apache-airflow-dag-creator

Scaffold Apache Airflow DAGs with standardized directory layouts and environment-gated scheduling.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/mporenta/airflow --skill apache-airflow-dag-creator
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: apache-airflow-dag-creator
Source: https://github.com/mporenta/airflow/tree/main/.claude/skills/apache-airflow-dag-creator
Command: npx skills add https://github.com/mporenta/airflow --skill apache-airflow-dag-creator

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill guides engineers to quickly scaffold Apache Airflow DAGs that conform to the data-airflow repository's verified conventions, ensuring consistent structure, naming, and callback patterns across pipelines.

Core Features & Use Cases

  • Provides a repeatable directory layout for new DAG projects (dags/<pipeline_name>/src/main.py and daily.py) with a business-logic class for data processing and a ready-to-run DAG file.
  • Enforces environment-gated scheduling, standard default_args, and Slack/Snowflake integration guidance to reduce configuration errors in local, staging, and prod environments.
  • Supports quick-start templates to jumpstart new pipelines, enabling rapid collaboration and standardization across teams.

Quick Start

Create a daily DAG skeleton for a new pipeline named <pipeline> following the standard structure and callback patterns.

Frequently Asked Questions about apache-airflow-dag-creator

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I scaffold an Apache Airflow DAG that follows standard directory conventions?▼

To scaffold an Apache Airflow DAG, this skill automates creating a standardized directory layout like dags/<pipeline>/src/main.py and daily.py, enforcing consistent structure, naming, and callback patterns across pipelines.

How do I configure environment-gated scheduling for Airflow pipelines?▼

Configuring environment-gated scheduling for Airflow pipelines is handled automatically, applying environment-specific gating patterns across development, staging, and production workflows to prevent accidental execution in the wrong environment.

What are the required default args and callback patterns for a new Airflow pipeline?▼

Required default args for a new Airflow pipeline include documented defaults for start_date, retries, and tagging, alongside standard Slack and Snowflake integration guidance to ensure consistent callback patterns and reduce configuration errors.

Can I use this Airflow DAG scaffolder for existing data pipeline repositories?▼

This Airflow DAG scaffolder targets new pipeline work in dags/ and related src structures, applying repository-specific conventions to ensure standardized layouts rather than refactoring pre-existing pipeline files.

Does Airflow DAG scaffolding support Slack and Snowflake integration out of the box?▼

Airflow DAG scaffolding includes Slack and Snowflake integration guidance out of the box, providing ready-to-run DAG templates with standard callback patterns to reduce configuration errors for local, staging, and prod environments.