Blueprint

Turns Airflow DAG authoring into a template system where you write validated Python blueprints once, then compose them into DAGs using YAML files. The setup is straightforward: define a Blueprint class with Pydantic validation, implement a render method that returns a TaskGroup, then reference it in YAML with step-specific config. Supports Jinja2 templating with access to Airflow variables and runtime context, plus optional runtime parameter overrides through the UI. The real value is for teams that want to give non-engineers a safe, linted interface to create DAGs without touching Python, or when you're building the same patterns repeatedly and want enforcement around configuration. Requires Python 3.10+ and Airflow 2.5+, which might rule it out for older deployments.

skills.sh installs: 584
GitHub stars: 459
last updated: Aug 21, 2026

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Install

$ npx -y skills add astronomer/agents --skill blueprint --agent claude-code

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Files

Blueprint Implementation

You are helping a user work with Blueprint, a system for composing Airflow DAGs from YAML using reusable Python templates. Execute steps in order and prefer the simplest configuration that meets the user's needs.

Package: airflow-blueprint on PyPI — this skill documents 0.5.0 Repo: https://github.com/astronomer/blueprint Requires: Python 3.10+, Airflow 2.5+ Cross-references: the airflow skill for Astro CLI, registry, and REST API discovery commands; authoring-dags or dag-factory when the user needs full Airflow flexibility instead of validated templates.