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running-dbt-commands

Execute dbt CLI commands with correct flavors, selectors, and flags.

653|60|Updated Jan 8, 2026
Search Tags:#workflow#dbt#command-line#selectors#dbt-cli#dbt-run#dbt-build
One-click install
npx skills add https://github.com/dbt-labs/dbt-agent-skills --skill running-dbt-commands-dbt-labs
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: running-dbt-commands
Source: https://github.com/dbt-labs/dbt-agent-skills/tree/main/skills/running-dbt-commands
Command: npx skills add https://github.com/dbt-labs/dbt-agent-skills --skill running-dbt-commands-dbt-labs

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill guides users to execute dbt CLI commands (build, run, show, test) with correct flavors, options, and selectors to avoid common mistakes and save time.

Core Features & Use Cases

  • Guidance on choosing the right dbt CLI flavor (Core, Fusion, Cloud) and applying consistent command patterns
  • Instructions for selecting models, tests, and resources with explicit selectors, variables, and flags
  • Practical scenarios like debugging a failing model, validating changes across models, and performing quick targeted runs

Quick Start

Run a targeted dbt command using the recommended CLI flavor with explicit selectors and the appropriate flags.

Frequently Asked Questions about running-dbt-commands

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

FAQPage Schema
How do I run targeted dbt CLI commands for specific models using selectors?▼

To run targeted dbt CLI commands, apply explicit selectors and flags to choose specific models, tests, or resources. This ensures precise execution across your dbt workflows and production pipelines without affecting unrelated resources.

What is the difference between dbt build and dbt run when executing commands?▼

The difference between dbt build and dbt run is that build executes models, tests, snapshots, and seeds together, while run only executes models. Choosing the correct command prevents incomplete testing during dbt CLI workflows.

Which dbt CLI flavor should I use for my production pipeline?▼

Choosing the right dbt CLI flavor—Core, Fusion, or Cloud—depends on your environment and production pipeline requirements. Applying consistent command patterns across your chosen flavor ensures reliable execution and management of dbt tasks.

Can I pass variables and flags when automating dbt CLI commands?▼

Yes, you can pass explicit variables and flags when automating dbt CLI commands. This allows you to parameterize builds, runs, and tests, ensuring the correct command parameters are applied during debugging sessions and workflow execution.

What is the best way to debug a failing dbt model from the command line?▼

The best way to debug a failing dbt model is to execute targeted dbt CLI commands using precise selectors and the show command. This isolates the failing resource, validates changes, and saves time during debugging sessions.

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