Which type checkers are supported by this skill?

The skill is specifically optimized for Pyright and Basedpyright, though the type hinting patterns it implements are generally compatible with Mypy as well.

Does this skill change the runtime behavior of my Python code?

No, one of the core principles of this skill is to ensure that type-checking improvements and annotations do not affect the runtime logic of your application.

Can it help with Pydantic model type errors?

Yes, it includes specific patterns for handling keyword syntax in field defaults and other common Pydantic-related static analysis issues.

How does it handle 'type: ignore' comments?

It treats 'type: ignore' as a last resort, prioritizing proper annotations, fixed return types, or explicit typing.cast() calls for legitimate cases.

What is the recommended workflow after applying type fixes?

The skill recommends a three-step verification process: running the type checker, performing a git diff to check for logic changes, and running your test suite (e.g., pytest).

Python Type Checking Standards

Name: Python Type Checking Standards
Author: gigaverse-app

bygigaverse-app

0•

开发者工具

Implements rigorous type-checking standards and best practices for Python projects using Pyright and Basedpyright.

This skill provides a standardized approach to Python type-checking, enabling Claude to effectively use Pyright or Basedpyright to improve code quality. It guides the model through gradual type adoption, prioritizing proper annotations and explicit type casting over suppressing errors with 'type: ignore' comments. By adhering to strict patterns for Pydantic models, optional parameters, and specific type definitions, it ensures a robust, type-safe codebase without altering runtime logic or introducing regressions.

主要功能

01Strategic implementation of type casting to resolve static analysis conflicts

02Strict avoidance of 'Any' types in favor of specific annotations

03Gradual type checking adoption using Pyright or Basedpyright

04Standardized fixes for common Pydantic and field default errors

05Automated verification workflows to ensure zero runtime behavior changes

060 GitHub stars

使用场景

01Standardizing type annotation patterns across a multi-developer team

02Resolving complex Pyright or Basedpyright errors in Pydantic models

03Migrating a legacy Python codebase to include comprehensive type hints

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add gigaverse-app/skillet type-checking

For use in Claude.ai and ChatGPT

Download Skill