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Master Python asyncio, concurrent programming, and async/await patterns for high-performance applications.
Passed 20 of 22 test cases with the skill, and 20 of 22 without it.
1 fixed19 passed either way1 still failing1 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.
I need a Python implementation of a message processing system where multiple workers generate data and several other workers process that data continuously. Output a fully working code snippet showing how to set up the workers, wait for the generation to finish, and cleanly shut down the processors.
| Checked | Without skill | With skill |
|---|---|---|
| Uses asyncio.Queue for the message queue | Missed | Passed |
| Uses asyncio.create_task to spawn worker coroutines | Missed | Passed |
| Calls queue.join() to wait for all items to be processed | Passed | Passed |
| Calls cancel() on the consumer tasks to shut them down | Missed | Passed |
The instructions your model reads when the skill loads.
Comprehensive guidance for implementing asynchronous Python applications using asyncio, concurrent programming patterns, and async/await for building high-performance, non-blocking systems.
The event loop is the heart of asyncio, managing and scheduling asynchronous tasks.
Key characteristics:
Functions defined with async def that can be paused and resumed.
Syntax:
async def my_coroutine():
result = await some_async_operation()
return result
Scheduled coroutines that run concurrently on the event loop.
test cases passed, vs 20 / 22 without
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