How does it handle the 'Any' type?

The skill follows a philosophy of 'Never use Any.' It actively works to replace Any with specific types, Protocols, or Generics to ensure maximum type safety.

Can it help me fix 'Incompatible types' errors?

Absolutely. It is specifically designed to interpret error messages from pyright and mypy and provide the correct annotations or type casts to resolve them.

Does this skill support modern Python syntax?

Yes, it prioritizes Python 3.9+ syntax, such as using list[str] instead of typing.List[str] for cleaner and more modern code.

Why does it prefer Pydantic over dataclasses?

Pydantic is preferred for its robust runtime validation and superior integration with static type checkers, ensuring that data structures remain valid throughout the application lifecycle.

Python Type Safety & Pydantic

Name: Python Type Safety & Pydantic
Author: gigaverse-app

bygigaverse-app

API開発

Enforces strict type annotations and Pydantic best practices for robust, error-free Python development.

概要

The pythonista-typing skill empowers Claude to implement modern Python type hinting standards and Pydantic data modeling. It focuses on eliminating type errors, replacing weak types like 'Any' or raw dictionaries with structured models, and ensuring compatibility with static analysis tools like pyright and mypy. By following a 'Type-First' philosophy, this skill helps developers build maintainable codebases where data structures are clearly defined, validated, and documented through code, significantly reducing runtime bugs and improving developer experience.

主な機能

Optimization of complex return types into readable, named Pydantic models
Implementation of structural subtyping using Protocols instead of hasattr checks
0 GitHub stars
Automated error resolution for pyright, basedpyright, and mypy type checkers
Strict type annotation enforcement using modern Python 3.9+ syntax
Seamless conversion of raw dictionaries and TypedDicts into Pydantic models

ユースケース

Designing robust API data structures and schemas using Pydantic BaseModel
Resolving complex type checker errors in CI/CD pipelines using pyright or mypy
Refactoring untyped legacy Python code into a strictly typed, modern codebase

概要

主な機能

Optimization of complex return types into readable, named Pydantic models
Implementation of structural subtyping using Protocols instead of hasattr checks
0 GitHub stars
Automated error resolution for pyright, basedpyright, and mypy type checkers
Strict type annotation enforcement using modern Python 3.9+ syntax
Seamless conversion of raw dictionaries and TypedDicts into Pydantic models

ユースケース

Designing robust API data structures and schemas using Pydantic BaseModel
Resolving complex type checker errors in CI/CD pipelines using pyright or mypy
Refactoring untyped legacy Python code into a strictly typed, modern codebase