Skills Added

dbt-agent-skills

A suite of 8 skills for working with dbt — the standard for data transformation in analytics engineering.

What problems they solve: AI agents lack context about dbt conventions, the Semantic Layer, MetricFlow, and dbt Cloud platform operations. These skills teach agents how to build models, write tests, query data, configure tooling, troubleshoot jobs, and migrate projects.

Who uses them: Analytics engineers and data teams using dbt with AI coding assistants.

Skills included:

• using-dbt-for-analytics-engineering — Build/modify dbt models, debug errors, explore data sources, write tests
• building-dbt-semantic-layer — Create semantic models, metrics, and dimensions with MetricFlow
• adding-dbt-unit-test — Add unit tests and practice TDD in dbt
• answering-natural-language-questions-with-dbt — Translate business questions into SQL queries via dbt
• configuring-dbt-mcp-server — Set up the dbt MCP server for Claude Desktop, Claude Code, and Cursor
• fetching-dbt-docs — Look up dbt Cloud, dbt Core, and Semantic Layer documentation
• troubleshooting-dbt-job-errors — Diagnose dbt Cloud job failures
• migrating-dbt-core-to-fusion — Migrate projects from dbt Core to the Fusion engine

GitHub: https://github.com/dbt-labs/dbt-agent-skills