databricks-app-design

这段内容是审核时保存的快照。外部来源才是完整且最新的版本。

---
name: databricks-app-design
parent: databricks-apps
description: 'Design the UX of custom-code Databricks Apps (AppKit/React) data screens — KPI/overview pages, reports, charts, tables, and Genie/chat data assistants — mapped to concrete AppKit components. Use when BUILDING or reviewing the UI of an AppKit/React app that displays data or answers data questions: choosing genre, layout, charts, KPIs, semantic color, required states (loading/empty/error), IBCS notation, and AI-result trust (showing generated SQL/sources for Genie/chat). A plain "create a dashboard" request means a managed AI/BI (Lakeview) dashboard → use databricks-aibi-dashboards, NOT this skill. Also NOT for non-data frontend (forms, settings, auth, marketing) or scaffolding/build/deploy (→ databricks-apps). Complements databricks-apps; use it alongside whenever a custom app has a chart, table, KPI, report, or Genie/chat/AI surface.'
metadata:
  version: 0.1.0
---

# Data App Design

Make Databricks data + AI apps that communicate clearly and compile to real AppKit code. This
skill merges two bodies of knowledge and binds them to implementation:

- **Composition** — what to show, how much to abstract, how to lay it out → `references/dashboard-patterns.md`
- **Notation** — make comparable things look comparable; honest scales; scenario marks → `references/ibcs-notation.md`
- **Implementation** — the exact AppKit components, hooks, and tokens to use → `references/appkit-cheatsheet.md`

Design advice that doesn't name a real component is incomplete. Always end at a component plan.

## When to use / when NOT
- USE for: the data screens of a custom-code Databricks App (AppKit/React) — overview/KPI pages, reports, metric/ontology pages, variance analysis, charts, tables, and Genie/NL data surfaces — design *or* critique.
- Do NOT use for: authoring managed **AI/BI (Lakeview) dashboards** (→ `databricks-aibi-dashboards`), generic frontend (forms, auth, settings, marketing), or scaffolding/build/deploy (→ `databricks-apps`). **A plain "create a dashboard" / "build a dashboard" request (no app / AppKit / React / custom-code signal) means a managed AI/BI (Lakeview) dashboard → use `databricks-aibi-dashboards`, not this skill.** If a request is "add a form", "deploy this", or "build a Lakeview / AI-BI dashboard", this skill should not fire.
- Relationship: `databricks-apps` builds/runs the app; this skill decides what the data screens should look like and which primitives realize them.

## Workflow
1. **Frame** — audience, the decision/question, refresh cadence, device, primary task. One sentence.
2. **Genre** — pick the closest from `dashboard-patterns.md` (static / analytic / magazine / infographic / repository / embedded mini). State it.
3. **Compose** — choose content + composition patterns (data abstraction, meta-info, layout, interaction, color). Make the tradeoff explicit: what's summarized, hidden, paginated, or made interactive — and why.
4. **Apply notation** — run the relevant `ibcs-notation.md` rules: message-in-title, scenario marks (actual/PY/plan/forecast), honest scales, semantic color. On any chart-vocabulary conflict, **IBCS wins** (see the conflict note in that file).
5. **Bind to components** — map every element to a primitive that's actually **exported from `@databricks/appkit` / `@databricks/appkit-ui`** (see `appkit-cheatsheet.md`); never cite a component AppKit doesn't ship. There's no prebuilt KPI/trend/distribution card — compose those from primitives, following the notation rules. Use `colorPalette` + semantic tokens, never hardcoded hex. Bind data with `useAnalyticsQuery`/`queryKey` + `sql.*` params.
6. **Cover the states** — every data view must handle loading / empty / error / partial (see checklist).
7. **Review** — run the checklists in both reference files; lead critiques with the highest-impact comprehension or integrity issue, citing the affected component/file.

## Required states & data realism (non-negotiable for data apps)
- **Lo