Best Claude Skills for Python

Quick reference for ADK Python patterns: agents, tools, callbacks, and state management.

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Comprehensive testing strategies for Python using pytest, fixtures, mocking, and test-driven development.

Profile and optimize Python code using cProfile, memory profilers, and performance best practices.

Universal release workflow. Auto-detects version files and changelogs. Supports Node.js, Python, Rust, Claude Plugin, GitHub Releases, annotated tags, historical release backfill, and generic projects. Use when user says "release", "发布", "new version", "bump version", "push", "推送", "release notes", "GitHub Release", or "回填 Release".

Production-ready FastAPI project structure with async patterns, dependency injection, and layered architecture.

python executor

Build applications with Google's Gemini models, supporting multimodal content, function calling, and structured outputs across Python, JavaScript, Go, and Java.

Comprehensive error handling patterns across Python, TypeScript, Rust, and Go with language-specific implementations.

Fundamental design principles for writing maintainable, testable Python code.

Comprehensive guide to asyncio, concurrent patterns, and async/await for building high-performance, non-blocking Python applications.

Python code style, linting, formatting, naming conventions, and documentation standards. Use when writing new code, reviewing style, configuring linters, writing docstrings, or establishing project standards.

Ultra-fast Python package installer and resolver written in Rust, 10-100x faster than pip.

Python project organization, module architecture, and public API design. Use when setting up new projects, organizing modules, defining public interfaces with __all__, or planning directory layouts.

Expert guidance for building high-performance FastAPI APIs with async best practices and clean Python patterns.

Python error handling patterns including input validation, exception hierarchies, and partial failure handling. Use when implementing validation logic, designing exception strategies, handling batch processing failures, or building robust APIs.

Run pytest with coverage reporting to identify and eliminate untested code lines.

Use this skill when reviewing Python code for common anti-patterns to avoid. Use as a checklist when reviewing code, before finalizing implementations, or when debugging issues that might stem from known bad practices.

python-executor

Create distributable Python packages with proper project structure, setup.py/pyproject.toml, and publishing to PyPI. Use when packaging Python libraries, creating CLI tools, or distributing Python code.

python-sdk

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.

Python resilience patterns including automatic retries, exponential backoff, timeouts, and fault-tolerant decorators. Use when adding retry logic, implementing timeouts, building fault-tolerant services, or handling transient failures.

Python observability patterns including structured logging, metrics, and distributed tracing. Use when adding logging, implementing metrics collection, setting up tracing, or debugging production systems.