databricks-agent-bricks

Automates provisioning of document, SQL and hybrid AI assistants via customizable templates.

27|9|Updated Feb 3, 2026
One-click install
npx skills add https://github.com/datasciencemonkey/coding-agents-databricks-apps --skill databricks-agent-bricks
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: databricks-agent-bricks
Source: https://github.com/datasciencemonkey/coding-agents-databricks-apps/tree/main/.claude/skills/databricks-agent-bricks
Command: npx skills add https://github.com/datasciencemonkey/coding-agents-databricks-apps --skill databricks-agent-bricks

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Databricks Agent Bricks provide pre-built AI components to rapidly assemble document QA, SQL exploration, and multi-agent orchestration within Databricks workflows, reducing integration effort and deployment time.

Core Features & Use Cases

  • Knowledge Assistants (KA) for document Q&A leveraging RAG across Unity Catalog volumes.
  • Genie Space for SQL-based exploration over Unity Catalog data.
  • Supervisor Agent (MAS) for multi-agent orchestration, routing queries across KAs, Genie Spaces, and model endpoints.
  • Use Case: Bootstrapping an end-to-end conversational assistant by provisioning KA + MAS and connecting to data sources.

Quick Start

Create a Knowledge Assistant from documents in a Unity Catalog Volume and deploy a Supervisor Agent to route queries.

Frequently Asked Questions about databricks-agent-bricks

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

FAQPage Schema
How do I build a multi-agent system on Databricks for conversational AI?

To build a multi-agent system on Databricks, you use a Supervisor Agent (MAS) to orchestrate and route queries across Knowledge Assistants, Genie Spaces, and model endpoints. This Skill provisions and connects these components to assemble conversational applications.

How do I create a document-backed knowledge assistant on Databricks?

You create a document-backed knowledge assistant by provisioning a Knowledge Assistant (KA) tile. The KA leverages retrieval-augmented generation across documents stored in Unity Catalog volumes to provide document Q&A capabilities.

Can I route user queries across both SQL data and documents in Databricks?

Yes, you can route queries across both formats using a Supervisor Agent. The Supervisor Agent handles cross-agent routing, directing SQL exploration to Genie Spaces and document questions to Knowledge Assistants.

What is the best way to set up SQL-based exploration over Unity Catalog data?

The best way to set up SQL-based exploration is by creating a Genie Space. This Skill provisions Genie Spaces via dedicated actions, enabling natural language SQL exploration directly over your Unity Catalog data.

Do I need Unity Catalog volumes to use Databricks Agent Bricks?

Yes, Unity Catalog volumes are required for Knowledge Assistants. The KA component uses these volumes to store and retrieve documents for retrieval-augmented generation, making them essential for document Q&A workflows.

How does cross-agent routing work in a Databricks multi-agent system?

Cross-agent routing works through a Supervisor Agent (MAS) that orchestrates complex queries. The MAS routes user requests to the appropriate Knowledge Assistant or Genie Space based on whether the query targets documents or SQL data.