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python-code-review

Analyze Python source code and pytest suites for PEP8, type safety, and async best practices.

Updated Jul 18, 2026
Search Tags:#type safety#testing#code review#pytest#python#async
One-click install
npx skills add https://github.com/arthrod/conejo-skills --skill python-code-review-arthrod
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: python-code-review
Source: https://github.com/arthrod/conejo-skills/tree/main/skills/python-code-review
Command: npx skills add https://github.com/arthrod/conejo-skills --skill python-code-review-arthrod

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill addresses the common pitfalls in Python development and test infrastructure, ensuring code is type-safe, performant, and follows industry-standard testing patterns.

Core Features & Use Cases

  • Infrastructure Validation: Automatically verifies pytest configuration, including test layout, conftest wiring, and marker registration.
  • Code Quality Enforcement: Analyzes source code for PEP8 compliance, type safety, and async pattern correctness.
  • Test Suite Optimization: Provides guidance on mocking, parametrization, and fixture scoping to ensure robust, maintainable test suites.

Quick Start

Run the python-code-review skill on the current directory to audit your source code and test suite configuration for potential issues.

Frequently Asked Questions about python-code-review

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

FAQPage Schema
How do I automate Python code review for PEP8 and type safety?▼

Automate Python code review by analyzing your source directory to verify PEP8 compliance, type safety, and async best practices. This process evaluates your code infrastructure and enforces clean architectural patterns.

How does pytest test suite optimization work for mocking and fixtures?▼

Pytest test suite optimization analyzes your test configuration to provide guidance on mocking strategies, parametrization, and fixture scoping. This validates your test infrastructure to ensure it remains robust and maintainable.

Can I validate pytest configuration including conftest wiring and markers?▼

Yes, you can validate pytest configuration by analyzing the test layout, conftest wiring, and marker registration. This infrastructure validation automatically verifies that your test suite is correctly configured.

What is async-aware debugging in Python and when do I need it?▼

Async-aware debugging in Python analyzes source code for async pattern correctness to identify performance and safety issues. You need it when building projects requiring robust test infrastructure and proper asynchronous execution.

What are the limitations of automated Python code quality analysis?▼

Automated Python code quality analysis is limited to detecting PEP8 violations, type safety issues, and async pattern correctness. It targets test infrastructure validation but may not catch complex architectural flaws or business logic errors.

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