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RamVegiraju
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databricks-genie

Create and query Genie Spaces over Unity Catalog data with natural language.

4|4|Updated Jan 5, 2026
Search Tags:#sql#nlp#conversational-ai#spaces#databricks#unity-catalog#genie
One-click install
npx skills add https://github.com/RamVegiraju/databricks-samples --skill databricks-genie-ramvegiraju
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: databricks-genie
Source: https://github.com/RamVegiraju/databricks-samples/tree/main/.claude/skills/databricks-genie
Command: npx skills add https://github.com/RamVegiraju/databricks-samples --skill databricks-genie-ramvegiraju

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Genie Spaces provide a natural-language interface to Unity Catalog data, translating user questions into SQL queries and returning results without manual SQL writing.

Core Features & Use Cases

  • Space management: create or update Genie Spaces that connect to catalog tables for guided analytics.
  • Conversation API: programmatically ask questions to Genie Spaces and receive SQL results.
  • Workflow guidance: end-to-end support from inspecting tables to space creation to querying, with curated sample questions.
  • Use Case: quickly scaffold a Genie Space for a dataset and test questions via the API.

Quick Start

Create a Genie Space for your Unity Catalog data and start querying it with the Conversation API.

Frequently Asked Questions about databricks-genie

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create a Genie Space over Unity Catalog data?▼

To create a Genie Space, you use the create_or_update_genie tool to connect to specific catalog tables, enabling a natural language interface for guided analytics over your data.

How do I query Genie Spaces using natural language instead of SQL?▼

You can query Genie Spaces using natural language by leveraging the ask_genie Conversation API, which translates your text questions into SQL and returns results without manual SQL writing.

What is the workflow for inspecting tables before setting up a Genie Space?▼

The workflow involves using get_table_details and execute_sql for validation to inspect tables, followed by space creation with create_or_update_genie, and finally querying the space programmatically.

Do I need to write SQL to use Genie Spaces for conversational analytics?▼

No, Genie Spaces provide a natural language interface that automatically translates user questions into SQL queries, returning results without requiring you to manually write SQL.

Can I programmatically manage and delete Genie Spaces via an API?▼

Yes, you can manage Genie Spaces programmatically using tools like get_genie to retrieve space details and delete_genie to remove spaces, ensuring full lifecycle management over your catalog data.

What is the best way to test natural language questions against a dataset?▼

The best way is to scaffold a Genie Space for your dataset and use the ask_genie Conversation API to test curated sample questions, validating that the natural language to SQL translation returns correct results.

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