python-development

Scaffold Python 3.12+ projects with typing, async patterns, and pytest tests.

Updated Feb 15, 2026
One-click install
npx skills add https://github.com/ricable/mcai --skill python-development-ricable
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: python-development
Source: https://github.com/ricable/mcai/tree/main/.agents/skills/python-development
Command: npx skills add https://github.com/ricable/mcai --skill python-development-ricable

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you design, implement, and maintain modern Python projects without reinventing the same setup patterns for every app. It reduces friction around project structure, typing, async code, API development, and testing so you can move from idea to reliable implementation faster.

Core Features & Use Cases

  • Project scaffolding: Set up clean Python 3.12+ layouts with src-based structure, packaging, and development tooling.
  • API and service development: Build FastAPI services, Django components, and other backend workflows with production-oriented patterns.
  • Async and data workflows: Write efficient asynchronous code for network calls, streaming, automation, and processing pipelines.
  • Testing and quality: Add pytest-based tests, type hints, linting, and maintainable patterns for long-term code health.
  • Use case: Use this Skill when starting a new Python web API, refactoring an automation script, or standardizing a team’s backend conventions.

Quick Start

Ask me to create or improve a modern Python project with strict typing, async-friendly patterns, FastAPI-ready structure, and a test setup.

Frequently Asked Questions about python-development

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I scaffold a modern Python project with async patterns and type hints?

To scaffold a modern Python project, generate a clean src-based directory layout configured for Python 3.12+ environments, complete with strict type hinting, async-ready patterns, and packaging tooling. This establishes a production-ready foundation for backend APIs and automation scripts.

What's the best way to set up a FastAPI project with pytest validation?

The best way to set up a FastAPI project is using production-oriented conventions that integrate pytest-based validation workflows. This approach ensures your API development includes maintainable code patterns, best-practice linting, and type checking from the start.

Does this Python scaffolding approach work for Django components and automation scripts?

Yes, this Python scaffolding approach works for Django components and automation scripts. It applies standardized project organization and testing workflows across backend APIs, data processing jobs, and maintainable application code in Python 3.12+ environments.

How do I structure asynchronous code for data processing pipelines in Python?

To structure asynchronous code for data processing pipelines, apply async-friendly patterns designed for network calls, streaming, and processing jobs. This ensures your Python automation workflows run efficiently while maintaining clean, typed, and testable project organization.

Do I need Python 3.12+ to use modern typing and async conventions?

Yes, you need Python 3.12+ to fully utilize the modern typing and async conventions applied here. The scaffolding enforces best-practice linting, type checking, and packaging standards specifically targeted at Python 3.12+ environments for long-term code health.

Why standardize a team's backend conventions with src-based project layouts?

Standardizing a team's backend conventions with src-based project layouts reduces friction around project structure, typing, and testing. This approach ensures maintainable application code, reliable API development, and consistent quality across FastAPI or Django workflows.