Testing Dags

This handles the full test-debug-fix loop for Airflow DAGs when you need more than a simple test run. The approach is refreshingly direct: just trigger the DAG first with `af runs trigger-wait`, then debug only if it fails. No pre-flight checks, no validation theater. When things break, `af runs diagnose` gives you the full picture in one call, and `af tasks logs` gets you the actual error messages. It's built for iterative workflows where you're bouncing between code changes and test runs until the pipeline works. The workflow diagrams and phase breakdown make it easy to figure out which command you actually need instead of guessing.

skills.sh installs: 1.2K
GitHub stars: 459
last updated: Aug 21, 2026

View on GitHub

Install

$ npx -y skills add astronomer/agents --skill testing-dags --agent claude-code

Installs into .claude/skills of the current project.

Files

DAG Testing Skill

Use af commands to test, debug, and fix DAGs in iterative cycles.

Running the CLI

These commands assume af is on PATH. Run via astro otto to get it automatically, or install standalone with uv tool install astro-airflow-mcp.

Quick Validation with Astro CLI

If the user has the Astro CLI available, these commands provide fast feedback without needing a running Airflow instance:

# Parse DAGs to catch import errors, syntax issues, and DAG-level problems
astro dev parse

# Run pytest against DAGs (runs tests in tests/ directory)
astro dev pytest

Use these for quick validation during development. For full end-to-end testing against a live Airflow instance, continue to the trigger-and-wait workflow below.