databricks-genie

name	databricks-genie
description	Create and query Databricks Genie Spaces for natural language SQL exploration. Use when building Genie Spaces or asking questions via the Genie Conversation API.

Databricks Genie

Create and query Databricks Genie Spaces - natural language interfaces for SQL-based data exploration.

Overview

Genie Spaces allow users to ask natural language questions about structured data in Unity Catalog. The system translates questions into SQL queries, executes them on a SQL warehouse, and presents results conversationally.

When to Use This Skill

Use this skill when:

• Creating a new Genie Space for data exploration
• Adding sample questions to guide users
• Connecting Unity Catalog tables to a conversational interface
• Asking questions to a Genie Space programmatically (Conversation API)

MCP Tools

Space Management

Tool	Purpose
list_genie	List all Genie Spaces accessible to you
create_or_update_genie	Create or update a Genie Space
get_genie	Get Genie Space details
delete_genie	Delete a Genie Space

Conversation API

Tool	Purpose
ask_genie	Ask a question to a Genie Space, get SQL + results
ask_genie_followup	Ask follow-up question in existing conversation

Supporting Tools

Tool	Purpose
get_table_details	Inspect table schemas before creating a space
execute_sql	Test SQL queries directly

Quick Start

1. Inspect Your Tables

Before creating a Genie Space, understand your data:

get_table_details(
    catalog="my_catalog",
    schema="sales",
    table_stat_level="SIMPLE"
)

2. Create the Genie Space

create_or_update_genie(
    display_name="Sales Analytics",
    table_identifiers=[
        "my_catalog.sales.customers",
        "my_catalog.sales.orders"
    ],
    description="Explore sales data with natural language",
    sample_questions=[
        "What were total sales last month?",
        "Who are our top 10 customers?"
    ]
)

3. Ask Questions (Conversation API)

ask_genie(
    space_id="your_space_id",
    question="What were total sales last month?"
)
# Returns: SQL, columns, data, row_count

Workflow

1. Inspect tables    → get_table_details
2. Create space      → create_or_update_genie
3. Query space       → ask_genie (or test in Databricks UI)
4. Curate (optional) → Use Databricks UI to add instructions

Reference Files

• spaces.md - Creating and managing Genie Spaces
• conversation.md - Asking questions via the Conversation API

Prerequisites

Before creating a Genie Space:

1. Tables in Unity Catalog - Bronze/silver/gold tables with the data
2. SQL Warehouse - A warehouse to execute queries (auto-detected if not specified)

Creating Tables

Use these skills in sequence:

1. databricks-synthetic-data-generation - Generate raw parquet files
2. databricks-spark-declarative-pipelines - Create bronze/silver/gold tables

Common Issues

Issue	Solution
No warehouse available	Create a SQL warehouse or provide warehouse_id explicitly
Poor query generation	Add instructions and sample questions that reference actual column names
Slow queries	Ensure warehouse is running; use OPTIMIZE on tables

Related Skills

• databricks-agent-bricks - Use Genie Spaces as agents inside Supervisor Agents
• databricks-synthetic-data-generation - Generate raw parquet data to populate tables for Genie
• databricks-spark-declarative-pipelines - Build bronze/silver/gold tables consumed by Genie Spaces
• databricks-unity-catalog - Manage the catalogs, schemas, and tables Genie queries