# dag-factory

> Claude/Codex skill by [@astronomer](https://omgskills.com/library/astronomer/index.md) · 454 stars · Updated 2026-10-14

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.

Tags: agentic-workflow, agents, ai, ai-agents, airflow, apache-airflow, claude, cursor, dag, data-engineering, data-pipelines, dbt, llm, mcp, orchestrator, skills, workflow-automation, workflow-management, workflow-orchestration, workflows

## Install

```sh
git clone https://github.com/astronomer/agents /tmp/agents && ln -s /tmp/agents/skills/dag-factory ~/.claude/skills/dag-factory
```

## From README

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: Airflow version ≥2.4 Python version ≥3.10 dag-factory version: this skill targets v1.0+. If the project is on Note: loader argument names and several other field names changed in v1.0.0. See reference/migration.md if you're working on an older project.

## Links

- HTML page: https://omgskills.com/skills/astronomer/agents/dag-factory/
- GitHub: https://github.com/astronomer/agents
- Author: [@astronomer](https://omgskills.com/library/astronomer/index.md)

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