Automate Airflow DAG operations and health checks via CLI commands.
npx skills add https://github.com/rory-data/copilot --skill airflow-rory-data
Please help me install this Agent Skill. Skill: airflow Source: https://github.com/rory-data/copilot/tree/main/skills/airflow Command: npx skills add https://github.com/rory-data/copilot --skill airflow-rory-data
Manages and optimizes Apache Airflow operations by provisioning tools to list, test, run, and debug DAGs, inspect logs, verify connections and variables, and monitor system health.
Describe your Airflow task and I will execute the corresponding af commands to manage and diagnose DAGs.
High-intent search queries and answers about installing and using this skill.
To run and debug Airflow DAGs, you can use structured CLI commands to trigger DAGs, inspect task logs, and diagnose pipeline failures. This includes running specific tasks and viewing detailed execution outputs to identify issues.
Checking Airflow pipeline health involves running specific diagnostic commands to list DAGs, verify active runs, and confirm system connections. This provides a clear status overview of your workflow deployments and highlights potential failures.
Yes, you can view Airflow task logs and verify variables using structured CLI commands. The system supports inspecting task outputs, checking connection configurations, and retrieving stored variables to ensure workflows have the correct parameters.
Managing multiple Airflow deployments is best handled through structured CLI commands that apply across environments. You can list DAGs, trigger runs, and perform health checks uniformly, ensuring consistent pipeline operations and monitoring.
An Airflow DAG might fail to trigger due to incorrect connections, missing variables, or task-level errors. You can diagnose this by running specific CLI commands to inspect source code, view task logs, and perform health checks.
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