A curated collection of Agent Skills for working with dbt, to help AI agents understand and execute dbt workflows more effectively.
65
82%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Risky
Do not use without reviewing
See below for all the required and optional keys in the YAML definition of unit tests.
models/schema.yml
unit_tests:
- name: <test-name> # this is the unique name of the test
description: <string> # optional
model: <model-name> # required
versions: # optional
include: <list-of-versions-to-include> # optional
exclude: <list-of-versions-to-exclude> # optional
given: # required
- input: <ref_or_source_call> # optional for seeds
format: dict | csv | sql # If not configured, defaults to `dict`
# either define `rows` inline or name of the `fixture`
rows: {dictionary} | <string>
fixture: <fixture-name> # available option for `sql` or `csv` formats
- input: ... # declare additional inputs
expect: # required
format: dict | csv | sql # If not configured, defaults to `dict`
# either define `rows` inline or name of the `fixture`
rows: {dictionary} | <string>
fixture: <fixture-name> # available option for `sql` or `csv` formats
config: # optional
meta: {dictionary} # optional
tags: <string> | [<string>] # optional
enabled: {boolean} # optional. v1.9 or higher. If not configured, defaults to `true`
overrides: # optional: configuration for the dbt execution environment
macros:
is_incremental: true | false
dbt_utils.current_timestamp: <string> # example macro name that your model depends upon
# ... any other Jinja function
# ... any other context property
vars: {dictionary}
env_vars: {dictionary}
- name: <test-name> ... # declare additional unit testsevals
skills
adding-dbt-unit-test
references
answering-natural-language-questions-with-dbt
building-dbt-semantic-layer
configuring-dbt-mcp-server
fetching-dbt-docs
scripts
migrating-dbt-core-to-fusion
running-dbt-commands
troubleshooting-dbt-job-errors
using-dbt-for-analytics-engineering