Teach cursor pagination, index documentation, and bulk updates for SQL and ORM queries.
npx skills add https://github.com/Corvalis-LLC/Crow-Stack --skill auto-database
Please help me install this Agent Skill. Skill: auto-database Source: https://github.com/Corvalis-LLC/Crow-Stack/tree/main/skills/auto-database Command: npx skills add https://github.com/Corvalis-LLC/Crow-Stack --skill auto-database
Addresses common database query anti-patterns that cause slow production queries, excessive round-trips, and resource waste, such as OFFSET pagination, N+1 queries, and row-by-row updates.
Audit your current queries for OFFSET usage and missing indexes, then refactor to keyset pagination and bulk updates.
High-intent search queries and answers about installing and using this skill.
To optimize database queries and fix slow OFFSET pagination, refactor to cursor or keyset pagination. This approach stabilizes ordering and avoids the performance degradation inherent in OFFSET-based pagination when navigating large datasets.
The best way to avoid N+1 queries and reduce round-trips is implementing bulk operations and explicit column selection instead of SELECT *. This minimizes data transfer and improves backend data-access layer throughput.
To improve SQL query planner performance, ensure explicit column selection and add index documentation comments directly in your code. This guides the planner by clarifying which indexes apply to specific query patterns.
Yes, this database optimization approach works with microservices and large datasets by applying cursor pagination, bulk updates, and minimized round-trips to typical backend data-access layers using SQL and ORM frameworks.
To ensure atomic writes and safe rollbacks during bulk updates, enforce proper transaction boundaries. This maintains data integrity by allowing the system to safely roll back if a bulk operation fails midway.
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