drizzle-patterns
Drizzle ORM patterns for SQLite - queries, relations, and safety guidelines. Use when writing database queries or debugging issues.
Drizzle ORM patterns for SQLite - queries, relations, and safety guidelines. Use when writing database queries or debugging issues.
Designs comprehensive database schemas including relational and NoSQL models, normalization, indexing strategies, relationship modeling, data types, constraints, and performance optimization. Covers entity-relationship diagrams, schema migrations, partitioning, and best practices for PostgreSQL, MySQL, MongoDB, and other databases. Use when designing databases, creating schemas, modeling data, optimizing queries, or when users mention "database design", "schema design", "data modeling", "ERD", "normalization", "indexing", or "database architecture".
Designs database schemas, data models, relationships, indexes, and migrations for relational, NoSQL, time-series, and warehouse databases. Covers normalization, denormalization, ETL optimization, event sourcing, star schema, and performance tuning. Trigger keywords: schema, table, column, migration, ERD, normalize, denormalize, index, foreign key, primary key, constraint, relationship, SQL, DDL, data model, database design, data warehouse, star schema, snowflake schema, time-series, event sourcing, dimension table, fact table, ETL, data pipeline, OLAP, OLTP.
Automatically discover database skills when working with SQL, PostgreSQL, MongoDB, Redis, database schema design, query optimization, migrations, connection pooling, ORMs, or database selection. Activates for database design, optimization, and implementation tasks.
Apply NoSQL best practices for MongoDB, Convex, and document databases. Use when designing schemas, writing queries, optimizing performance, or building applications with non-relational databases. Use with database-expert for query optimization and DBA-level tuning (20+ years experience).
Production-grade PostgreSQL query optimization, indexing strategies, performance tuning, and modern features including pgvector for AI/ML workloads. Master EXPLAIN plans, query analysis, and database design for high-performance applications
When working with JSON data in LLM prompts (especially large arrays or tabular data), consider the token-efficient TOON (Token-Oriented Object Notation) format which reduces tokens by 30-70% while maintaining lossless JSON representation and structural validation. Use for reading/writing .toon files, converting JSON↔TOON, or optimizing structured data for LLM consumption with guardrails like [N] counts and {field} headers.
PostgreSQL-native identity, configuration, metering, and job queues. SQL functions that work with any language or driver. Use when working with user management, sessions, permissions, access control, login/logout, MFA, password resets, relationship-based access, versioned configuration, prompts, usage tracking, quotas, billing periods, or background jobs in PostgreSQL. Covers authn (user/session management), authz (ReBAC permissions), config (versioned key-value storage), meter (usage tracking with reservations), and queue (job scheduling with retries and dead letters).
Database design and optimization specialist. Schema design, query optimization, indexing strategies, data modeling, and migration planning for relational and NoSQL databases.
Production-grade SQL optimization for OLTP systems: EXPLAIN/plan analysis, balanced indexing, schema and query design, migrations, backup/recovery, HA, security, and safe performance tuning across PostgreSQL, MySQL, SQL Server, Oracle, SQLite.
Design and manage relational databases including table creation, migrations, and schema design. Use for database modeling and maintenance.
Write and query high-cardinality event data at scale with SQL. Load when tracking user events, billing metrics, per-tenant analytics, A/B testing, API usage, or custom telemetry. Use writeDataPoint for non-blocking writes and SQL API for aggregations.
**Master Skill**: Data Architect for PayU. Expert in PostgreSQL design, Performance Tuning (Indexing/Locking), Flyway migrations, CQRS/Event-Sourcing, TimescaleDB, and high-scale JSONB patterns.
Design and optimize database schemas for SQL and NoSQL databases. Use when creating new databases, designing tables, defining relationships, indexing strategies, or database migrations. Handles PostgreSQL, MySQL, MongoDB, normalization, and performance optimization.
Assists with PostgreSQL database migrations using Alembic. Automatically activates when working with schema changes, table creation, column modifications, index creation, or migration files. Keywords: migration, alembic, schema, database, table, column, index, foreign key
PostgreSQL database patterns for query optimization, schema design, indexing, and security. Based on Supabase best practices.
PostgreSQL database patterns for query optimization, schema design, indexing, and security. Based on Supabase best practices.
This skill should be used when defining a robust, type-safe, and async-compatible database schema for the Todo application using SQLModel, ensuring compatibility with Better Auth and optimized for PostgreSQL.
Guides and best practices for working with Neon Serverless Postgres. Covers getting started, local development with Neon, choosing a connection method, Neon features, authentication (@neondatabase/...
Database patterns for user data and credentials storage
MongoDB schema design patterns and anti-patterns. Use when designing data models, reviewing schemas, migrating from SQL, or troubleshooting performance issues caused by schema problems. Triggers on "design schema", "embed vs reference", "MongoDB data model", "schema review", "unbounded arrays", "one-to-many", "tree structure", "16MB limit", "schema validation", "JSON Schema".