Download for MacApple silicon, macOS 14+
Skill

airflow-dag-patterns

@wshobson Updated 2026-08-05

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.

agent-skillsagentic-aiagentsai-agentsanthropicautomationclaude-codeclaude-code-plugins

Install

With your agent

Install OMGSkills skill "wshobson/agents:airflow-dag-patterns" into this agent's normal skills directory: call the OMGSkills MCP get_install_plan tool for your agent and run the script it returns (it installs only the pinned commit and verifies SKILL.md), and stop if MCP or the pin is unavailable. Do not overwrite or change existing skills without asking me.

Manual command

git clone https://github.com/wshobson/agents /tmp/agents && ln -s /tmp/agents/plugins/data-engineering/skills/airflow-dag-patterns ~/.claude/skills/airflow-dag-patterns

From README

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 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 | Task Dependencies Detailed patterns and worked examples Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.