databricks-aibi-dashboards

Design and deploy Databricks AI/BI dashboards with validated SQL queries.

27|9|Updated Feb 3, 2026

Search Tags:#dashboard #data-visualization #databricks #ai-bi #dashboard-json #sql-validation #execute_sql

Ready to run

npx skills add https://github.com/datasciencemonkey/coding-agents-databricks-apps --skill databricks-aibi-dashboards

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: databricks-aibi-dashboards
Source: https://github.com/datasciencemonkey/coding-agents-databricks-apps/tree/main/.claude/skills/databricks-aibi-dashboards
Command: npx skills add https://github.com/datasciencemonkey/coding-agents-databricks-apps --skill databricks-aibi-dashboards

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Databricks AI/BI dashboards can be brittle without a formal validation workflow. This skill enforces a mandatory process to design, test, and deploy dashboards by validating all SQL queries with execute_sql before production deployment.

Core Features & Use Cases

Enforces a strict validation workflow: inspect schemas, write and test SQL queries, construct dashboard JSON, and deploy dashboards via create_or_update_dashboard.
Integrates MCP tooling to streamline dashboard creation, testing, and publishing across Databricks workspaces.
Use case: data teams build production dashboards that require query verification, governance, and reproducible deployment across environments.

Quick Start

Provide a validated dataset and run the automation to produce and deploy a dashboard after SQL testing.

Frequently Asked Questions about databricks-aibi-dashboards

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

FAQPage Schema

How do I validate SQL queries before deploying a Databricks AI/BI dashboard?▼

You can validate SQL queries before dashboard deployment by running them through execute_sql to verify correctness. This skill enforces a strict workflow that requires query validation before constructing dashboard JSON and deploying via create_or_update_dashboard.

What is the process for building Databricks AI/BI dashboards with query validation?▼

Building Databricks AI/BI dashboards with query validation requires a strict workflow: inspect schemas, write and test SQL via execute_sql, construct dashboard JSON, and deploy using create_or_update_dashboard. This ensures datasets, queries, and widgets are tested before production.

Can I use this skill to deploy dashboards across multiple Databricks workspaces?▼

Yes, this skill supports deploying dashboards across multiple Databricks workspaces by integrating MCP tooling. It streamlines creation, testing, and publishing while ensuring governance and reproducible deployment across environments.

Why do my Databricks AI/BI dashboards break in production without query validation?▼

Databricks AI/BI dashboards break in production without query validation because untested SQL can cause brittle failures. This skill prevents this by enforcing a mandatory process that validates all SQL queries with execute_sql before production deployment.

What do I need to provide to automate Databricks dashboard creation and deployment?▼

To automate Databricks dashboard creation and deployment, you need to provide a validated dataset. The automation then produces and deploys the dashboard after SQL testing, handling schema inspection, query validation, JSON construction, and production deployment.

Does this dashboard deployment workflow support custom widget and dataset naming?▼

Yes, this dashboard deployment workflow meets strict requirements for dataset naming, query validation via execute_sql, dashboard JSON construction, and deployment via create_or_update_dashboard, ensuring properly configured widgets and datasets.