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Found 333 Skills
Provides comprehensive Drizzle ORM patterns for schema definition, CRUD operations, relations, queries, transactions, and migrations. Proactively use for any Drizzle ORM development including defining database schemas, writing type-safe queries, implementing relations, managing transactions, and setting up migrations with Drizzle Kit. Supports PostgreSQL, MySQL, SQLite, MSSQL, and CockroachDB.
Creates and scaffolds a new Spring Boot project (3.x or 4.x) by downloading from Spring Initializr, generating package structure (DDD or Layered architecture), configuring JPA, SpringDoc OpenAPI, and Docker Compose services (PostgreSQL, Redis, MongoDB). Use when creating a new Java Spring Boot project from scratch, bootstrapping a microservice, or initializing a backend application.
testcontainers-python specialist. Covers all container modules (PostgreSQL, MySQL, MongoDB, Redis, Kafka, RabbitMQ, MinIO, Elasticsearch, LocalStack), GenericContainer, wait strategies, Docker Compose, networks, pytest fixtures, and CI/CD integration. USE WHEN: user mentions "testcontainers", "docker in tests", "real database in tests", "test with real postgres/redis/kafka", asks about container fixtures or Docker-based testing. DO NOT USE FOR: Spring Boot testcontainers (Java) - use `spring-boot-integration`; Mocking HTTP - use `fastapi-testing`; Pure pytest patterns - use `pytest`
Production-grade backend service development across Node.js (Express/Fastify/NestJS/Hono), Bun, Python (FastAPI), Go, and Rust (Axum), with PostgreSQL and common ORMs (Prisma/Drizzle/SQLAlchemy/GORM/SeaORM). Use for REST/GraphQL/tRPC APIs, auth (OIDC/OAuth), caching, background jobs, observability (OpenTelemetry), testing, deployment readiness, and zero-trust defaults.
SQL query optimization and database performance specialist. Use when optimizing slow queries, fixing N+1 problems, designing indexes, implementing caching, or improving database performance. Works with PostgreSQL, MySQL, and other databases.
Complete knowledge domain for Cloudflare Hyperdrive - connecting Cloudflare Workers to existing PostgreSQL and MySQL databases with global connection pooling, query caching, and reduced latency. Use when: connecting Workers to existing databases, migrating PostgreSQL/MySQL to Cloudflare, setting up connection pooling, configuring Hyperdrive bindings, using node-postgres/postgres.js/mysql2 drivers, integrating Drizzle ORM or Prisma ORM, or encountering "Failed to acquire a connection from the pool", "TLS not supported by the database", "connection refused", "nodejs_compat missing", "Code generation from strings disallowed", or Hyperdrive configuration errors. Keywords: hyperdrive, cloudflare hyperdrive, workers hyperdrive, postgres workers, mysql workers, connection pooling, query caching, node-postgres, pg, postgres.js, mysql2, drizzle hyperdrive, prisma hyperdrive, workers rds, workers aurora, workers neon, workers supabase, database acceleration, hybrid architecture, cloudflare tunnel database, wrangler hyperdrive, hyperdrive bindings, local development hyperdrive
Drizzle ORM documentation covering queries, CRUD operations, schema definitions, migrations, caching (50 topics), custom types, and database connections. Includes integrations for PostgreSQL (Neon, Vercel, Supabase, AWS Data API, PlanetScale, Prisma), MySQL (AWS Data API, PlanetScale, TiDB), and SQLite (Bun, Cloudflare D1/Durable Objects, Expo, Turso, OP SQLite). Use when working with Drizzle queries, database schemas, migrations, type-safe SQL, ORM patterns, or connecting to supported databases.
Complete E2E (end-to-end) and integration testing skill for TypeScript/NestJS projects using Jest, real infrastructure via Docker, and GWT pattern. ALWAYS use this skill when user needs to: **SETUP** - Initialize or configure E2E testing infrastructure: - Set up E2E testing for a new project - Configure docker-compose for testing (Kafka, PostgreSQL, MongoDB, Redis) - Create jest-e2e.config.ts or E2E Jest configuration - Set up test helpers for database, Kafka, or Redis - Configure .env.e2e environment variables - Create test/e2e directory structure **WRITE** - Create or add E2E/integration tests: - Write, create, add, or generate e2e tests or integration tests - Test API endpoints, workflows, or complete features end-to-end - Test with real databases, message brokers, or external services - Test Kafka consumers/producers, event-driven workflows - Working on any file ending in .e2e-spec.ts or in test/e2e/ directory - Use GWT (Given-When-Then) pattern for tests **REVIEW** - Audit or evaluate E2E tests: - Review existing E2E tests for quality - Check test isolation and cleanup patterns - Audit GWT pattern compliance - Evaluate assertion quality and specificity - Check for anti-patterns (multiple WHEN actions, conditional assertions) **RUN** - Execute or analyze E2E test results: - Run E2E tests - Start/stop Docker infrastructure for testing - Analyze E2E test results - Verify Docker services are healthy - Interpret test output and failures **DEBUG** - Fix failing or flaky E2E tests: - Fix failing E2E tests - Debug flaky tests or test isolation issues - Troubleshoot connection errors (database, Kafka, Redis) - Fix timeout issues or async operation failures - Diagnose race conditions or state leakage - Debug Kafka message consumption issues **OPTIMIZE** - Improve E2E test performance: - Speed up slow E2E tests - Optimize Docker infrastructure startup - Replace fixed waits with smart polling - Reduce beforeEach cleanup time - Improve test parallelization where safe Keywords: e2e, end-to-end, integration test, e2e-spec.ts, test/e2e, Jest, supertest, NestJS, Kafka, Redpanda, PostgreSQL, MongoDB, Redis, docker-compose, GWT pattern, Given-When-Then, real infrastructure, test isolation, flaky test, MSW, nock, waitForMessages, fix e2e, debug e2e, run e2e, review e2e, optimize e2e, setup e2e
AWS CloudFormation patterns for Amazon RDS databases. Use when creating RDS instances (MySQL, PostgreSQL, Aurora), DB clusters, multi-AZ deployments, parameter groups, subnet groups, and implementing template structure with Parameters, Outputs, Mappings, Conditions, and cross-stack references.
Senior Database Administrator with expertise in PostgreSQL, MySQL, MongoDB, and enterprise database systems. Specializes in high availability architectures, performance tuning, backup strategies, and database security for production environments.
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.
Advanced Python unit testing framework for customer support tech enablement, covering FastAPI, SQLAlchemy, PostgreSQL, async operations, mocking, fixtures, parametrization, coverage, and comprehensive testing strategies for backend support systems