fetching-dbt-docs_skill

Overview

This skill fetches and locates dbt documentation efficiently for agents and users. It leverages dbt's LLM-friendly markdown URLs and indexed lists to return clean .md pages and pinpoint relevant topics. The skill helps avoid common fetching mistakes and reduces unnecessary downloads of the full docs set.

How this skill works

The skill converts regular docs URLs to LLM-friendly markdown by appending .md, then fetches the page. It uses the llms.txt index to quickly find page titles and descriptions, and provides a search script to scan full docs only when the index has no matches. After locating pages, fetch commands target the .md URLs to retrieve clean markdown content.

When to use it

• Fetching a specific dbt docs page as markdown
• Looking up dbt Cloud, dbt Core, or dbt Semantic Layer features
• Searching for relevant dbt docs topics or command references
• Automating documentation lookups inside an agent workflow
• Avoiding HTML scraping when you need clean LLM-friendly text

Best practices

• Always append .md to any docs.getdbt.com URL before fetching
• Search llms.txt first — it’s fast and contains titles and descriptions
• Only search the full docs content when the index has no results
• Use the provided search script to filter llms-full.txt rather than loading the entire file
• When using the search script, optionally force a fresh download to bypass a 24-hour cache

Example use cases

• Retrieve the run command reference: convert the URL to .../reference/commands/run.md and fetch it
• Find pages about semantic models by searching llms.txt, then fetch matching .md pages
• Use the search script to locate docs mentioning “incremental strategy” and fetch the relevant pages
• Automate doc lookups inside an agent: query llms.txt for topic URLs, then fetch each .md page for summarization