Fastapi Code Review

The fastapi-code-review skill enables AI agents to automatically analyze FastAPI application code for security vulnerabilities, performance bottlenecks, and adherence to best practices. It provides detailed feedback on dependency injection patterns, route definitions, and data validation logic within Python-based APIs.

When to use it

• Before deploying a new API endpoint to production to catch critical errors early.
• During the development phase to ensure consistent coding standards across a team.
• When refactoring legacy FastAPI codebases to modernize architecture and improve maintainability.
• To validate that input data validation schemas are correctly implemented for security.

Key capabilities

• Automated static analysis of FastAPI source files.
• Identification of common security flaws such as injection vulnerabilities.
• Detection of performance issues in route handlers and dependencies.
• Verification of proper use of Pydantic models for data validation.
• Suggestions for improving error handling and response structures.

Example prompts

• "Review this FastAPI router file for potential security risks and suggest fixes."
• "Analyze the following code snippet for performance bottlenecks in database queries."
• "Check if my dependency injection setup follows FastAPI best practices."

Tips & gotchas

Ensure your codebase is fully written in Python before running the analysis, as the tool relies on parsing Python syntax. While effective at catching common issues, complex architectural decisions may still require human judgment to interpret context-specific trade-offs.