Agent skill · Audited from source

running-dbt-commands

skill · dbt-labs/dbt-agent-skillsApache-2.0 licenceAudited 26 Oct 2026 · source 462d9a0d3c07

★ 747pushed 4 days ago
✓SAFEGrade B · 89/100 · 26 Oct 2026 · 462d9a0
747repo stars · whole dbt-labs/dbt-agent-skills

Is it safe? Yes — SAFE, grade B (89/100). We read this skill's source at commit 462d9a0d3c07 and found no filesystem, network or shell access and no hard-coded secrets. What it does: 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…

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Cite this page

ModelsAtlas. “running-dbt-commands (dbt-labs/dbt-agent-skills)”. Retrieved 26 Oct 2026. https://modelsatlas.com/skills/dbt-labs/running-dbt-commands

Trust audit

Audit 0.4.1 · source read 26 Oct 2026

Trust score89/100✓SAFE B
0 critical0 high0 medium0 low0 info

SAFE means nothing in the source contradicts what the skill says it does. Grade B is shared by 13,985 of 14,816 audited skills.

What the source does

  • FilesystemNone observedNo reads or writes in the source
  • NetworkNone observedNo outbound calls in the source
  • ShellNone observedNo commands run in the source
  • DependenciesPinnedNothing floats
  • SecretsNone foundNo keys in source

Five audit layers

LayerWhat we checkResultFindings
L0 ProvenanceRepo owner, licence, archive status, activityPASS0
L1 Static sourceSecrets, path traversal, supply chain, hidden codeNA0
L2 InstructionsPrompt injection, authority framing, hidden directivesPASS0
L3 InventoryThe files and declarations match the sourcePASS0
L4 SandboxRun in isolation and watch behaviourSKIPPED why0

Gates applied: no behavioural pass.

Findings (0)

No findings at any severity. We re-audit when the source changes.

Audit 0.4.1 · source sha 462d9a0d3c07 · 26 Oct 2026Report an issue or request a re-scan

Provenance

Who published it, and what the verdict is pinned to

  • Publisherdbt-labs GitHub organizationOwner of the repository this skill is read from
  • Source folderdbt-labs/dbt-agent-skills/skills/dbt/skills/running-dbt-commandsThe exact folder we audited
  • LicenceApache-2.0As the repository states it
  • Commit pinned for this verdict462d9a0d3c07A new audit runs when the source changes
  • Repository statusNot archivedLast push 4 days ago
  • Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

What it tells the agent

Full source on GitHub ↗

Its 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…

---
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. **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

```bash
# 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` |

```bash
--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:**
```bash
--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`

> **Fusion:** `--resource-type` is **not supported with `dbt test`** ([dbt-fusion#1628](https://github.com/dbt-labs/dbt-fusion/issues/1628)). To run unit tests in Fusion:
> - `dbt build --select model_name` — builds the model first, then runs all tests including unit tests
> - `dbt build --select unit_test_name` — targets a specific unit test by name
> - `dbt list --resource-type unit_test` — lists unit test names for use in selectors

## List

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

```bash
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.

```bash
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`).

```bash
--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:

```bash
# 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:

```bash
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

```bash
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:

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

#

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

Install

Pinned to the audited commit 462d9a0

Download folder ↗
git clone https://github.com/dbt-labs/dbt-agent-skills
git -C dbt-agent-skills checkout 462d9a0d3c07

The author documents no install command, so this uses the repository directly. Our verdict covers commit 462d9a0d3c07 only.

Works in

The author has not said which agents this skill supports, and we have not tested it in any.

Audit history

Every audit, every source change

  1. ✓SAFE B 89 / 100

    first audit · source 462d9a0d3c07

Similar skills

Questions about running-dbt-commands

What does the running-dbt-commands skill do?
A curated collection of Agent Skills for working with dbt, to help AI agents understand and execute dbt workflows more effectively.
Is running-dbt-commands safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can running-dbt-commands access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (462d9a0d3c07), read on 2026-10-26. The repository is watched, and a new audit runs when it changes — this is the first audit.

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