Motherduck enable self serve analytics

Skill motherduckdb/agent-skills/plugins/motherduck-skills-claude/skills/motherduck-enable-self-serve-analytics

Opinionated AI agent skills for building applications with MotherDuck

Install

npx -y skills add motherduckdb/agent-skills --skill motherduck-enable-self-serve-analytics

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What its author says it does

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Roll out self-serve analytics on MotherDuck for internal teams. Use when deciding the first governed dataset, the first Dive or share, ownership boundaries, and the rollout path from one audience to broader adoption.

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

4.6 KB, as published. Nobody here has run it

Enable Self-Serve Analytics

Use this skill when the user wants broad internal access to analytics with clear guardrails, trusted datasets, and a practical rollout path.

This is a use-case skill. It orchestrates motherduck-explore, motherduck-query, motherduck-model-data, motherduck-create-dive, and motherduck-share-data.

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 rollout.
Explore the live data model before defining the rollout:
- trusted source tables
- candidate curated views
- department-level dimensions
- core KPIs
- share boundaries

Use the actual data model to pick the first audience and first asset.

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

Rollout Defaults

first audience first, not company-wide exposure
curated dataset before broad access
Dive or share boundary over raw table dumping
standard ownership for metric changes
lightweight metric definitions and owners before inviting more users

Workflow

Inspect the available MotherDuck server or supplied schema context.
Inspect the data model that internal teams would use.
Pick the first audience and first use case.
Publish one trusted dataset.
Document the metric owner, refresh expectation, and access boundary.
Publish one Dive or one share.
Expand only after the first workflow is stable.

Match execution to the request: answer, review, or planning work returns the requested rollout artifacts; build or change work creates the requested in-scope dataset, Dive, or share and validates it. Ask before broader access grants, destructive changes, or external writes not already authorized.

When this skill produces a native DuckDB (md:) connection, watermark it with custom_user_agent=agent-skills/2.4.0(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 first audience
the first asset
the governing dataset
the ownership model
the rollout guardrails

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:

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

References

Read this as reference, not as a script to execute:

references/SELF_SERVE_ROLLOUT_GUIDE.md -- curate-publish-expand sequence, Dive-versus-share choice, data freshness checks, scale guidance, and starter snippets

Runnable Artifact

artifacts/self_serve_rollout_example.py -- MotherDuck-backed Python example that publishes a curated view and produces team KPI output for a first rollout asset
artifacts/self_serve_rollout_example.ts -- TypeScript companion artifact with the same rollout output contract

Run it with:

uv run --with duckdb python skills/motherduck-enable-self-serve-analytics/artifacts/self_serve_rollout_example.py

Run the same artifact against a temporary MotherDuck database:

MOTHERDUCK_ARTIFACT_USE_MOTHERDUCK=1 \
uv run --with duckdb python skills/motherduck-enable-self-serve-analytics/artifacts/self_serve_rollout_example.py

Validate the TypeScript companion artifact:

uv run scripts/test_typescript_artifacts.py

Related Skills

motherduck-explore -- inspect the real workspace before rollout
motherduck-query -- validate KPI definitions
motherduck-model-data -- publish curated analytical views or tables
motherduck-create-dive -- build the first shareable answer surface
motherduck-share-data -- publish governed data access when users need SQL, not just a Dive