troubleshooting-dbt-job-errors

Diagnose and resolve dbt Cloud job failures by classifying errors and guiding root cause analysis.

1|Updated Jan 17, 2026
One-click install
npx skills add https://github.com/juandaniel190/personal-projects --skill troubleshooting-dbt-job-errors-juandaniel190
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: troubleshooting-dbt-job-errors
Source: https://github.com/juandaniel190/personal-projects/tree/main/.cursor/skills/troubleshooting-dbt-job-errors
Command: npx skills add https://github.com/juandaniel190/personal-projects --skill troubleshooting-dbt-job-errors-juandaniel190

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you systematically diagnose and resolve failures in dbt Cloud or dbt platform jobs, especially when error messages are unclear or failures are intermittent.

Core Features & Use Cases

  • Error Classification: Identifies whether failures are due to infrastructure, code/compilation, or data/test issues.
  • Information Gathering: Utilizes MCP Admin API tools or prompts users for logs and run_results.json when the API is unavailable.
  • Root Cause Analysis: Guides through checking git history, dbt CLI/LSP tools, and data investigation using the discovering-data skill.
  • Resolution Workflow: Provides steps for fixing issues, adding tests, and creating pull requests, or documenting unresolved issues.
  • Use Case: A dbt Cloud job fails overnight. You use this skill to gather the run details, identify a data test failure, and then use the discovering-data skill to query the underlying data and pinpoint the schema mismatch causing the test to fail.

Quick Start

Use the troubleshooting-dbt-job-errors skill to diagnose a failed dbt Cloud job run.

Frequently Asked Questions about troubleshooting-dbt-job-errors

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

FAQPage Schema
How do I troubleshoot a failed dbt Cloud job run?

To troubleshoot a failed dbt Cloud job run, gather run details via the MCP Admin API or logs, classify the failure into infrastructure, code, or data categories, and perform root cause analysis using git history and dbt tools.

What is the best way to debug intermittent dbt pipeline failures?

Debugging intermittent dbt pipeline failures involves classifying the error source, inspecting `run_results.json`, and investigating data anomalies or schema mismatches that cause inconsistent data test failures.

How do I find the root cause of a dbt compilation error?

Finding the root cause of a dbt compilation error requires classifying it as a code issue, checking git history for recent changes, and using dbt CLI or LSP tools to pinpoint syntax or dependency problems.

Can I use dbt tools to investigate data test failures?

Yes, you can investigate data test failures by classifying the error as a data issue and querying the underlying data to pinpoint schema mismatches or anomalies causing the dbt test to fail.

What should I do after fixing a dbt job failure?

After fixing a dbt job failure, you should follow the resolution workflow to implement the fix, add tests to prevent recurrence, create a pull request, and document any unresolved issues.