---
name: strict-mypy
description: Enforces strict MyPy type checking conventions matching the project's pyproject.toml configuration. Use whenever writing or modifying Python code.
---
# Strict MyPy Typing Standards

This project uses a highly strict MyPy configuration (`strict = true`). When writing or refactoring Python code, you MUST adhere to the following rules to ensure the code passes type checking:

## 1. Absolute Signature Completeness
- EVERY function and method must have fully typed arguments and a return type (`disallow_untyped_defs`, `disallow_incomplete_defs`).
- ALWAYS specify `-> None` for functions and methods that do not return a value.
- NEVER leave type hints partially defined (e.g., typing only some arguments).
- Decorators must be completely type-hinted using `typing.Callable` or `typing.ParamSpec` (`disallow_untyped_decorators`).

## 2. No Implicit Optionals
- `arg: str = None` is strictly forbidden.
- You MUST explicitly union with None: `arg: str | None = None` (`no_implicit_optional`).

## 3. Strict Generics
- NEVER use bare collections as types.
- ALWAYS specify the inner types: use `list[str]`, `dict[str, int]`, or `tuple[int, ...]` instead of bare `list`, `dict`, or `tuple` (`disallow_any_generics`).

## 4. Restrictions on `Any` and Subclassing
- Do not subclass from untyped external libraries or `Any` (`disallow_subclassing_any`).
- Avoid using external types that have no stubs and resolve to `Any` (`disallow_any_unimported`).
- Refrain from returning `Any` to avoid contaminating the type inference of calling functions (`warn_return_any`).

## 5. Pydantic Strictness
- `pydantic.mypy` is active with strict initialization.
- When instantiating Pydantic models, ensure you are passing exactly the expected typed arguments, as extra or untyped arguments will fail type checks (`init_typed = true`, `init_forbid_extra = true`).