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Troubleshooting Dbt Job Errors

Official
dbt-labs·vlatest·data·Apache-2.0

This skill automatically analyzes and explains Dbt job error messages, quickly pinpointing issues and speeding up resolution for faster data pipelines.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add dbt-labs/dbt-agent-skills --skill troubleshooting-dbt-job-errors -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

dbt-labs

Matched to the vendor's own GitHub organisation.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned dbt-labs/dbt-agent-skills at 0d094169f5.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
0d094169f5
Manifest
skills/dbt/skills/troubleshooting-dbt-job-errors/SKILL.md
Scanned
2 files, 297 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill enables AI agents to automatically diagnose and resolve errors occurring within dbt (data build tool) jobs. It analyzes job logs and configuration files to identify root causes, such as model definition issues or data type mismatches, and suggests specific fixes to restore pipeline functionality.

When to use it

  • A dbt job fails during the compile or run phase with an unclear error message in the CI/CD pipeline.
  • An AI agent needs to autonomously inspect a failed transformation job and propose code corrections without human intervention.
  • You are debugging complex dependency errors where standard log parsing does not reveal the underlying schema conflict.

Key capabilities

  • Parses dbt job logs to extract specific error contexts and stack traces.
  • Identifies common failure patterns including missing models, column type mismatches, and syntax errors in SQL definitions.
  • Generates targeted remediation steps or corrected SQL snippets based on the detected issue.
  • Validates proposed fixes against standard dbt best practices before suggesting implementation.

Example prompts

  • "Analyze this failed dbt run log and explain why the customers model compilation failed."
  • "Review the provided YAML configuration and suggest a fix for the 'ref' function error in the orders model."
  • "Diagnose the data type mismatch causing the job to halt and propose a corrected SQL cast statement."

Tips & gotchas

Ensure the AI agent has access to the full, unredacted dbt job logs and the relevant project files (models, macros, and profiles) to provide accurate diagnoses. This skill is specific to the dbt ecosystem and will not resolve errors in unrelated data processing tools or generic SQL syntax outside of a dbt context.