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Create production-ready FastAPI projects with async patterns, dependency injection, and comprehensive error handling.
Passed 5 of 23 test cases with the skill, and 4 of 23 without it.
1 fixed4 passed either way18 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
A test case the skill fixed. Same model, same prompt, with and without the skill.
How should I package my async FastAPI app for production deployment in Docker? I plan to run python main.py using the standard built-in WSGI server.
| Checked | Without skill | With skill |
|---|---|---|
| The response recommends an ASGI server for containerized deployment. | Passed | Passed |
| The response includes verification steps to validate container deployment. | Missed | Passed |
The instructions your model reads when the skill loads.
Production-ready FastAPI project structures with async patterns, dependency injection, middleware, and best practices for building high-performance APIs.
resources/implementation-playbook.md.resources/implementation-playbook.md for detailed patterns and examples.test cases passed, vs 4 / 23 without
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