ClaudeSuperPower
SubmitLog in

dag-factory

Skill

Authors Apache Airflow DAGs declaratively from dag-factory YAML configs. Use when building DAGs declaratively from YAML via dag-factory; creating/editing dag-factory templates/YAML configs,reating/editing dag-factory YAML configs, defaults, dynamic tasks, datasets, or callbacks; or validating dag-fa

412Machine Learning

Install

git clone https://github.com/astronomer/agents.git ~/.claude/skills/dag-factory

What is dag-factory?

Authors Apache Airflow DAGs declaratively from dag-factory YAML configs. Use when building DAGs declaratively from YAML via dag-factory; creating/editing dag-factory templates/YAML configs,reating/editing dag-factory YAML configs, defaults, dynamic tasks, datasets, or callbacks; or validating dag-factory configurations; upgrading or re-pinning dag-factory.

What this can do

Capabilities declared in this component's own frontmatter — not inferred.

Inherit all session tools

Declares no tool restrictions — inherits every session tool

~90 tokens of context used while enabled, before you invoke anything

Trust

87/100 · Excellent

2 factors scored below maximum

Documentation

README · ~9 min read

DAG Factory

You are helping a user build Apache Airflow DAGs declaratively with dag-factory, a library that turns YAML configuration files into Airflow DAGs. Execute steps in order and prefer the simplest configuration that meets the user's needs.

Package: dag-factory on PyPI Repo: https://github.com/astronomer/dag-factory Docs: https://astronomer.github.io/dag-factory/latest/ Targets: dag-factory v1.0+ only. For pre-1.0 projects, see reference/migration.md before applying any guidance from this skill. Requires: Python 3.10+, Airflow 2.4+ (Airflow 3 supported)

Before Starting

Confirm with the user:

  1. Airflow version ≥2.4

Reviews

Log in to leave a review.

No reviews yet — be the first.

Explore related

Other things in this space — across every part of the ecosystem, not just skills.