Databricks Docs skill

Databricks Documentation Reference

This skill provides access to the complete Databricks documentation index via llms.txt - use it as a reference resource to supplement other skills.

Role of This Skill

This is a reference skill, not an action skill. Use it to:

• Look up documentation when other skills don't cover a topic
• Get authoritative guidance on Databricks concepts and APIs
• Find detailed information to inform CLI commands and SDK usage
• Discover features and capabilities you may not know about

Always prefer using CLI/SDK for actions and load specific skills for workflows (databricks-python-sdk, databricks-pipelines, etc.). Use this skill when you need reference documentation.

How to Use

Fetch the llms.txt documentation index:

URL: https://docs.databricks.com/llms.txt

Use WebFetch to retrieve this index, then:

1. Search for relevant sections/links
2. Fetch specific documentation pages for detailed guidance
3. Apply what you learn using the appropriate CLI commands or SDK

Documentation Structure

The llms.txt file is organized by category:

• Overview & Getting Started - Basic concepts and tutorials
• Data Engineering - Lakeflow, Spark, Delta Lake, pipelines
• SQL & Analytics - Warehouses, queries, dashboards
• AI/ML - MLflow, model serving, GenAI
• Governance - Unity Catalog, permissions, security
• Developer Tools - SDKs, CLI, APIs, Terraform

Example: Complementing Other Skills

Scenario: User wants to create a Delta Live Tables pipeline

1. Load databricks-pipelines skill for workflow patterns
2. Use this skill to fetch docs if you need clarification on specific DLT features
3. Use databricks pipelines create CLI command to create the pipeline

Scenario: User asks about an unfamiliar Databricks feature

1. Fetch llms.txt to find relevant documentation
2. Read the specific docs to understand the feature
3. Determine which skill/tools apply, then use them

Related Skills

• databricks-python-sdk - SDK patterns for programmatic Databricks access
• databricks-pipelines - DLT / Lakeflow pipeline workflows
• databricks-unity-catalog - Governance and catalog management
• databricks-model-serving - Serving endpoints and model deployment
• databricks-mlflow-evaluation - MLflow agent evaluation and scorers; use databricks-mlflow-tracing for tracing and observability