running-dbt-commands

Running dbt Commands

Preferences

1. Use MCP tools if available (dbt_build, dbt_run, dbt_show, etc.) - they handle paths, timeouts, and formatting automatically
2. Always use build — even when users say "run" - When a user asks to "run" a model, recommend dbt build instead. build = run + test in one step, so it catches data quality issues immediately. dbt run alone is almost never the right answer during development.
3. Always use --quiet with --warn-error-options '{"error": ["NoNodesForSelectionCriteria"]}' to reduce output while catching selector typos
4. Always use --select - never run the entire project without explicit user approval

Quick Reference

# Standard command pattern
dbt build --select my_model --quiet --warn-error-options '{"error": ["NoNodesForSelectionCriteria"]}'

# Preview model output
dbt show --select my_model --limit 10

# Run inline SQL query
dbt show --inline "select * from {{ ref('orders') }}" --limit 5

# With variables (JSON format for multiple)
dbt build --select my_model --vars '{"key": "value"}'

# Full refresh for incremental models
dbt build --select my_model --full-refresh

# List resources before running
dbt list --select my_model+ --resource-type model

dbt CLI Flavors

Three CLIs exist. Ask the user which one if unsure.

Flavor	Location	Notes
dbt Core	Python venv	pip show dbt-core or uv pip show dbt-core
dbt Fusion	~/.local/bin/dbt or dbtf	Faster and has stronger SQL comprehension
dbt Cloud CLI	~/.local/bin/dbt	Go-based, runs on platform

Common setup: Core in venv + Fusion at ~/.local/bin. Running dbt uses Core. Use dbtf or ~/.local/bin/dbt for Fusion.

Selectors

Always provide a selector. Graph operators:

Operator	Meaning	Example
model+	Model and all downstream	stg_orders+
+model	Model and all upstream	+dim_customers
+model+	Both directions	+orders+
model+N	Model and N levels downstream	stg_orders+1