databricks-docs
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npx mdskill add databricks/databricks-agent-skills/databricks-docsProvides access to Databricks documentation for reference and guidance.
- Solves the problem of needing authoritative Databricks documentation for APIs or features
- Uses the llms.txt index and WebFetch to retrieve documentation content
- Searches documentation based on user queries or gaps in other skills
- Returns relevant documentation links or sections for further exploration
SKILL.md
.github/skills/databricks-docsView on GitHub ↗
--- name: databricks-docs description: "Databricks documentation reference via llms.txt index. Use when other skills do not cover a topic, looking up unfamiliar Databricks features, or needing authoritative docs on APIs, configurations, or platform capabilities." --- # 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-spark-declarative-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-spark-declarative-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](../databricks-python-sdk/SKILL.md)** - SDK patterns for programmatic Databricks access - **databricks-pipelines** - DLT / Lakeflow pipeline workflows - **[databricks-unity-catalog](../databricks-unity-catalog/SKILL.md)** - Governance and catalog management - **databricks-model-serving** - Serving endpoints and model deployment - **[databricks-mlflow-evaluation](../databricks-mlflow-evaluation/SKILL.md)** - MLflow 3 GenAI evaluation workflows