sql-optimization-patterns

Diagnose slow SQL with query plans, preserve query results, and verify indexing or query changes against representative data.

By sickn33 · 393 installs

npx skills add sickn33/agentic-awesome-skills --skill sql-optimization-patterns

Source repository · Upstream listing

SQL Optimization Patterns Diagnose slow SQL with query plans, preserve query results, and verify indexing or query changes against representative data. Use this skill when Debugging slow running queries Designing performant database schemas Optimizing application response times Reducing database load and costs Improving scalability for growing datasets Analyzing EXPLAIN query plans Implementing efficient indexes Resolving N+1 query problems Do not use this skill when The task is unrelated to sql optimization patterns You need a different domain or tool outside this scope Instructions Confirm database engine/version, query parameters, expected rows, data distribution and the permitted environment. Start read only; obtain authorization before DDL, data changes, configuration changes or maintenance. Compare result sets before comparing performance. EXPLAIN ANALYZE executes the statement: use approved representative data, account for functions and triggers, and do not assume a transaction rollback undoes every side effect. Record the observed plan, timing conditions and correctness checks. Indexes and query rewrites are hypotheses, not universal speed improvements. If detailed examples are required, open resources/implementation playbook.md . Resources resources/implementation playbook.md for detailed patterns and examples. Limitations Use this skill only when the task clearly matches the scope described above. Do not treat the output as a substitute for environment specific validation, testing, or expert review. Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing. Worked example The playbook includes an executable SQLite batch loading example with bound values and an empty input case. The repository test exercises it alongside pagination ties and aggregation equivalence. SQLite correctness checks do not establish PostgreSQL performance or production safety.