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aibi-dashboards

Create Databricks AI/BI dashboards with validated SQL queries and structured JSON deployment.

Updated Mar 5, 2026
Search Tags:#data visualization#databricks#unity catalog#lakeview#sql validation#dashboard json#aibi dashboards
One-click install
npx skills add https://github.com/FMurray/mlfts --skill aibi-dashboards-fmurray
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: aibi-dashboards
Source: https://github.com/FMurray/mlfts/tree/main/.agents/skills/aibi-dashboards
Command: npx skills add https://github.com/FMurray/mlfts --skill aibi-dashboards-fmurray

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Building Databricks AI/BI (Lakeview) dashboards by hand often produces broken widgets, field name mismatches, and invalid widget definition errors because the dashboard JSON schema has strict versioning, encoding, and layout rules. This Skill enforces a mandatory validate-then-deploy workflow so every SQL query is tested before the dashboard is deployed. ## Core Features & Use Cases - Mandatory SQL validation workflow: Test every dataset query via execute_sql before deploying, preventing broken widgets. - Widget specifications: Correct version and encoding rules for counters (v2), tables (v2), bar/line/pie charts (v3), text headers, and filter widgets. - Layout and filter guidance: 6-column grid layout with no gaps, plus global vs page-level filters using PAGE_TYPE_GLOBAL_FILTERS and PAGE_TYPE_CANVAS. - Use Case: A data analyst needs a KPI dashboard over Unity Catalog sales data with region filters; the Skill walks through schema inspection, query testing, JSON construction, and deployment via create_or_update_dashboard. ## Quick Start Ask the agent to build an AI/BI dashboard on Databricks from a specified Unity Catalog table, including KPI counters, charts, and filters.

Frequently Asked Questions about aibi-dashboards

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

FAQPage Schema
How do I create an AI/BI dashboard on Databricks?▼

First get table schemas with get_table_details, write and test every SQL query via execute_sql, then build the dashboard JSON with datasets, pages, and widgets, and deploy it using create_or_update_dashboard with a warehouse ID.

Why does my Databricks dashboard widget show invalid widget definition?▼

This usually means wrong spec versions: counters, tables, and filters require version 2, while bar, line, and pie charts require version 3. Text widgets must not have a spec block and should use multilineTextboxSpec directly.

How do I fix the no selected fields to visualize error in Lakeview dashboards?▼

The name in query.fields must exactly match the fieldName in encodings. For example, if the field name is sum(spend) with expression SUM(`spend`), the encoding fieldName must also be sum(spend).

What is the difference between global and page-level filters in AI/BI dashboards?▼

Global filters sit on a page with pageType PAGE_TYPE_GLOBAL_FILTERS and affect all pages whose datasets contain the filter field. Page-level filters sit on a PAGE_TYPE_CANVAS page and affect only widgets on that page.

Can I use INTERVAL syntax in Databricks dashboard SQL queries?▼

No, avoid INTERVAL syntax in dashboard datasets. Use Spark SQL functions like date_sub(current_date(), N) for day offsets, add_months for months, and DATE_TRUNC for date truncation instead.

How many categories should a chart dimension have in a Databricks dashboard?▼

Limit chart color or grouping dimensions to 3-8 distinct values for readability. For high-cardinality fields like customer_id or order_id, use a table widget or aggregate into a TOP-N plus Other bucket.

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