.com/zengbin93/python_coding_skills/tree/main/skills/python-code-review
Command: npx skills add https://github.com/zengbin93/python_coding_skills --skill python-code-review-zengbin93

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a structured, repeatable process to detect and document Python code quality issues before merging changes, reducing regressions and maintenance costs by focusing on style, typing, tests, readability, and performance.

Core Features & Use Cases

  • Comprehensive Checklist: Covers type annotations, naming, docstrings, linting, testing coverage, complexity, duplication, and common performance pitfalls.
  • Actionable Findings: Produces locations, suggested fixes, and prioritization including blocking issues for merge decisions.
  • Tool Integration & Commands: Recommends and references commands to run ruff formatting/linting and basedpyright type checks as part of CI or local review workflows.
  • Use Case: Run this Skill during a pull request review to generate a review summary that lists style violations, missing type hints, test gaps, and concrete remediation steps.

Quick Start

Review the changes in src/processor.py and produce a concise code review highlighting missing type annotations, linting errors, test gaps, complexity issues, and suggested fixes.

Frequently Asked Questions about python-code-review

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

FAQPage Schema
How do I review Python code for quality and best practices in a pull request?▼

Review Python code by evaluating adherence to style, type annotations, tests, readability, and performance. This produces a checklist of violations, suggested fixes with file locations, testing coverage gaps, and commands to run ruff and basedpyright.

What is the best way to check Python type annotations and linting errors before merging?▼

Check Python type annotations and linting errors by running ruff for formatting and linting alongside basedpyright for type checking. This identifies blocking issues and provides concrete remediation steps to ensure code meets repository quality standards.

How do I find missing type hints and test coverage gaps in my Python code?▼

Find missing type hints and test coverage gaps by applying a structured code review checklist focused on type annotations and testing coverage. This yields a prioritized list of actionable findings with file locations and suggested fixes.

Does the Python code review process work with ruff and basedpyright?▼

Yes, the Python code review process works with ruff and basedpyright by integrating their commands into CI or local workflows. It references these tools to validate linting, formatting, and type checking results during the review.

Can I automate pre-commit Python code checks for complexity and duplication?▼

You can automate pre-commit Python code checks by applying a comprehensive review checklist covering complexity, duplication, and common performance pitfalls. This generates a review summary with violations and suggested fixes to prevent regressions before merging.

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