WHEN: Database schema review, table design, normalization, constraints, index planning WHAT: Normalization analysis + Constraint validation + Index strategy + Data types + Relationship design WHEN NOT: Query optimization → sql-optimizer, ORM code → orm-reviewer
Detailed rules for SQL schema, 3NF normalization, RLS, and Triggers.
Execute SQL queries and data modifications on PostgreSQL databases running in Docker containers. Auto-detects running PostgreSQL containers and executes SELECT, INSERT, UPDATE, and DELETE operations. Use when working with PostgreSQL databases in containers for querying data, modifying records, analyzing database contents, or performing ad-hoc database operations. Triggers on database queries, SQL operations, data inspection, or PostgreSQL interactions.
Generate safe PostgreSQL queries from natural language. Supports three databases (small, medium, large) with automatic schema detection. Only generates SELECT queries - no writes, no dangerous operations.
Write optimized and secure database queries using parameterized queries, eager loading, strategic indexing, and proper transaction management. Use this skill when writing database queries, repository methods, or data fetching logic that interacts with SQL or NoSQL databases. Use when implementing query builders, ORM query methods, raw SQL queries, or database service functions. Use when working with files containing database access code (repositories.ts, services.ts, queries.py, dao.java), when optimizing N+1 query problems, implementing query caching strategies, or writing queries with JOINs and WHERE clauses. Use when preventing SQL injection vulnerabilities, setting up query timeouts, or wrapping related operations in database transactions.
Configures and manages database connection pools, with a focus on SQLAlchemy. Use this skill for tasks involving connection pool configuration, sizing, lifecycle management, health checks, and monitoring. It provides specialized guidance for both traditional server-based databases and serverless databases like Neon and PlanetScale.
Use when editing .sql files, reviewing SQL in Python/JavaScript/TypeScript code, writing database queries, or when user mentions PostgreSQL, SQL validation, query optimization, or database schema.
DynamoDB single-table design using dynamodb-toolbox v2. Use when creating entities, defining key patterns, designing GSIs, writing queries, implementing pagination, or working with any DynamoDB data layer in TypeScript projects.
SQL migrations and stored procedures management in the tools bounded context. Trigger: Creating migrations, procedures, functions, triggers, or sequences for PostgreSQL.
PostgreSQL database patterns for Neon serverless database. Use when configuring database connections, writing queries, or optimizing PostgreSQL for the Todo backend.
Create and manage database migrations following best practices for reversibility, zero-downtime deployments, and version control. Use this skill when creating migration files, modifying database schemas, adding or removing tables/columns, managing indexes, or performing data transformations. Apply when working on migration files (migrations/*.ts, migrations/*.sql, *_migration.py), Prisma schema changes, Supabase migrations, or any database evolution tasks. This skill ensures reversible migrations with rollback/down methods, small focused single-change migrations, zero-downtime deployment compatibility, separated schema and data migrations, safe concurrent index creation on large tables, clear descriptive naming conventions, and proper version control practices (never modify deployed migrations).
Expert guidance for SQLModel - the Python library combining SQLAlchemy and Pydantic for database models. Use when (1) creating database models that work as both SQLAlchemy ORM and Pydantic schemas, (2) building FastAPI apps with database integration, (3) defining model relationships (one-to-many, many-to-many), (4) performing CRUD operations with type safety, (5) setting up async database sessions, (6) integrating with Alembic migrations, (7) handling model inheritance and mixins, or (8) converting between database models and API schemas.
ALWAYS USE when working with Iceberg table storage, ACID transactions, or time-travel queries. Use IMMEDIATELY when creating/loading Iceberg tables, implementing schema evolution, querying historical snapshots, or debugging catalog operations. Provides research steps for PyIceberg SDK, catalog integration, and storage layer operations.
Guide for creating database tables with Drizzle ORM migrations and repository pattern
Checks database schema integrity and data consistency, specifically focusing on critical columns and legacy data migration.
Automated PostgreSQL DB construction and SQL testing for immutable data models. Sets up PostgreSQL container with project-specific schema/data, executes all queries, and generates comprehensive test reports. Use when validating DDL generation results or testing query examples against real database. Triggers include "PostgreSQLで検証", "SQLをテスト", "クエリを実行", "データベースで動作確認", "DDLを検証".
Learn from database query patterns and recommend optimized approaches
Write secure, performant database queries using parameterized queries, proper eager loading, and transaction management. Use this skill when writing database queries, ORM operations, raw SQL statements, or repository methods. When working on files in repositories/, queries/, services/, or any code that interacts with the database. When optimizing query performance, preventing N+1 queries, implementing transactions, adding query timeouts, or caching expensive queries. When reviewing code for SQL injection vulnerabilities.
Single table design patterns for DynamoDB with SST - modeling complex data relationships in a single table for optimal performance and cost
Write secure, performant database queries using parameterized statements, proper indexing, eager loading, and transaction management to prevent SQL injection and N+1 query problems. Use this skill when writing database queries, constructing SQL statements, using ORM query builders, optimizing database performance, or working with repositories, services, or DAO files that interact with databases. Applies to SELECT, INSERT, UPDATE, DELETE operations, joins, aggregations, and any code that retrieves or manipulates data from databases.
Generate comprehensive dbt test suites following FF Analytics data quality standards and dbt 1.10+ syntax. This skill should be used when creating tests for new dbt models, adding tests to existing models, standardizing test coverage, or implementing data quality gates. Covers grain uniqueness, FK relationships, enum validation, and freshness tests.
