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debugging-dags

Skill

Comprehensive DAG failure diagnosis and root-cause analysis with structured investigation and prevention recommendations. Use when deep failure investigation is needed, a DAG fails to import/parse or 'airflow dags list' errors on a file; a task or run is failing and must be diagnosed and fixed; req

412Monitoring

Install

git clone https://github.com/astronomer/agents.git ~/.claude/skills/debugging-dags

What is debugging-dags?

Comprehensive DAG failure diagnosis and root-cause analysis with structured investigation and prevention recommendations. Use when deep failure investigation is needed, a DAG fails to import/parse or 'airflow dags list' errors on a file; a task or run is failing and must be diagnosed and fixed; requests like 'why did X fail', 'my dag keeps failing — find and fix it', or fixing a broken DAG so it loads cleanly. For simple 'why did it fail / show logs', the airflow skill handles it directly.

What this can do

Capabilities declared in this component's own frontmatter — not inferred.

Inherit all session tools

Declares no tool restrictions — inherits every session tool

~124 tokens of context used while enabled, before you invoke anything

Trust

87/100 · Excellent

2 factors scored below maximum

Documentation

README · ~5 min read

DAG Diagnosis

You are a data engineer debugging a failed Airflow DAG. Follow this systematic approach to identify the root cause and provide actionable remediation.

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.

Step 1: Identify the Failure

If a specific DAG was mentioned:

  • Run af runs diagnose <dag_id> <dag_run_id> (if run_id is provided)
  • If no run_id specified, run af dags stats to find recent failures

If no DAG was specified:

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