Agent Skills
› rmyndharis/antigravity-skills
› airflow-dag-patterns
airflow-dag-patterns
GitHub提供生产级 Apache Airflow DAG 的最佳实践，涵盖设计、算子、传感器、测试及部署。适用于数据管道编排、工作流调度、自定义组件实现及故障排查，确保任务幂等性与可观测性。
Trigger Scenarios
创建 Airflow DAG
设计数据管道依赖
实现自定义算子或传感器
本地测试 DAG
配置生产环境 Airflow
调试失败的 DAG 运行
Install
npx skills add rmyndharis/antigravity-skills --skill airflow-dag-patterns -g -y
SKILL.md
Frontmatter
{
"name": "airflow-dag-patterns",
"description": "Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs."
}
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.
Version History
- e63f7dd Current 2026-07-05 09:27
