A curated collection of Agent Skills for working with dbt, to help AI agents understand and execute dbt workflows more effectively.
91
Does it follow best practices?
Validation for skill structure
A user is migrating their dbt project to Fusion. A model retrieves the meta config as a plain dictionary (config.get('meta', {})), then incorrectly calls .meta_get() on that plain dict. Only config objects have meta_get() — plain dicts must use .get().
The agent should:
.meta_get() is being called on a plain dict, not a config objectmeta_config.meta_get('owner', 'unknown') with meta_config.get('owner', 'unknown').meta_get() only exists on config objects, not plain dicts.get() for the plain dictionaryconfig.get('meta') (correct) with the .meta_get() call on the resultInstall with Tessl CLI
npx tessl i dbt-labs/dbt-agent-skillsevals
scenarios
dbt-docs-arguments
dbt-docs-unit-test-fixtures
dbt-job-failure
dbt-unit-test-format-choice
example-yaml-error
fusion-migration-triage-basic
fusion-migration-triage-blocked
fusion-triage-cat-a-static-analysis
fusion-triage-cat-b-dict-meta-get
fusion-triage-cat-b-unexpected-config
fusion-triage-cat-b-unused-schema
fusion-triage-cat-b-yaml-syntax
fusion-triage-cat-c-hardcoded-fqn
tests
scripts
skills
dbt
skills
adding-dbt-unit-test
references
answering-natural-language-questions-with-dbt
building-dbt-semantic-layer
configuring-dbt-mcp-server
fetching-dbt-docs
scripts
running-dbt-commands
troubleshooting-dbt-job-errors
references
using-dbt-for-analytics-engineering
dbt-migration
skills
migrating-dbt-core-to-fusion
migrating-dbt-project-across-platforms