databricks-docs

You can retrieve Databricks API reference and concepts by fetching the llms.txt index, which provides comprehensive guidance on features not covered by other skills. This allows quick lookup of specific APIs and platform concepts.

The llms.txt index serves as a comprehensive reference resource for Databricks documentation, enabling information retrieval for APIs, concepts, and features when specific tools or skills do not cover the topic.

You should fetch Databricks documentation when querying about a feature not covered by a more specific skill, or when you need authoritative guidance to inform the use of MCP tools and workflows.

Yes, this documentation lookup requires web fetching capabilities to retrieve the documentation index from the Databricks docs site and perform subsequent parsing for the relevant information.

Yes, you can use this to find Databricks features not covered by other skills by fetching the llms.txt index to parse relevant documentation and provide accurate answers.

A limitation of using the llms.txt index for Databricks reference is that it only provides an index, requiring subsequent parsing of the fetched web content to extract specific API or concept details.