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Found 23 Skills
Automatically add or improve type annotations in legacy Python code. Use to improve code readability, IDE support, and catch type errors early.
Python type safety with type hints, generics, protocols, and strict type checking. Use when adding type annotations, implementing generic classes, defining structural interfaces, or configuring mypy/pyright.
Idiomatic Python 3.14+ development. Use when writing Python code, CLI tools, scripts, or services. Emphasizes stdlib, type hints, uv/ruff toolchain, and minimal dependencies.
Provides Python patterns for type-first development with dataclasses, discriminated unions, NewType, and Protocol. Must use when reading or writing Python files.
Pythonic idioms, PEP 8 standards, type hints, and best practices for building robust, efficient, and maintainable Python applications.
Senior Python developer expertise for writing clean, efficient, and well-documented code. Use when: writing Python code, optimizing Python scripts, reviewing Python code for best practices, debugging Python issues, implementing type hints, or when user mentions Python, PEP 8, or needs help with Python data structures and algorithms.
Python development principles and decision-making. Framework selection, async patterns, type hints, project structure. Teaches thinking, not copying.
Expert-level Python development with Python 3.12+ features, async/await, type hints, and modern best practices
Python data validation using type hints and runtime type checking with Pydantic v2's Rust-powered core for high-performance validation in FastAPI, Django, and configuration management.
Python Coding Standards, including type hints, logging specifications, naming conventions, code structure, etc. Applicable to all Python code files.
Core Python development concepts, idioms, best practices, and language features. Covers Python 3.10+ features, type hints, async/await, and Pythonic patterns. For running scripts, see uv-run. For project setup, see uv-project-management. Use when user mentions Python, type hints, async Python, decorators, context managers, or writing Pythonic code.
Use when defining or evolving public interfaces, schema boundaries, or pydantic usage in Python. Also use when annotations are missing on public APIs, pydantic models appear everywhere instead of at trust boundaries, contract changes lack migration guidance, or Any/object types are overused across module boundaries.