How does it handle type checking recommendations?

The skill flags markers of 'type deficiency' such as the use of Any, raw dicts, or hasattr(), suggesting better alternatives like Protocols and Type Hints.

Can I use different AI models for the review?

The included scripts support multiple models like Claude 3 Opus, Sonnet, and GPT-4 Turbo to provide different perspectives on the same diff.

What is the primary focus of this code review skill?

It focuses on egregious structural issues like code duplication, God functions, and weak typing, rather than minor stylistic issues like line length or naming.

Does it automatically change my code?

No. The skill is designed to present findings and a list of suggested actions, then wait for your explicit approval before executing any changes or creating TODOs.

Does it support large Pull Requests?

Yes, it includes specialized scripts to filter out lock files (uv.lock, poetry.lock) and documentation to ensure the core logic fits within the LLM context window.

Pythonista Code Reviewer

Name: Pythonista Code Reviewer
Author: gigaverse-app

bygigaverse-app

Collaboration Tools

Performs high-level Python code reviews focused on architectural integrity, structural patterns, and type safety.

About

The pythonista-reviewing skill empowers Claude to act as a senior Python architect during the code review process. Unlike standard linters, it focuses on 'egregious' structural issues such as massive code duplication, God functions over 100 lines, and weak type annotations while intentionally ignoring minor stylistic nitpicks. It provides a standardized framework for reviewing at the Pull Request level, including utility scripts for diff extraction and a structured post-review workflow that ensures every suggested fix is explicitly approved by the developer.

Key Features

Enforces strong typing by flagging Any types and 'hasattr' patterns in favor of Protocols.
Standardized post-review action lists with explicit approval gates.
Provides automated scripts for LLM-powered PR analysis using diverse models.
Identifies structural anti-patterns like God functions and massive code duplication.
0 GitHub stars
Filters out noise by excluding lock files and documentation from code diffs.

Use Cases

Automating the first pass of Pull Request reviews to catch architectural debt.
Ensuring consistent interface design across large-scale Python projects.
Modernizing legacy Python codebases by identifying logic that lacks type safety.

About

Key Features

Enforces strong typing by flagging Any types and 'hasattr' patterns in favor of Protocols.
Standardized post-review action lists with explicit approval gates.
Provides automated scripts for LLM-powered PR analysis using diverse models.
Identifies structural anti-patterns like God functions and massive code duplication.
0 GitHub stars
Filters out noise by excluding lock files and documentation from code diffs.

Use Cases

Automating the first pass of Pull Request reviews to catch architectural debt.
Ensuring consistent interface design across large-scale Python projects.
Modernizing legacy Python codebases by identifying logic that lacks type safety.