motherduck-build-cfa-a…
Build MotherDuck analytics into customer-facing applications with tenant isolation, backend routing, and serving APIs.
Build a MotherDuck dashboard as a Dive, choosing the analytical story, metrics, and section queries.
$ npx -y skills add motherduckdb/agent-skills --skill motherduck-build-dashboard --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/motherduck-build-dashboardContext preview
The summary Claude sees to decide when to auto-load this skill.
Build a MotherDuck dashboard as a Dive, choosing the analytical story, metrics, and section queries.
name: motherduck-build-dashboard description: Build a MotherDuck dashboard as a Dive, choosing the analytical story, metrics, and section queries. license: MIT
Use an active remote MotherDuck MCP server or local MotherDuck server to inspect the in-scope database, schema, grain, keys, and relevant metrics. Reuse known context and narrow discovery to the requested work; do not scan the whole workspace by default. Let the actual data model shape the result.
Resolve the target from the request or active context. Ask only if ambiguity materially affects the result. Without a server, use supplied schema and explicit assumptions for planning; do not imply live validation.
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. For a new dashboard or layout change, use the responsive and theme guidance in `motherduck-design-dive`; preserve the existing design for a scoped SQL or text edit. 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`.
For a full engagement, cover the following as relevant to the request:
For explicit structured JSON requests, read [the output contract](references/EXECUTION_REFERENCE.md#structured-output). Otherwise use the format that fits the requested deliverable.
Read only the sections relevant to the task; these are guidance, not a mandatory itinerary.
Read [the execution reference](references/EXECUTION_REFERENCE.md) only to run the bundled examples or reproduce their validation.
Load related skills only for missing capabilities; reuse established context.
Opinionated AI agent skills for building applications with MotherDuck
Repo: motherduckdb/agent-skills
Build MotherDuck analytics into customer-facing applications with tenant isolation, backend routing, and serving APIs.
Build ingestion-to-serving pipelines on MotherDuck, including stage boundaries, transformations, and publication.
Use the MotherDuck CLI for terminal queries, authentication, and file-based Dive or Flight workflows.
Set up or troubleshoot MotherDuck connections, authentication, client runtimes, and read scaling.
Create, edit, publish, share, or embed MotherDuck Dives using their React and SQL runtime.
Create, run, schedule, or debug MotherDuck Flights, Python jobs executed on MotherDuck compute.