Setting Up Astro Project

Organization

astronomer

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.

Overview

Publisher	astronomer
Repository	`agents`
Skill name	`setting-up-astro-project`
Stars	455
Forks	71
Bundled files	Instructions only
License	Apache-2.0
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by astronomer on GitHub. Read the source before you install it.

Installation

Install the Setting Up Astro Project AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/astronomer/agents/tree/main/skills/setting-up-astro-project
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/astronomer/agents.git /tmp/agents
mkdir -p .claude/skills
cp -r /tmp/agents/skills/setting-up-astro-project .claude/skills/setting-up-astro-project

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Setting Up Astro Project in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Setting Up Astro Project on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Setting Up Astro Project is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

bash
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):

dockerfile
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:

yaml
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

bash
# 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:

bash
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)

Frequently asked questions

What does the Setting Up Astro Project AI skill do?

Why use Setting Up Astro Project on TypingMind?

Because you install it once and use it with any model. Setting Up Astro Project is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Setting Up Astro Project in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/astronomer/agents/tree/main/skills/setting-up-astro-project. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Setting Up Astro Project?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Setting Up Astro Project?

As many as you like. As long as a model supports skills, you can use Setting Up Astro Project with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Setting Up Astro Project AI skill free?

Yes. It is published on GitHub by astronomer under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Astro Project Setup

Initialize a New Project

Adding Dependencies

Python Packages (requirements.txt)

OS Packages (packages.txt)

Custom Dockerfile

Configuring Connections & Variables

airflow_settings.yaml

Export/Import

Validate Before Running

Related Skills

Frequently asked questions

Related AI Skills

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