/setting-up-astro-project
Initialize and configure Astro/Airflow projects. Use when the user wants to create a new project, set up dependencies, configure connections/variables, or understand project structure. For running the local environment, see managing-astro-local-env.
$ npx -y skills add astronomer/agents --skill setting-up-astro-project --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/setting-up-astro-project
Context preview
The summary Claude sees to decide when to auto-load this skill.
Initialize and configure Astro/Airflow projects. Use when the user wants to create a new project, set up dependencies, configure connections/variables, or understand project structure. For running the local environment, see managing-astro-local-env.
SKILL.md
setting-up-astro-project.SKILL.mdname: setting-up-astro-project
description: Initialize and configure Astro/Airflow projects. Use when the user wants to create a new project, set up dependencies, configure connections/variables, or understand project structure. For running the local environment, see managing-astro-local-env.
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.
---
Initialize a New Project
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:
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)
apache-airflow-providers-snowflake==5.3.0
pandas==2.1.0
requests>=2.28.0
OS Packages (packages.txt)
gcc
libpq-dev
Custom Dockerfile
For complex setups (private PyPI, custom scripts):
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`
---
Configuring Connections & Variables
airflow_settings.yaml
Loaded automatically on environment start:
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: 5Export/Import
# 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:
astro dev parse
---
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)
Read more
name: setting-up-astro-project description: Initialize and configure Astro/Airflow projects. Use when the user wants to create a new project, set up dependencies, configure connections/variables, or understand project structure. For running the local environment, see managing-astro-local-env.
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.
---
Initialize a New Project
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:
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)
apache-airflow-providers-snowflake==5.3.0 pandas==2.1.0 requests>=2.28.0
OS Packages (packages.txt)
gcc libpq-dev
Custom Dockerfile
For complex setups (private PyPI, custom scripts):
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`
---
Configuring Connections & Variables
airflow_settings.yaml
Loaded automatically on environment start:
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: 5Export/Import
# 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:
astro dev parse
---
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)
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