Airflow dag patterns
Skill ComeOnOliver/skillshub/skills/rmyndharis/antigravity-skills/airflow-dag-patterns
🧠The right skill, one API call. AI agent skills registry with token-efficient skill resolution. 5,000+ skills from 500+ top repos.From the repository description
npx -y skills add ComeOnOliver/skillshub --skill airflow-dag-patternsAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
SKILL.md
1.2 KB, 242 tokens by cl100k_base, as published. Nobody here has run it
Apache Airflow DAG Patterns
Production-ready patterns for Apache Airflow including DAG design, operators, sensors, testing, and deployment strategies.
Use this skill when
- Creating data pipeline orchestration with Airflow
- Designing DAG structures and dependencies
- Implementing custom operators and sensors
- Testing Airflow DAGs locally
- Setting up Airflow in production
- Debugging failed DAG runs
Do not use this skill when
- You only need a simple cron job or shell script
- Airflow is not part of the tooling stack
- The task is unrelated to workflow orchestration
Instructions
- Identify data sources, schedules, and dependencies.
- Design idempotent tasks with clear ownership and retries.
- Implement DAGs with observability and alerting hooks.
- Validate in staging and document operational runbooks.
Refer to resources/implementation-playbook.md for detailed patterns, checklists, and templates.
Safety
- Avoid changing production DAG schedules without approval.
- Test backfills and retries carefully to prevent data duplication.
Resources
resources/implementation-playbook.mdfor detailed patterns, checklists, and templates.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.