motherduck-query · git:20260827.1ff9a10 · 2026-08-27 · sha256 7919c48ea0b41492

motherduck-query git:20260827.1ff9a10A

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---
name: motherduck-query
description: Execute DuckDB SQL queries against MotherDuck databases. Use when running analytics, aggregations, transformations, or any SQL operation. Covers query best practices, CTEs, window functions, QUALIFY, and performance optimization.
license: MIT
---

# Query MotherDuck

Use this skill when executing SQL queries for analytics, aggregations, transformations, or data exploration against MotherDuck databases.

## Prerequisites

- An established MotherDuck connection (or an active MotherDuck MCP server)
- Target database and tables identified

## Default Posture

- When MotherDuck MCP is available and the query answers a business question, call `get_query_guide` before writing SQL. Traverse only relevant topics and validate Guide claims against the live schema.
- Write DuckDB SQL, not PostgreSQL SQL, even when using the PG endpoint.
- Always use fully qualified `"database"."schema"."table"` names.
- Preserve the intended grain of every result set; state the grain before optimizing or materializing a query.
- Filter early, aggregate early, and prefer serving tables or summaries for repeated reads.
- Keep SQL obvious, multi-line, and explicit about grain, filters, and output shape.
- Treat DDL, DML, `ATTACH`, `DETACH`, recovery commands such as `CREATE SNAPSHOT`, `ALTER DATABASE ... SET SNAPSHOT`, `UNDROP DATABASE`, and lifecycle commands such as `SHUTDOWN` as writes. Use the MotherDuck MCP `query_rw` tool when the user's change request authorizes the write. Ask for confirmation only when the action is destructive, externally visible, or outside the stated scope.
- Tag long-lived integrations with `custom_user_agent` when the connection path supports it.

## Workflow

1. Confirm the actual tables, columns, and grain before writing SQL.
2. Load relevant Guide context when MCP is available, without treating it as a substitute for schema inspection.
3. Write the query in SQL first, then wrap it in Python or TypeScript only if needed.
4. Use CTEs and DuckDB-native patterns such as `GROUP BY ALL`, `QUALIFY`, and `arg_max`.
5. Check the plan, row count, and shape for pushdown, unnecessary sorts, or repeated raw rescans.
6. Materialize expensive repeated queries into serving tables or light views when warranted.

## Open Next

- Read `references/QUERY_PLAYBOOK.md` for DuckDB query patterns, exploration SQL, performance rules, common analytical shapes, and common mistakes

## Related Skills

- `motherduck-connect` for session setup
- `motherduck-duckdb-sql` for syntax and function reference
- `motherduck-explore` for understanding the source schema before writing queries
- `motherduck-manage-guides` when semantic definitions or reusable query rules need to be read or maintained