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JingyiWng
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databricks-aibi-dashboards

Build Databricks AI/BI dashboards by testing SQL queries and assembling widget specifications into JSON.

Updated Mar 25, 2026
Search Tags:#analytics#ai#dashboard#sql#visualization#bi#databricks
One-click install
npx skills add https://github.com/JingyiWng/databricks_ai_dev_kit_price_watcher --skill databricks-aibi-dashboards-jingyiwng
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: databricks-aibi-dashboards
Source: https://github.com/JingyiWng/databricks_ai_dev_kit_price_watcher/tree/main/.claude/skills/databricks-aibi-dashboards
Command: npx skills add https://github.com/JingyiWng/databricks_ai_dev_kit_price_watcher --skill databricks-aibi-dashboards-jingyiwng

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Users often encounter broken Databricks AI/BI dashboards because SQL queries are not validated and widget specifications are misaligned. This Skill ensures dashboards are built with tested queries, strict field naming, and consistent layout, preventing runtime errors and invalid widget definitions.

Core Features & Use Cases

  • Step-by-step workflow: discover table schemas, write and test SQL, construct dashboard JSON, and deploy with validation.
  • Built-in MCP tools such as get_table_details, execute_sql, get_best_warehouse, and create_or_update_dashboard.
  • Enforced widget specifications: version compliance, field-name matching, widget size limits, and 6-column grid layout.
  • Support for counters, tables, line, bar, pie charts, and filter widgets with global or page-level scope.
  • Guidelines for cardinality, layout, and filter configuration to create readable and performant dashboards.

Quick Start

Ask the skill to build a dashboard called “Sales Overview” using your validated SQL queries.

Frequently Asked Questions about databricks-aibi-dashboards

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

FAQPage Schema
How do I build a Databricks AI/BI dashboard without running into broken widgets?▼

Building reliable Databricks AI/BI dashboards requires testing SQL queries and aligning widget specifications before deployment. Validating queries and enforcing strict field-name matching prevents broken dashboards and runtime errors.

What is the workflow for creating Databricks AI/BI dashboards from SQL queries?▼

The dashboard creation workflow involves discovering table schemas, writing and testing SQL, constructing dashboard JSON definitions, and deploying with validation. It uses functions like get_table_details and execute_sql to verify data before assembling widgets.

Can I use filter widgets and different chart types in my Databricks AI/BI dashboards?▼

You can use counters, tables, line, bar, and pie charts alongside filter widgets in Databricks AI/BI dashboards. Filters support global or page-level scope to maintain readability and performance.

Why are my Databricks AI/BI dashboard widgets failing at runtime?▼

Dashboard widgets fail at runtime when SQL queries are not validated and widget specifications are misaligned. Enforcing widget version compliance, strict field-name matching, and widget size limits prevents these invalid widget definition errors.

What layout rules do I need to follow for Databricks AI/BI dashboards?▼

Databricks AI/BI dashboards enforce a mandatory six-column grid layout. Adhering to this layout standard along with widget size limits and cardinality guidelines ensures your dashboard configuration remains readable and performant.

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