running-dbt-commands

name	running-dbt-commands
description	Formats and executes dbt CLI commands, selects the correct dbt executable, and structures command parameters. Use when running models, tests, builds, compiles, or show queries via dbt CLI. Use when unsure which dbt executable to use or how to format command parameters.
user-invocable	false
metadata	{"author":"dbt-labs"}

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. Use build instead of run or test - test doesn't refresh the model, so testing a model change requires build. build does a run and a test of each node (model, seed, snapshot) in the order of the DAG
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

--select my_model              # Single model
--select staging.*             # Path pattern
--select fqn:*stg_*            # FQN pattern
--select model_a model_b       # Union (space)
--select tag:x,config.mat:y    # Intersection (comma)
--exclude my_model             # Exclude from selection

Resource type filter:

--resource-type model
--resource-type test --resource-type unit_test

Valid types: model, test, unit_test, snapshot, seed, source, exposure, metric, semantic_model, saved_query, analysis

List

Use dbt list to preview what will be selected before running. Helpful for validating complex selectors.

dbt list --select my_model+              # Preview selection
dbt list --select my_model+ --resource-type model  # Only models
dbt list --output json                   # JSON output
dbt list --select my_model --output json --output-keys unique_id name resource_type config

Available output keys for --output json: unique_id, name, resource_type, package_name, original_file_path, path, alias, description, columns, meta, tags, config, depends_on, patch_path, schema, database, relation_name, raw_code, compiled_code, language, docs, group, access, version, fqn, refs, sources, metrics

Show

Preview data with dbt show. Use --inline for arbitrary SQL queries.

dbt show --select my_model --limit 10
dbt show --inline "select * from {{ ref('orders') }} where status = 'pending'" --limit 5

Important: Use --limit flag, not SQL LIMIT clause.

Variables

Pass as STRING, not dict. No special characters (\, \n).

--vars 'my_var: value'                              # Single
--vars '{"k1": "v1", "k2": 42, "k3": true}'         # Multiple (JSON)

Analyzing Run Results

After a dbt command, check target/run_results.json for detailed execution info:

# Quick status check
cat target/run_results.json | jq '.results[] | {node: .unique_id, status: .status, time: .execution_time}'

# Find failures
cat target/run_results.json | jq '.results[] | select(.status != "success")'

Key fields:

• status: success, error, fail, skipped, warn
• execution_time: seconds spent executing
• compiled_code: rendered SQL
• adapter_response: database metadata (rows affected, bytes processed)

Defer (Skip Upstream Builds)

Reference production data instead of building upstream models:

dbt build --select my_model --defer --state prod-artifacts

Flags:

• --defer - enable deferral to state manifest
• --state <path> - path to manifest from previous run (e.g., production artifacts)
• --favor-state - prefer node definitions from state even if they exist locally

dbt build --select my_model --defer --state prod-artifacts --favor-state

Static Analysis (Fusion Only)

Override SQL analysis for models with dynamic SQL or unrecognized UDFs:

dbt run --static-analysis=off
dbt run --static-analysis=unsafe

Common Mistakes

Mistake	Fix
Using test after model change	Use build - test doesn't refresh the model
Running without --select	Always specify what to run
Using --quiet without warn-error	Add --warn-error-options '{"error": ["NoNodesForSelectionCriteria"]}'
Running dbt expecting Fusion when we are in a venv	Use dbtf or ~/.local/bin/dbt
Adding LIMIT to SQL in dbt_show	Use limit parameter instead
Vars with special characters	Pass as simple string, no \ or \n