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Databricks documentation reference. Use as a lookup resource alongside other skills and MCP tools for comprehensive guidance.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Deploy and query Databricks Model Serving endpoints. Use when (1) deploying MLflow models or AI agents to endpoints, (2) creating ChatAgent/ResponsesAgent agents, (3) integrating UC Functions or Vector Search tools, (4) querying deployed endpoints, (5) checking endpoint status. Covers classical ML models, custom pyfunc, and GenAI agents.
Create and manage Databricks Agent Bricks: Knowledge Assistants (KA) for document Q&A, Genie Spaces for SQL exploration, and Supervisor Agents (MAS) for multi-agent orchestration. Use when building conversational AI applications on Databricks.
Create Databricks AI/BI dashboards. CRITICAL: You MUST test ALL SQL queries via execute_sql BEFORE deploying. Follow guidelines strictly.
Builds Python-based Databricks applications using Dash, Streamlit, Gradio, Flask, FastAPI, or Reflex. Handles OAuth authorization (app and user auth), app resources, SQL warehouse and Lakebase connectivity, model serving integration, and deployment. Use when building Python web apps, dashboards, ML demos, or REST APIs for Databricks, or when the user mentions Streamlit, Dash, Gradio, Flask, FastAPI, Reflex, or Databricks app.
Create and configure Databricks Asset Bundles (DABs) with best practices for multi-environment deployments. Use when working with: (1) Creating new DAB projects, (2) Adding resources (dashboards, pipelines, jobs, alerts), (3) Configuring multi-environment deployments, (4) Setting up permissions, (5) Deploying or running bundle resources
Configure Databricks profile and authenticate for Databricks Connect, Databricks CLI, and Databricks SDK.
| name | databricks-docs |
| description | Databricks documentation reference. Use as a lookup resource alongside other skills and MCP tools for comprehensive guidance. |
This skill provides access to the complete Databricks documentation index via llms.txt - use it as a reference resource to supplement other skills and inform your use of MCP tools.
This is a reference skill, not an action skill. Use it to:
Always prefer using MCP tools for actions (execute_sql, create_or_update_pipeline, etc.) and load specific skills for workflows (databricks-python-sdk, databricks-spark-declarative-pipelines, etc.). Use this skill when you need reference documentation.
Fetch the llms.txt documentation index:
URL: https://docs.databricks.com/llms.txt
Use WebFetch to retrieve this index, then:
The llms.txt file is organized by category:
Scenario: User wants to create a Delta Live Tables pipeline
databricks-spark-declarative-pipelines skill for workflow patternscreate_or_update_pipeline MCP tool to actually create the pipelineScenario: User asks about an unfamiliar Databricks feature