dbt-labs

Use when a user needs help triaging dbt-core to dbt v2 migration errors. Runs dbt-autofix first, then classifies remaining errors into actionable categories (auto-fixable, guided fixes, needs input, blocked).

Use when migrating a dbt project from one data platform or data warehouse to another (e.g., Snowflake to Databricks, Databricks to Snowflake) using dbt Fusion's real-time compilation to identify and fix SQL dialect differences.

Use when a user wants to upgrade, update, or migrate a dbt-core project to the latest version — e.g. "upgrade my dbt project," "migrate this off dbt-core 1.5," "get this project running on the latest dbt," "bump the dbt-core version." Upgrades a dbt-core v1…

Audits dbt documentation coverage and drafts missing model/column descriptions in the project's own house style, one folder at a time, for human review. Use when documenting undocumented models, backfilling missing YAML descriptions, auditing doc coverage, or…

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…

Use when a user is enabling, configuring, optimizing, or debugging dbt State (the server-backed reuse mechanism that clones or skips nodes instead of rebuilding them). Use when they conflate dbt State with the `state:modified` selector or `--state` deferral.…

Creates unit test YAML definitions that mock upstream model inputs and validate expected outputs. Use when adding unit tests for a dbt model or practicing test-driven development (TDD) in dbt.

Builds and modifies dbt models, writes SQL transformations using ref() and source(), creates tests, and validates results with dbt show. Use when doing any dbt work - building or modifying models, debugging errors, exploring unfamiliar data sources, writing…

Add or resolve an `availability` frontmatter field for a docs.getdbt.com page, so the page renders the correct applicability badge (where a feature runs, what plan/access it needs, which dbt engine version). Use when asked to add an availability badge, mark a…

Use when converting a Notion markdown export to a Docusaurus blog post for the dbt docs site, or when given a path to a Notion export folder/file.

Scaffold a new skeleton markdown doc for docs.getdbt.com — standard guide, reference page, feature/product page, or release note entry. Use when asked to create a new doc page, scaffold a doc, start a new page, or add a page to the sidebar.

Use this skill to triage, score, and label GitHub issues in the docs.getdbt.com repo. Triggers when the user asks to triage issues, rank issues by priority or size, label GitHub issues, review the issue backlog, or score open docs issues. Also use this skill…

Use this skill to triage, score, and label GitHub issues in the docs.getdbt.com repo. Triggers when the user asks to triage issues, rank issues by priority or size, label GitHub issues, review the issue backlog, or score open docs issues. Also use this skill…

Use in a reviewer agent in agent loops or when reviewing your own code.

Use when annotating fs adapter implementations with upstream dbt-adapters Python reference links. Triggers whenever you need to add or audit GitHub permalink comments in adapter_impl.rs, trace an fs adapter method back to its Python origin in dbt-adapters, or…

Connect an AI coding agent to Snowflake, BigQuery, or Databricks so it can run SQL. Use when warehouse access is missing, authentication or connection selection is required, or before using a warehouse-data skill such as agents-schema-search.

Use when answering questions about data in a warehouse (BigQuery, Snowflake, etc.) and you have direct SQL access (CLI, driver, or console). Discover metadata and run knowledge search through the warehouse-native AGENTS schema instead of INFORMATION_SCHEMA.

Use when troubleshooting dbt query performance, comparing model implementations, retrieving query plans/stats, or helping users understand how to use the dbt-query-profiler package. Also use when users ask about getting query IDs from dbt runs.

Use when adding support for a new data warehouse adapter (e.g., Trino, Postgres, Spark) to dbt-query-profiler. Triggers include creating adapter macros, implementing query history/plan/stats, or extending platform support.

Release a new version of dbt-mcp to PyPi

Use when authoring or debugging ade-bench tasks that must run on both DuckDB and Snowflake, including shared project migrations, setup patches, and solution patches

Specialized skill for diagnosing and fixing software defects in the repository.

Create a new integration test for dbt-autofix with proper folder structure and golden files