Is this a replacement for a standard linter?

It complements linters like Flake8 or Black by focusing on deep logic, security vectors, and framework-specific architectural patterns that static analysis often misses.

Does it support FastAPI's async features?

Absolutely. It identifies blocking I/O calls within async endpoints and suggests proper asynchronous client implementations to prevent event loop blocking.

Can this skill detect SQL injection in Django?

Yes, it specifically identifies unsafe string formatting in raw queries and recommends parameterized queries or ORM best practices to prevent injection.

How does it improve Celery task performance?

It flags patterns like passing large objects to tasks and suggests passing object IDs instead, alongside recommending proper retry configurations and heartbeats.

Will it help with common Python logic bugs?

Yes, it catches frequent issues such as mutable default arguments, bare except clauses, and late binding in closures that can cause unpredictable behavior.

Python Code Review Patterns

Name: Python Code Review Patterns
Author: jpoutrin

byjpoutrin

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Seguridad y Pruebas

Identifies critical security vulnerabilities, performance anti-patterns, and framework-specific logic bugs during Python code reviews.

Acerca de

This skill equips Claude with advanced Python code review capabilities, focusing on security risks like SQL injection, performance bottlenecks like the N+1 query problem, and common logic errors such as mutable default arguments. It provides specialized knowledge for modern Python frameworks, including Django, FastAPI, and Celery, ensuring that code changes are not only functional but also secure, scalable, and idiomatic. Use this skill to automate the identification of complex bugs that standard linters often miss, specifically during pull request reviews or security audits.

Características Principales

5 GitHub stars
Detects high-risk security flaws like SQL injection and path traversal
Catches subtle Python logic bugs like late binding and mutable defaults
Provides actionable recommendations for asynchronous code optimization
Identifies performance bottlenecks including N+1 queries and blocking I/O
Enforces framework-specific best practices for Django, FastAPI, and Celery

Casos de Uso

Reviewing Pull Requests for Django and FastAPI backend applications
Performing security-focused audits on legacy Python codebases
Optimizing long-running Celery background tasks for better scalability

Acerca de

Características Principales

5 GitHub stars
Detects high-risk security flaws like SQL injection and path traversal
Catches subtle Python logic bugs like late binding and mutable defaults
Provides actionable recommendations for asynchronous code optimization
Identifies performance bottlenecks including N+1 queries and blocking I/O
Enforces framework-specific best practices for Django, FastAPI, and Celery

Casos de Uso

Reviewing Pull Requests for Django and FastAPI backend applications
Performing security-focused audits on legacy Python codebases
Optimizing long-running Celery background tasks for better scalability