astronomer-data-agents

Q: How to install astronomer-data-agents?

Create the agents directory: mkdir -p .claude/agents. Then add the config to .claude/agents/astronomer-data-agents.md. Finally, @astronomer-data-agents in Claude Code.

Q: What is astronomer-data-agents best for?

astronomer-data-agents is categorized under Development. It covers: deployment, agent.

389Official PluginDevelopmentby Anthropic

Data engineering for Apache Airflow and Astronomer. Author DAGs with best practices, debug pipeline failures, trace data lineage, profile tables, migrate Airflow 2 to 3, and manage local and cloud deployments.

Python53 forks15 issuesUpdated 6/15/2026First seen 4/17/2026

Summary

This skill integrates data engineering best practices for Apache Airflow and Astronomer directly into Claude Code.

It helps you author DAGs with proper structure, debug pipeline failures, trace data lineage, profile tables, migrate from Airflow 2 to 3, and manage both local and cloud deployments, saving time and reducing errors.

Install & Usage

Create the agents directory

mkdir -p .claude/agents

Save the agent file

Add the configuration to .claude/agents/astronomer-data-agents.md

Invoke with @agent-name

@astronomer-data-agents

Use Cases

Author a new DAG with best practices for task dependencies, retries, and scheduling.

Debug a failed Airflow task by analyzing logs and suggesting fixes.

Trace data lineage across a pipeline to identify upstream or downstream impacts.

Profile a table in your data warehouse to understand schema, nulls, and distributions.

Migrate an Airflow 2 DAG to Airflow 3 syntax and operators.

Deploy a DAG to an Astronomer cloud environment from a local development setup.

Usage Examples

/astronomer-data-agents create a DAG that runs a SQL query daily and sends an email with results

Debug the failure in my Airflow DAG 'etl_pipeline' task 'load_data' from yesterday's run

Trace lineage for table 'orders' in our Snowflake warehouse back to source systems

View source on GitHub

deploymentagentagentic-workflowagentsaiai-agentsairflowapache-airflowclaudecursordagdata-engineeringdata-pipelinesdbtllmmcporchestratorskillsworkflow-automationworkflow-managementworkflow-orchestrationworkflows

Security Audits

LicenseUnknownSourcePassRepositoryPass

Frequently Asked Questions

What is astronomer-data-agents?

This skill integrates data engineering best practices for Apache Airflow and Astronomer directly into Claude Code. It helps you author DAGs with proper structure, debug pipeline failures, trace data lineage, profile tables, migrate from Airflow 2 to 3, and manage both local and cloud deployments, saving time and reducing errors.

How to install astronomer-data-agents?

To install astronomer-data-agents: create the agents directory (mkdir -p .claude/agents), then add the config to .claude/agents/astronomer-data-agents.md. Finally, @astronomer-data-agents in Claude Code.

What is astronomer-data-agents best for?

astronomer-data-agents is a agent categorized under Development. It is designed for: deployment, agent. Created by Anthropic.

What can I use astronomer-data-agents for?

astronomer-data-agents is useful for: Author a new DAG with best practices for task dependencies, retries, and scheduling.; Debug a failed Airflow task by analyzing logs and suggesting fixes.; Trace data lineage across a pipeline to identify upstream or downstream impacts.; Profile a table in your data warehouse to understand schema, nulls, and distributions.; Migrate an Airflow 2 DAG to Airflow 3 syntax and operators.; Deploy a DAG to an Astronomer cloud environment from a local development setup..