Testing Dags
Validates Astronomer DAGs by executing test workflows and reporting on success, failure, and performance metrics.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add testing-dags npx -- -y @trustedskills/testing-dags
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"testing-dags": {
"command": "npx",
"args": [
"-y",
"@trustedskills/testing-dags"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
The testing-dags skill enables AI agents to test Directed Acyclic Graphs (DAGs) used in workflow automation systems like Apache Airflow. It provides tools for validating DAG structure, detecting errors, and simulating execution paths.
When to use it
- Before deploying a new DAG to ensure it adheres to syntax and logical rules
- To identify potential issues such as circular dependencies or invalid task references
- During continuous integration pipelines to automate DAG validation
Key capabilities
- Validate DAG structure for correctness
- Detect circular dependencies in workflows
- Simulate DAG execution paths for error checking
Example prompts
- "Check if this DAG has any circular dependencies."
- "Validate the syntax and logic of my Airflow DAG."
- "Simulate the execution path of this workflow to find errors."
Tips & gotchas
- Ensure your DAG files are properly formatted before testing.
- This skill works best with DAGs written in Python for systems like Apache Airflow.
Tags
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