fastapi

Name: fastapi
Availability: InStock
Author: bomm79cris

Enforce FastAPI best practices and modern development patterns.

Updated Apr 11, 2026

Search Tags:#best practices #fastapi #python #api development #dependency injection

Ready to run

npx skills add https://github.com/bomm79cris/mcp-cristian --skill fastapi-bomm79cris

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: fastapi
Source: https://github.com/bomm79cris/mcp-cristian/tree/main/.agents/skills/fastapi
Command: npx skills add https://github.com/bomm79cris/mcp-cristian --skill fastapi-bomm79cris

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires fastapi, uvicorn, python-multipart, pydantic, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps streamline FastAPI development by enforcing best practices and conventions, ensuring that your code remains up-to-date with the latest features and patterns.

Core Features & Use Cases

Code Cleanliness: Utilizes Annotated for parameters and dependencies, improving reusability and readability.
Dependency Injection: Implements detailed patterns for dependency injection, including class dependencies and scope handling.
Performance: Provides guidance on serialization, return types, and blocking code to optimize performance.
Use Case: Ideal for developers looking to integrate FastAPI into their projects, maintain a clean codebase, and leverage modern best practices.

Quick Start

Use the fastapi skill to initialize your FastAPI project with best practices.

Frequently Asked Questions about fastapi

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

FAQPage Schema

What are the best practices for FastAPI dependency injection?▼

FastAPI dependency injection best practices utilize the `Annotated` construct for parameters to improve readability and reusability. This approach streamlines class dependencies and scope handling for maintainable Python code.

How do I optimize FastAPI performance and serialization?▼

Optimize FastAPI performance by defining return types, managing serialization, and avoiding blocking code. These modern patterns ensure efficient Python API request handling without bottlenecks.

Does this FastAPI guidance work with Pydantic and Uvicorn?▼

Yes, this FastAPI best practices guidance targets Python environments using Pydantic and Uvicorn. It aligns API development workflows with the latest conventions of these dependencies.

How do I structure a clean FastAPI project with modern conventions?▼

Structure a clean FastAPI project by enforcing modern conventions like `Annotated` dependencies and optimized serialization. This maintains an up-to-date, readable Python codebase leveraging latest features.

What is the best way to handle FastAPI parameters and dependencies?▼

The best way to handle FastAPI parameters and dependencies is using the `Annotated` construct. This modern Python pattern improves code reusability and readability while maintaining strict typing.