databricks-agent-brick…
Create Agent Bricks: Knowledge Assistants (KA) for document Q&A and Supervisor Agents for…
Create Databricks AI/BI dashboards. Must use when creating, updating, or deploying Lakeview dashboards as Databricks Dashboard have a unique json structure. CRITICAL: You MUST test ALL SQL queries via CLI BEFORE deploying. Follow guidelines strictly.
$ npx -y skills add databricks/databricks-agent-skills --skill databricks-aibi-dashboards --agent claude-codeHow it fires
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Create Databricks AI/BI dashboards. Must use when creating, updating, or deploying Lakeview dashboards as Databricks Dashboard have a unique json structure. CRITICAL: You MUST test ALL SQL queries via CLI BEFORE deploying. Follow guidelines strictly.
name: databricks-aibi-dashboards description: "Create Databricks AI/BI dashboards. Must use when creating, updating, or deploying Lakeview dashboards as Databricks Dashboard have a unique json structure. CRITICAL: You MUST test ALL SQL queries via CLI BEFORE deploying. Follow guidelines strictly." compatibility: Requires databricks CLI (>= v1.0.0) metadata: version: "0.2.1" parent: databricks-core
Create Databricks AI/BI dashboards (formerly Lakeview dashboards). A dashboard should be showing something relevant for a human, typically some KPI on the top, and based on the story, some graph (often temporal), and we see "something happens". **Follow these guidelines strictly.**
> **When a custom app fits better:** A managed AI/BI dashboard is the right tool for read-only KPIs, charts, and filters over governed tables. If the user instead needs a *custom-code interactive app* — write-back / data entry, bespoke UI or interactions beyond the dashboard grid, embedded or auth-gated workflows, or a conversational Genie/chat assistant as the primary surface — build a Databricks App instead with the `databricks-apps` skill (which brings in `databricks-app-design` for the data-screen UX). Linking an "Ask Genie" space to *this* dashboard stays here (see Linking a Genie Space below).
| Task | Command | |------|---------| | List warehouses | `databricks warehouses list` | | List tables | `databricks experimental aitools tools query --warehouse WH "SHOW TABLES IN catalog.schema"` | | Get schema | `databricks experimental aitools tools discover-schema catalog.schema.table1 catalog.schema.table2` | | Test query | `databricks experimental aitools tools query --warehouse WH "SELECT..."` | | Create dashboard | `databricks lakeview create --display-name "X" --warehouse-id "WH" --dataset-catalog CATALOG --dataset-schema SCHEMA --serialized-dashboard "$(cat file.json)" --json '{"parent_path": "/Workspace/Users/<you>/path"}'` — `--dataset-catalog` / `--dataset-schema` are **flag-only** (REQUIRED; CLI silently drops them if put in `--json`); `parent_path` is JSON-only (no flag). Queries must use bare table names. | | Update dashboard | `databricks lakeview update DASHBOARD_ID --dataset-catalog CATALOG --dataset-schema SCHEMA --serialized-dashboard "$(cat file.json)"` — **always re-pass `--dataset-catalog` / `--dataset-schema` on update** (same flag-only rule as create); update replaces the serialized dashboard, so omitting them nulls the per-dataset defaults and breaks every bare-table query. | | Publish | `databricks lakeview publish DASHBOARD_ID --warehouse-id WH` | | Delete | `databricks lakeview trash DASHBOARD_ID` |
> **`--warehouse` flag**: if `databricks experimental aitools tools query --warehouse WH "..."` fails with `unknown flag: --warehouse` on your CLI version, set `DATABRICKS_WAREHOUSE_ID=WH` in the environment instead and drop the flag — the command auto-picks it from there.
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> **Wrong version = broken widget!** This is the #1 cause of dashboard errors.
| Widget Type | Version | Documented in | |-------------|---------|---------------| | text (markdown, no spec block) | N/A | [1-widget-specifications.md#text-headersdescriptions](references/1-widget-specifications.md#text-headersdescriptions) | | `counter` (KPI + sparkline + comparison) | **2** | [1-widget-specifications.md#counter-kpi](references/1-widget-specifications.md#counter-kpi) | | `table` | **2** | [1-widget-specifications.md#table](references/1-widget-specifications.md#table) | | `bar`, `line` | **3** | [1-widget-specifications.md#line--bar-charts](references/1-widget-specifications.md#line--bar-charts) | | `pie` | **3** | [1-widget-specifications.md#pie-chart](references/1-widget-specifications.md#pie-chart) | | `symbol-map` (lat/lon point map) | **2** | [1-widget-specifications.md#symbol-map-bubble-map](references/1-widget-specifications.md#symbol-map-bubble-map) | | `area` | **3** | [2-advanced-widget-specifications.md#area-chart](references/2-advanced-widget-specifications.md#area-chart) | | `scatter` | **3** | [2-advanced-widget-specifications.md#scatter-plot--bubble-chart](references/2-advanced-widget-specifications.md#scatter-plot--bubble-chart) | | `combo` (bar+line, dual-axis) | **1** | [2-advanced-widget-specifications.md#combo-chart-bar--line](references/2-advanced-widget-specifications.md#combo-chart-bar--line) | | `choropleth-map` (regions colored by value) | **1** | [2-advanced-widget-specifications.md#choropleth-map](references/2-advanced-widget-specifications.md#choropleth-map) | | `forecast-line` (with `AI_FORECAST` SQL) | **1** | [2-advanced-widget-specifications.md#forecast-line-with-ai_forecast](references/2-advanced-widget-specifications.md#forecast-line-with-ai_forecast) | | `pivot` (with conditional cell rules) | **3** | [2-advanced-widget-specifications.md#pivot](references/2-advanced-widget-specifications.md#pivot) | | `histogram` (with `bin(col, binWidth=N)`) | **3** | [2-advanced-widget-specifications.md#histogram](references/2-advanced-widget-specifications.md#histogram) | | `sankey` | **1** | [2-advanced-widget-specifications.md#sankey](references/2-advanced-widget-specifications.md#sankey) | | `heatmap` | **3** | [2-advanced-widget-specifications.md#heatmap](references/2-advanced-widget-specifications.md#heatmap) | | `funnel` | **1** | [2-advanced-widget-specifications.md#funnel](references/2-advanced-widget-specifications.md#funnel) | | `box` | **1** | [2-advanced-widget-specifications.md#box](references/2-advanced-widget-specifications.md#box) | | `waterfall` | **1** | [2-advanced-widget-specifications.md#waterfall](references/2-advanced-widget-specifications.md#waterfall) | | `filter-single-select`, `filter-multi-select`, `filter-date-range-picker` | **2** | [3-filters.md#filter-widget-structure](references/3-filters.md#filter-widget-structure) | | `range-slider` | **2** | [3-filters.md#range-slid
Build on Databricks with AI coding agents such as Claude Code, Cursor, Codex, and GitHub Copilot. This repository provides the skills and agent plugins for Databricks AI Tools.
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