databricks-genie-agents
Create, manage, and query Databricks Genie Agents — curated, per-data natural-language agents (formerly Genie Spaces): build, export/import, migrate across workspaces, and ask questions of a *specific* Agent via the Conversation API. For general data questions or finding data across your workspace, use databricks-data-discovery (Genie One) instead.
Databricks Genie Agents
Create, manage, and query Genie Agents (formerly Genie Spaces) - natural language interfaces for SQL-based data exploration.
Overview
Genie Agents 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.
A Genie Agent is a curated agent scoped to specific data — its tables, sample questions, and instructions are authored for a particular business area. This is distinct from Genie One / the general "ask Genie" data-discovery path (see the databricks-data-discovery skill), which answers questions across your data without a curated, per-scope agent.
Genie Agent Lifecycle
| Phase | Reference | Load when | Typical CLI |
|---|---|---|---|
| Design + Create | create-genie-agent.md | Always load before creating or updating. Gather requirements, profile data, design surfaces, get approval — before any CLI | discover-schema → create-space / update-space |
| Query / validate | query-genie-agent.md | Querying via Conversation API or Agent mode API; authoring SQL for Metric View sources | start-conversation / get-message |
| Diagnose | diagnose-genie-agent.md | Agent gives wrong/empty answers — gather space ID + failing question + observed behavior first | get-space --include-serialized-space; system.query.history |
| Optimize | optimize-genie-agent.md | Benchmark-driven quality tuning — gather space ID + optimization goal + benchmark target first | genie-create-eval-run; update-space |
| Export / migrate | genie-agent-cicd.md | Export, import, cross-workspace migration, batch migration, DABs/CI-CD | get-space → remap → create-space |
| — | serialized-space.md | Constructing or debugging serialized_space payloads — field schemas, constraints, Python helper | — |
| — | uc-persistence.md | Setting up UC Delta tables for multi-pass optimization history — CREATE TABLE DDL only | — |
Typical flow: create → query/validate → diagnose → optimize.
Prerequisites
- Tables in Unity Catalog — bronze/silver/gold tables with the data
- SQL Warehouse — a warehouse to execute queries (auto-detected if not specified)
Related Skills
- databricks-data-discovery - General natural-language data exploration / "ask Genie" (Genie One) across your data; use it when you are not targeting a specific curated Genie Agent
- databricks-metric-views - Build governed business metrics that Genie consumes. See SKILL.md for metric-view design rules that affect Genie answer quality, and query-patterns.md for the
MEASURE()query rules Genie must follow. - databricks-agent-bricks - Use Genie Agents as agents inside Supervisor Agents
- databricks-unity-catalog - Manage the catalogs, schemas, and tables Genie queries
- Repository
databricks/databricks-agent-skills
- Revision
c570f88
- Last updated
- First committed
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.