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testing-dags

Trigger Airflow DAG runs, wait for completion, and retrieve task logs for failure diagnosis.

3|Updated Jul 22, 2025
Search Tags:#debugging#airflow#etl orchestration#task logs#dag testing#astro cli#trigger-wait
One-click install
npx skills add https://github.com/minyeamer/linkmerce --skill testing-dags-minyeamer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: testing-dags
Source: https://github.com/minyeamer/linkmerce/tree/main/.agents/skills/testing-dags
Command: npx skills add https://github.com/minyeamer/linkmerce --skill testing-dags-minyeamer

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It reduces the time you spend diagnosing broken Airflow DAGs by providing a disciplined test-debug-fix loop that starts by running the DAG and then drills into failures only when needed.

Core Features & Use Cases

  • Iterative trigger-and-wait testing: Run a specific DAG run and immediately observe success, failure, or timeout outcomes.
  • Targeted debugging on failure: Diagnose runs, inspect task instance logs, and identify upstream causes when tasks fail.
  • Cycle-based remediation: Apply a fix and retest the same DAG until it succeeds, without wasting time on pre-flight checks.

Use Case: When a DAG fails in staging due to an import issue, missing dependency, connection/credential problem, or a task timeout, use this Skill to trigger the run, pinpoint the failing task and error, then update the DAG and retest.

Quick Start

Ask the AI to test and debug DAG runs by triggering the DAG and, if it fails, retrieving diagnostics and task logs to guide your fix.

Frequently Asked Questions about testing-dags

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I debug a failing Airflow DAG by triggering a run and checking task logs?▼

Debug an Airflow DAG by triggering a run, waiting for completion, and retrieving task instance logs to pinpoint failures. This iterative test-debug-fix loop diagnoses import issues, missing dependencies, or task timeouts before retesting the DAG.

What is the best way to test Airflow DAGs for upstream failure propagation?▼

Testing DAGs for upstream failure propagation involves triggering the DAG run and waiting for the final state. If a task fails, targeted diagnostics identify upstream causes, allowing you to apply a fix and retest without pre-flight checks.

How do I diagnose Airflow task timeouts after a manual DAG trigger?▼

Diagnose Airflow task timeouts by triggering the DAG and waiting for execution to finish. Upon timeout or failure, retrieve diagnostics and task logs to isolate the root cause, apply code fixes, and re-trigger the run to verify resolution.

Can I use Astro CLI to iteratively test and fix DAG load or import failures?▼

You can test and fix DAG load or import failures by triggering the DAG run and observing the outcome. If an import failure occurs, inspect diagnostics and task logs to guide your fix, then retest the same DAG until it succeeds.

Why does my Airflow DAG fail in staging and how do I identify the root cause?▼

Airflow DAGs fail in staging due to import issues, missing dependencies, or credential problems. Identify the root cause by triggering the run, then using diagnostics and task log retrieval to pinpoint the failing task and error.

Does trigger-wait testing work for custom-configured Airflow DAG runs?▼

Trigger-wait testing works for manual or custom-configured Airflow DAG runs. It triggers the DAG, waits for completion, and returns state-based outcomes to perform targeted diagnostics and task log retrieval when failures occur.

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