How is data validation handled?

The skill enforces the use of Pydantic for data models and configuration management to ensure strict type safety and runtime validation.

What tools are used for code quality?

It implements Ruff for linting and Black for formatting, along with Pytest and Mypy for testing and static type analysis.

Does it support Model Context Protocol (MCP)?

Yes, it includes specific patterns and boilerplate code for building MCP servers, including tool definitions and server setup.

Which Python version does this skill focus on?

This skill is designed for Python 3.11 and later, ensuring developers can leverage modern features like advanced type hinting and optimized asyncio.

Python Development Standards

Name: Python Development Standards
Author: violetio

byvioletio

API 开发

Provides standardized Python conventions and implementation patterns for building high-quality SDKs and Model Context Protocol servers.

关于

This skill equips Claude with modern Python 3.11+ development best practices, emphasizing robust type safety via Pydantic and efficient concurrency through asyncio. It streamlines the creation of SDKs and Model Context Protocol (MCP) servers by providing pre-defined project structures, specialized error handling patterns, and comprehensive testing configurations. Whether building backend APIs with FastAPI or specialized AI integrations, this skill ensures code consistency, performance, and maintainability across the entire Python ecosystem.

主要功能

Python 3.11+ async/await implementation patterns
Model Context Protocol (MCP) server boilerplate and tools
0 GitHub stars
Strong type validation with Pydantic and Pydantic Settings
Automated linting and formatting standards using Ruff and Black
Pre-configured project structures for services and APIs

使用场景

Standardizing Python SDK development across enterprise teams
Building production-grade MCP servers for AI tool integrations
Implementing robust error handling and logging in async backends

关于

主要功能

Python 3.11+ async/await implementation patterns
Model Context Protocol (MCP) server boilerplate and tools
0 GitHub stars
Strong type validation with Pydantic and Pydantic Settings
Automated linting and formatting standards using Ruff and Black
Pre-configured project structures for services and APIs

使用场景

Standardizing Python SDK development across enterprise teams
Building production-grade MCP servers for AI tool integrations
Implementing robust error handling and logging in async backends