Data Studio dashboards

The Data Studio feature lets Claude build charts and dashboards in RUCKUS One’s Data Studio — the Apache Superset console over Druid — without you touching the UI. A published dashboard is a first-class deliverable: you ask for it in conversation, and a human opens it in Data Studio afterwards.

This is an Early Access feature: unlock Early Access, then turn it on in the Early Access card of the dashboard. Its toggles appear once the password is accepted; the Features card holds only the generally available features.

No extra credential is involved. The tools drive Data Studio with the same RUCKUS bearer token R1-MCP already mints from your connection.

Every Data Studio tool except the two notes tools takes an optional connection (label or id). With more than one connection enabled you must name one, or the call returns connection_required; with no connection at all it returns no_connection.

The build order that works

Doing these out of order is the main way a dashboard comes out empty or broken:

1. Discover the dataset — ds_list_datasets, then ds_dataset_fields. Dataset ids are per-tenant integers and must always be discovered, never assumed.
2. Validate the query — ds_query runs a Superset query without saving anything, so you can see real venue data and refine metrics, filters, and scope before committing.
3. Create the dashboard shell — ds_build_dashboard.
4. Create each chart attached to it — ds_build_chart with dashboards: [<dashboard id>].
5. Lay it out and publish — ds_update_dashboard with positionJson, and published: true.
6. Check it renders — ds_diagnose_charts.

Caution

Attaching a chart is what creates dashboard membership. Referencing chart ids inside positionJson does not register them as members, and those charts will not render. Each chart must be created (or updated) with dashboards: [<dashboard id>]. When a positionJson references non-member charts, the response carries a membershipWarning naming them.

ds_build_chart checks two things before it writes:

• The dataset id must agree across datasourceId, params.datasource, and the query context. If they differ, the write is refused with datasource_id_mismatch — such a chart would save but render empty.
• The viz type is checked against a list of types known to render. A type that is known not to render, or isn’t on the list, gets a vizTypeWarning. The chart still saves, so read the warning.

Dashboard calls return a dashboardUrl — the link to open the dashboard in Data Studio.

RUCKUS’s chart limits

RUCKUS enforces performance guardrails on every Data Studio chart and dashboard. A chart outside them errors on save or render, so reduce it rather than retrying:

Limit	Value
Dimensions per chart	At most 6 (DATASTUDIO-20010); 3–4 performs best
Time range	At most 31 days — use Last month, not Last quarter
Time grain	Must be one supported for the chosen range
Unpaginated table	At most 500 rows — enable server pagination for more
Charts per dashboard	At most 40 across all tabs; 20 or fewer recommended

New dashboards are drafts

A newly created dashboard defaults to draft, and a draft is visible only to its owner — which is the API client, not you. If you look in Data Studio and the dashboard isn’t there, this is almost always why.

Pass published: true — on ds_build_dashboard at creation, or on ds_update_dashboard afterwards — to make it visible to everyone in the tenant.

Charts and dashboards created this way are API-managed: the API client owns them, and they show as “Modified by Application …” in the UI. You can still add them to your own dashboards there. Only API-owned charts and dashboards can be updated or deleted through these tools; anything else returns 403 or 404, passed through for you to inspect. ds_list_dashboards likewise sees only the dashboards the API client owns, not ones you built by hand.

Caution

You can’t delete API-managed charts or dashboards in the Data Studio UI. ds_delete_chart and ds_delete_dashboard are the only way to clean them up, and deleting a dashboard leaves its charts in place — delete those separately.

The 16 tools

Group	Tools
Discovery	ds_list_datasets, ds_dataset_fields
Ad-hoc query	ds_query
Authoring	ds_build_chart, ds_build_dashboard
Diagnosis	ds_diagnose_charts
Learned notes	ds_save_note, ds_list_notes
Chart lifecycle	ds_list_charts, ds_get_chart, ds_update_chart, ds_delete_chart
Dashboard lifecycle	ds_list_dashboards, ds_get_dashboard, ds_update_dashboard, ds_delete_dashboard

ds_dataset_fields returns each column and named metric with its format — the d3-format or unit string such as BPS, BYTES, or ,.2%. That’s what resolves axis units and the fraction-versus-percent question, so it’s worth asking for when a chart’s numbers look wrong by a factor of 100.

When a chart saves but won’t render

A chart can save successfully, and its bare query can pass ds_query, and it still throws “Unexpected Error” in the Data Studio UI. That happens when a render-time field is invalid — the classic case being an annotation_layers entry missing the required showMarkers, which is only validated once the render injects the layers into the query.

ds_diagnose_charts reproduces the real render: it replays each chart’s query context with its annotation layers injected, and reports Superset’s own error verbatim plus a recognition hint for known classes. It is read-only.

Point it at a specific dashboardId after building a dashboard — that checks exactly that dashboard’s member charts, with no tenant-wide noise.

Failed ds_query calls surface the same way: the response carries a top-level queryErrors array holding Superset’s own error text, which usually names the offending column or metric.

Notes that survive the conversation

ds_save_note records a quirk you or Claude worked out — a viz type that needs a particular field, a post-processing shape Superset insists on — under a free-form topic. Notes are private to your account and resurface automatically on ds_list_notes and on the data-studio reference doc, so a hard-won discovery isn’t re-learned next session.

See also

• Bundled reference docs — the data-studio recipe and caveats
• Features and feature flags — unlocking Early Access
• Multiple connections — which tenant’s Data Studio you’re building in