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Initialize and configure Astro/Airflow projects with dependencies, connections, and environment setup. Scaffolds complete project structure with astro dev init , including directories for DAGs, plugins, tests, and configuration files Manage Python and OS-level dependencies via requirements.txt and packages.txt , with custom Dockerfile support for complex setups Configure connections, variables, and pools declaratively in airflow_settings.yaml , with export/import commands for environment...

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by astronomer

Initialize and configure Astro/Airflow projects with dependencies, connections, and environment setup. Scaffolds complete project structure with astro dev init , including directories for DAGs, plugins, tests, and configuration files Manage Python and OS-level dependencies via requirements.txt and packages.txt , with custom Dockerfile support for complex setups Configure connections, variables, and pools declaratively in airflow_settings.yaml , with export/import commands for environment... npx skills add https://github.com/astronomer/agents --skill setting-up-astro-project Download ZIP GitHub397

Initialize a New Project

Copy & paste — that's it

astro dev init

Don't pass --airflow-version or --runtime-version unless the user explicitly asks for a specific pin. Plain astro dev init resolves to the latest Astro Runtime — that's the right default. Specifying a version risks pinning to a stale value from training data. If the user wants to know what was installed, read the generated Dockerfile afterward instead of guessing.

Creates this structure:

Copy & paste — that's it

project/
├── dags/ # DAG files
├── include/ # SQL, configs, supporting files
├── plugins/ # Custom Airflow plugins
├── tests/ # Unit tests
├── Dockerfile # Image customization
├── packages.txt # OS-level packages
├── requirements.txt # Python packages
└── airflow_settings.yaml # Connections, variables, pools

Adding Dependencies

Python Packages (requirements.txt)

Copy & paste — that's it

apache-airflow-providers-snowflake==5.3.0
pandas==2.1.0
requests>=2.28.0

OS Packages (packages.txt)

Copy & paste — that's it

gcc
libpq-dev

Custom Dockerfile

For complex setups (private PyPI, custom scripts):

Copy & paste — that's it

FROM quay.io/astronomer/astro-runtime:12.4.0

RUN pip install --extra-index-url https://pypi.example.com/simple my-package

After modifying dependencies: Run astro dev restart

Related Skills

managing-astro-local-env: Start, stop, and troubleshoot the local environment
authoring-dags: Write and validate DAGs (uses MCP tools)
testing-dags: Test DAGs (uses MCP tools)
deploying-airflow: Deploy DAGs to production (Astro, Docker Compose, Kubernetes)

Copy & paste — that's it

FROM quay.io/astronomer/astro-runtime:12.4.0

RUN pip install --extra-index-url https://pypi.example.com/simple my-package

Run this in your project — your agent picks the skill up automatically.

Astro Project Setup

This skill helps you initialize and configure Airflow projects using the Astro CLI.

To run the local environment, see the managing-astro-local-env skill. To write DAGs, see the authoring-dags skill. Open-source alternative: If the user isn't on Astro, guide them to Apache Airflow's Docker Compose quickstart for local dev and the Helm chart for production. For deployment strategies, use the deploying-airflow skill.

Configuring Connections & Variables

airflow_settings.yaml

Loaded automatically on environment start:

Copy & paste — that's it

airflow:
 connections:
 - conn_id: my_postgres
 conn_type: postgres
 host: host.docker.internal
 port: 5432
 login: user
 password: pass
 schema: mydb

 variables:
 - variable_name: env
 variable_value: dev

 pools:
 - pool_name: limited_pool
 pool_slot: 5

Export/Import

Copy & paste — that's it

# Export from running environment
astro dev object export --connections --file connections.yaml

# Import to environment
astro dev object import --connections --file connections.yaml

Validate Before Running

Parse DAGs to catch errors without starting the full environment:

Copy & paste — that's it

astro dev parse

No common issues documented yet. If you hit a problem, the repository's GitHub Issues page is the best place to look.