airflow-dag-patterns SKILL.md skillA

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airflow-dag-patterns from rudycity/superagent is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

mdr add rudycity/superagent/airflow-dag-patterns@git:20260626.019dba9

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Kind

SKILL.md skill

Repository

rudycity/superagent

Path

.agents/skills/airflow-dag-patterns/SKILL.md

Versions recorded

1

Latest version

git:20260626.019dba9, committed Jun 26, 2026

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64

License

MIT

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.

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# 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

```python
# Linear
task1 >> task2 >> task3

# Fan-out
task1 >> [task2, task3, task4]

# Fan-in
[task1, task2, task3] >> task4

# Complex
task1 >> task2 >> task4
task1 >> task3 >> task4
```

## Quick Start

```python
# dags/example_dag.py
from datetime import datetime, timedelta
from airflow import DAG
from airflow.operators.python import PythonOperator
…

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How to install

mdr add rudycity/superagent/airflow-dag-patterns@sha256:99cf58e6d32b977e

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Versions

The registry has recorded 1 version of this file, committed on Jun 26, 2026.

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Source

API

GET https://markdownregistry.com/api/v1/artifacts/art_yfycuxc66ljwitrb
GET https://markdownregistry.com/api/v1/resolve?ref=rudycity/superagent/airflow-dag-patterns
GET https://markdownregistry.com/api/v1/blob/99cf58e6d32b977e02a9c7ae2ed0ae4894e24ece95260134ac22925497c2a732

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Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

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