Motherduck Build Dashboard

---
name: motherduck-build-dashboard
description: Build a live MotherDuck dashboard as a Dive. Use when composing one shareable KPI, trend, and breakdown story over existing MotherDuck data, especially when the result should stay a saved workspace artifact rather than a full application.
license: MIT
---

# Build an Analytics Dashboard

Use this skill when the user wants a multi-section Dive-backed dashboard with a clear analytical story, not just a single chart.

This is a use-case skill. It orchestrates `motherduck-explore`, `motherduck-query`, `motherduck-manage-guides`, `motherduck-create-dive`, and `motherduck-design-dive`; use `motherduck-duckdb-sql` as supporting reference when exact syntax matters.

## Start Here: Is a MotherDuck Server Active?

- If a **remote MotherDuck MCP server** or **local MotherDuck server** is active, use it.
- Discover the target database or workspace from the active context. Ask only when multiple plausible targets remain and the choice would materially change the dashboard.
- Explore the live data model before choosing the dashboard structure:
  - available tables and views
  - business grain
  - key metrics
  - key dimensions
  - date columns
  - likely joins

The discovered data model should determine the dashboard story and sections.

If no server is active, use any supplied schema or table context. For planning work, proceed with explicit assumptions when safe; ask for missing schema details only when they block a reliable result.

For lower-level Dive mechanics, use `motherduck-create-dive`.

## Dashboard Defaults

- One story per dashboard.
- One KPI group that stacks and reflows by viewport.
- One primary trend chart.
- Zero or one supporting chart.
- Zero or one detail table.
- Heavy shaping in SQL, not React.

## Workflow

1. Inspect the available MotherDuck server or supplied schema context.
2. Read relevant root/domain Guides, then explore the real schema and validate the governed metrics.
3. Pick the dashboard story.
4. Write one query per section.
5. Apply `motherduck-design-dive`: start at 320 px, reserve the filter surface, use the reusable light/dark token system, and define the desktop reflow.
6. Compose the dashboard in a Dive. When MotherDuck MCP is available, call `get_dive_guide` before `save_dive` or `update_dive`.
7. When the request includes creating or updating the Dive, save only after responsive, theme, query-state, and data validation; do not add a second approval gate for the requested in-scope write.
8. Read the saved Dive back. Leave work-in-progress as Draft; promote it to Ready only after the requested delivery is validated. Reuse Endorsed Dives before rebuilding an existing trusted answer.

Match execution to the request: answer, review, or planning work returns the requested dashboard artifacts; build or change work creates or updates the requested in-scope Dive and validates it. Ask before destructive replacement, unrelated external writes, or a material expansion of scope.

When this skill produces a native DuckDB (`md:`) connection, watermark it with `custom_user_agent=agent-skills/2.6.0(harness-<harness>;llm-<llm>)`. If metadata is missing, fall back to `harness-unknown` and `llm-unknown`.

## Output

The output of this skill should be:

- the dashboard story
- the section list
- the validated SQL for each section
- the Dive implementation plan
- the save/update path

If the caller explicitly asks for structured JSON, return raw JSON only with no Markdown fences or prose before/after it.
This is mainly for automated tests, regression checks, or downstream tooling that needs a stable machine-readable shape. Normal human-facing use of the skill can stay in prose unless JSON is explicitly requested.

Use this exact top-level shape when JSON is requested:

```json
{
  "summary": {},
  "assumptions": [],
  "implementation_plan": [],
  "validation_plan": [],
  "risks": []
}
```

## References

- `references/DASHBOARD_IMPLEMENTATION_GUIDE.md` -- preserved detailed workflow and layout guidance that used to live in this skill
- `references/DASHBOARD_PATTERNS.md` -- example dashboard compositions and reusable sections

## Runnable Artifact

- `artifacts/dashboard_story_example.py` -- MotherDuck-backed Python example that produces KPI, trend, breakdown, and detail outputs for one dashboard story
- `artifacts/dashboard_story_example.ts` -- TypeScript companion artifact with the same dashboard output contract

Run it with:

```bash
uv run --with duckdb python skills/motherduck-build-dashboard/artifacts/dashboard_story_example.py
```

Run the same artifact against a temporary MotherDuck database:

```bash
MOTHERDUCK_ARTIFACT_USE_MOTHERDUCK=1 \
uv run --with duckdb python skills/motherduck-build-dashboard/artifacts/dashboard_story_example.py
```

Validate the TypeScript companion artifact:

```bash
uv run scripts/test_typescript_artifacts.py
```

## Related Skills

- `motherduck-explore` -- inspect the actual database before deciding the dashboard sections
- `motherduck-query` -- validate each dashboard query
- `motherduck-create-dive` -- useSQLQuery, theming, preview/save, loading, and visual mechanics
- `motherduck-design-dive` -- responsive layout, filter capacity, light/dark tokens, reusable components, and visual QA
- `motherduck-duckdb-sql` -- resolve syntax and function questions