dbt-labs/dbt-agent-skills
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
Passed
Use when adding unit tests for a dbt model or practicing test-driven development (TDD) in dbt
Passed
Use when a user asks a business question that requires querying data (e.g., "What were total sales last quarter?"). NOT for validating, testing, or building dbt models during development.
Passed
Use when creating or modifying dbt Semantic Layer components — semantic models, metrics, dimensions, entities, measures, or time spines. Covers MetricFlow configuration, metric types (simple, derived, cumulative, ratio, conversion), and validation for both latest and legacy YAML specs.
Risky
Use when setting up, configuring, or troubleshooting the dbt MCP server for AI tools like Claude Desktop, Claude Code, Cursor, or VS Code.
Passed
Use when fetching dbt documentation, looking up dbt features, or answering questions about dbt Cloud, dbt Core, or the dbt Semantic Layer
Advisory
Guides migration of dbt projects from dbt Core to the Fusion engine. Use when making a project compatible with Fusion, addressing deprecations, or running dbtf commands.
Passed
Use when executing dbt commands via CLI - running models, tests, builds, compiles, or show queries. Use when unsure which dbt executable to use or how to format command parameters.
Advisory
Use when a dbt Cloud/platform job fails and you need to diagnose the root cause, especially when error messages are unclear or when intermittent failures occur. Do not use for local dbt development errors.
Advisory
Use when doing any dbt work - building or modifying models, debugging errors, exploring unfamiliar data sources, writing tests, or evaluating impact of changes. Use for analytics pipelines, data transformations, and data modeling.
Security
1 high severity finding. You should review these findings carefully before considering using this skill.
W007: Insecure credential handling detected in skill instructions
What this means
The skill handles credentials insecurely by requiring the agent to include secret values verbatim in its generated output. This exposes credentials in the agent’s context and conversation history, creating a risk of data exfiltration.
Why it was flagged
Insecure credential handling detected (high risk: 0.90). The prompt includes configuration templates and header examples that require inserting tokens (DBT_TOKEN / Authorization headers / x-dbt-user-id) into JSON/.env or requests, which would force an agent to accept and embed secret values verbatim in generated configs or commands, creating an exfiltration risk.
- Audited
- Security analysis