claude

dbt-labs-dbt-agent-skills

Curated agent skills collection for dbt workflows, helping AI agents understand and execute data transformation pipelines more effectively.

0 on GitHubupdated 6 months agodata_storage
/

Plugin dbt-labs-dbt-agent-skills from marketplace cascade-data-storage in joshuarweaver/cascade-data-storage. Commands read from the repo's manifest — 1 month ago.

What it installs

Skills (17)

  • auditing-skills

    Use when checking skills for security or quality issues, reviewing audit results from skills.sh or Tessl, or remediating findings across published skills.

  • creating-mermaid-dbt-dag

    Generates a Mermaid flowchart diagram of dbt model lineage using MCP tools, manifest.json, or direct code parsing as fallbacks. Use when visualizing dbt model lineage and dependencies as a Mermaid diagram in markdown format.

  • migrating-dbt-core-to-v2

    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).

  • migrating-dbt-project-across-platforms

    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.

  • upgrading-dbt

    Use when a user wants to upgrade, update, or migrate a dbt project to the latest version — e.g. "upgrade my dbt project," "migrate this off dbt 1.5," "get this project running on the latest dbt," "bump the dbt version." Upgrades a dbt v1 project (on 1.3, 1.4, 1.5, 1.6, or 1.7) all the way to 1.12, a

  • adding-dbt-unit-test

    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.

  • answering-natural-language-questions-with-dbt

    Writes and executes SQL queries against the data warehouse using dbt's Semantic Layer or ad-hoc SQL to answer business questions. Use when a user asks about analytics, metrics, KPIs, or data (e.g., "What were total sales last quarter?", "Show me top customers by revenue"). NOT for validating, testin

  • building-dbt-semantic-layer

    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.

  • configuring-dbt-mcp-server

    Generates MCP server configuration JSON, resolves authentication setup, and validates server connectivity for dbt. Use when setting up, configuring, or troubleshooting the dbt MCP server for AI tools like Claude Desktop, Claude Code, Cursor, or VS Code.

  • fetching-dbt-docs

    Retrieves and searches dbt documentation pages in LLM-friendly markdown format. Use when fetching dbt documentation, looking up dbt features, or answering questions about dbt Cloud, dbt Core, or the dbt Semantic Layer.

  • maintaining-dbt-documentation

    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 keeping schema YAML in sync with model S

  • querying-the-dbt-information-schema

    Use when answering questions about a dbt v2 project's own metadata — which models, sources, tests, columns, configs, tags, packages or lineage exist, what is untested or undocumented, what depends on what, how long models took in the last run — or when using `dbt show --info`, `{{ info_schema() }}`,

  • running-dbt-commands

    Formats and executes dbt CLI commands, selects the correct dbt executable, and structures command parameters. Use when running models, tests, builds, compiles, or show queries via dbt CLI. Use when unsure which dbt executable to use or how to format command parameters.

  • troubleshooting-dbt-job-errors

    Diagnoses dbt Cloud/platform job failures by analyzing run logs, querying the Admin API, reviewing git history, and investigating data issues. 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 occ

  • using-dbt-for-analytics-engineering

    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 tests, or evaluating impact of changes.

  • using-dbt-state

    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. Use when asked about models rebuilding un

  • working-with-dbt-mesh

    Use when changing a dbt model in a way that could break its consumers — renaming, removing, or retyping a column, or changing a model that downstream models, exposures, dashboards, or BI tools depend on — to judge whether the change is breaking and who it affects. Also use when versioning a model (m

View source on GitHub

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