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Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment.
Passed 21 of 22 test cases with the skill, and 20 of 22 without it.
1 fixed20 passed either way1 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.
When exponential backoff is enabled on retries, what default parameter prevents the delay between retries from growing indefinitely?
| Checked | Without skill | With skill |
|---|---|---|
| The parameter max_retry_delay is configured in default_args. | Missed | Passed |
The instructions your model reads when the skill loads.
Production-ready patterns for Apache Airflow including DAG design, operators, sensors, testing, and deployment strategies.
| Principle | Description |
|---|---|
| Idempotent | Running twice produces same result |
| Atomic | Tasks succeed or fail completely |
| Incremental | Process only new/changed data |
| Observable | Logs, metrics, alerts at every step |
# Linear
task1 >> task2 >> task3
# Fan-out
task1 >> [task2, task3, task4]
# Fan-in
[task1, task2, task3] >> task4
# Complex
task1 >> task2 >> task4
task1 >> task3 >> task4
test cases passed, vs 20 / 22 without
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