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.
Claude Code
$ npx -y skills add motherduckdb/agent-skills --skill motherduck-build-dashboard --agent claude-code
Codex
$ npx skills add motherduckdb/agent-skills --skill motherduck-build-dashboard -a codex -y
Cursor
$ npx skills add motherduckdb/agent-skills --skill motherduck-build-dashboard -a cursor -y
Gemini CLI
$ npx skills add motherduckdb/agent-skills --skill motherduck-build-dashboard -a gemini-cli -y
GitHub Copilot
$ npx skills add motherduckdb/agent-skills --skill motherduck-build-dashboard -a github-copilot -y
OpenCode
$ npx skills add motherduckdb/agent-skills --skill motherduck-build-dashboard -a opencode -y
Windsurf
$ npx skills add motherduckdb/agent-skills --skill motherduck-build-dashboard -a windsurf -y
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 design defaults and responsive references in `motherduck-create-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 writing Dive code and before every `save_dive`, `update_dive`, or `edit_dive_content`. 7. When the request includes creating or updating the Dive, save only after responsive, theme, query-state, and data validation. Before `save_dive` or `update_dive`, follow the review step that `get_dive_guide` sets for your client: when it asks you to show the final source or preview and get the user's go-ahead, do that once, unless the user already said to save without review. 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/3.0.0(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.
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