Agent skill · software engineering · aiskillstore
airflow-dag-patterns
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.
Why this skill is useful
Provides specific patterns and best practices for building production-ready Apache Airflow DAGs that the AI wouldn't reliably generate on its own.
What it needs
Requires apache-airflow installed locally. About 6k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
Apache Airflow DAG Patterns Production-ready patterns for Apache Airflow including DAG design, operators, sensors, testing, and deployment strategies. When to Use This Skill 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 Core Concepts 1. DAG Design Principles 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 2. Task Dependencies Quick Start Patterns Pattern 1: TaskFlow API (Airflow 2.0+) Pattern 2: Dynamic DAG Generation Pattern 3: Branching and Conditional Logic Pattern 4: Sensors and External Dependencies Pattern 5: Error Handling and Alerts Pattern 6: Testing DAGs Project Structure Best Practices Do's Use TaskFlow API - Cleaner code, automatic XCom Set timeouts - Prevent zombie tasks Use mode='reschedule' - For sensors, free up workers Test DAGs - Unit tests and integration tests Idempotent tasks - Safe to retry Don'ts Don't use dependsonpast=True - Creates bottlenecks Don't hardcode dates - Use {{ ds }} macros Don't use global state - Tasks should be stateless Don't skip catchup blindly - Understand implications Don't put heavy logic in DAG file - Import from modules Resources Airflow Documentation Astronomer Guides TaskFlow API
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/airflow-dag-patterns--7ee20e