Does this skill support dbt Cloud and dbt Core?

Yes, it supports dbt Cloud, dbt Core, and the dbt Semantic Layer documentation, providing a unified interface for all dbt-related queries.

How do I ensure I am reading the most recent dbt docs?

The skill includes a built-in search script that supports a --fresh flag, allowing you to bypass the standard 24-hour cache and download the latest documentation directly.

Can I search the entire dbt documentation site at once?

Yes, the skill utilizes a two-step approach: it first searches a fast index (llms.txt) and then uses a specialized shell script to perform keyword searches across all available documentation pages.

Why does this skill append .md to dbt documentation URLs?

Adding .md to dbt docs URLs converts the page into a clean Markdown format. This is significantly more token-efficient and easier for Claude to parse compared to standard HTML versions.

Fetch dbt Documentation

Name: Fetch dbt Documentation
Author: dbt-labs

bydbt-labs

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Learning & Documentation

Optimizes Claude's ability to retrieve and search dbt Cloud, Core, and Semantic Layer documentation in LLM-friendly Markdown format.

About

This skill empowers Claude to interact seamlessly with dbt documentation by automatically converting standard web URLs into clean, LLM-optimized Markdown versions. It provides specialized search capabilities through indexed files and a local search script, ensuring the AI has immediate access to accurate, up-to-date information on dbt features, commands, and implementation patterns while avoiding the noise and token overhead of standard HTML pages.

Key Features

13 GitHub stars
Comprehensive coverage of dbt Cloud, Core, and Semantic Layer docs
High-speed index searching via llms.txt integration
Smart 24-hour caching with options for fresh-fetch updates
Local full-text search script for deep content discovery
Automatic Markdown conversion for dbt documentation URLs

Use Cases

Looking up specific dbt command syntax and reference materials
Troubleshooting dbt Semantic Layer configurations using official technical guides
Searching for implementation patterns for incremental models and metrics

About

Key Features

13 GitHub stars
Comprehensive coverage of dbt Cloud, Core, and Semantic Layer docs
High-speed index searching via llms.txt integration
Smart 24-hour caching with options for fresh-fetch updates
Local full-text search script for deep content discovery
Automatic Markdown conversion for dbt documentation URLs

Use Cases

Looking up specific dbt command syntax and reference materials
Troubleshooting dbt Semantic Layer configurations using official technical guides
Searching for implementation patterns for incremental models and metrics