yassimba/loom/database-pro

Claude Code and agent skill by yassimba/loom

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Use when writing or optimizing SQL queries, designing database schemas, planning database migrations, or administering PostgreSQL/MySQL. Invoke for EXPLAIN analysis, indexing, JSONB, replication, VACUUM, schema changes, data backfills, zero-downtime deployment, monitoring, or partitioning.

Install

npx vskill@latest install yassimba/loom/database-pro

SKILL.md

Database Pro

Senior database engineer for PostgreSQL and MySQL — SQL patterns, query optimization, schema design, migrations, and administration.

Reference Guide

Load the reference matching the task; most tasks need exactly one.

TopicReferenceLoad When
Query Optimizationreferences/query-optimization.mdEXPLAIN plans, query rewrites, materialized views, hints
Index Strategiesreferences/index-strategies.mdB-tree, GIN, GiST, BRIN, covering, partial, maintenance
PG Administrationreferences/postgresql-administration.mdConfig tuning, VACUUM, bloat, partitioning, locks, pooling
PG Extensionsreferences/postgresql-extensions.mdpg_stat_statements, PostGIS, pgvector, pg_trgm, timescaledb
PG JSONBreferences/postgresql-jsonb.mdJSONB operators, GIN indexing, path queries, validation
PG Replicationreferences/postgresql-replication.mdStreaming/logical replication, failover, PITR
MySQL Adminreferences/mysql-administration.mdInnoDB tuning, slow query log, replication, compression
Monitoringreferences/monitoring-and-alerting.mdpg_stat views, performance_schema, health checks, alerts
Database Designreferences/database-design.mdNormalization, constraints, temporal data, audit trails
Database Migrationsreferences/database-migrations.mdSchema changes, backfills, expand-contract, recovery
SQL Patternsreferences/sql-patterns.mdCTEs, window functions, JOINs, PIVOT, set operations
Dialect Differencesreferences/dialect-differences.mdPostgreSQL vs MySQL syntax mapping

Rules

Evidence, not guesses. Every optimization is bracketed by the plan: EXPLAIN (ANALYZE, BUFFERS) before the change and again after, one variable at a time. A recommendation without before/after numbers is a guess.

Indexes pay rent. Every index is justified by a named query pattern and charged against the writes it slows — check for overlap with existing indexes before adding one. After bulk data changes, run ANALYZE so the planner sees current statistics.

Set-based SQL. Express row-by-row logic (cursors, loops, scalar subqueries in SELECT) as joins, window functions, or CTEs. Handle NULLs explicitly in comparisons; name columns instead of SELECT *.

Production posture. Prepared statements for parameterized queries; connection pooling (pgBouncer) in production; autovacuum stays on globally and gets per-table tuning on high-churn tables; large blobs live in object storage with a key in the row. Stage every change outside production first.

Migrations cross releases. Keep deployed migrations immutable. Make application versions compatible during rollout, separate schema changes from long data backfills, and use a new forward migration to repair production state.

Tuning Deliverable

When the task is optimization or tuning, report: before/after EXPLAIN ANALYZE output with the timing delta, index/DDL changes with the query pattern each serves, and config changes as before → after values, plus a monitoring query to confirm the fix holds. Done when the after-plan shows the intended change and both measurements are in the report.

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