Agent skill · google
managed-airflow-dag-troubleshooting
Provides guidance for troubleshooting Apache Airflow DAGs (failed DAG runs and task instances) in Managed Service for Apache Airflow (MSAA; formerly Cloud Composer). Use when figuring out reasons for DAG run or task instance failures. Don't use when looking for overall recommendations for Managed Airflow environment performance.
What it needs
About 8k tokens when loaded.
What this skill does
Managed Service for Apache Airflow (formerly Cloud Composer) DAG troubleshooting guide This skill provides instructions for troubleshooting Managed Airflow DAGs (DAG runs and task instances), utilizing gcloud composer, gcloud logging and gcloud storage commands to fetch remote logs and code. General rules 1. Provide suggestions on how to troubleshoot the failed jobs. Provide only the steps that the user can actually take. Ground all troubleshooting advice in direct findings. 2. When troubleshooting a failure, follow the following practices to always provide a deterministic diagnosis: Fetch relevant logs: Always fetch the logs for a task under investigation using gcloud logging read; check the logs for specific error patterns: Python tracebacks, API error codes (e.g., 400, 403, 404, 500), or Airflow signals (e.g., AirflowTaskTimeout). Fetch task metadata: When troubleshooting a task, fetch the task state and metadata (execution state, try number, timestamps, and execution details) using: or for an individual task instance: Retrieve and compare DAG source code: Download the remote DAG source code using gcloud storage cp gs://{bucketname}/dags/{dagfile}.py . (find the environment bucket via gcloud composer environments describe {envname} --location {location} --format="value(config.dagGcsPrefix)"). Compare the parameters in the code (e.g., table IDs, disk sizes, URI paths) against the error messages found in the task logs. Explain code mistakes and potential fixes: Explain mistakes in the code (if any are actually visible); suggest potential fixes (if they are very likely to be meaningful); discuss source code availability if needed - if some source code is unavailable (e.g. imported from a file other than the main source code file), mention this (you can mention the package name) - in such a case take into account most likely trigger rules if they are unknown. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills google/managed-airflow-dag-troubleshooting