Loading...
Loading...
Found 211 Skills
Enterprise-grade architecture combining DDD bounded contexts with Feature-Sliced Design. Use for large-scale monorepos with multiple domains, microservices, event-driven communication, and scalable frontend modules.
Apply cloud-native architecture patterns. Use when designing for scalability, resilience, or cloud deployment. Covers microservices, containers, and distributed systems.
This skill should be used when the user asks to "design REST APIs", "optimize database queries", "implement authentication", "build microservices", "review backend code", "set up GraphQL", "handle database migrations", or "load test APIs". Use for Node.js/Express/Fastify development, PostgreSQL optimization, API security, and backend architecture patterns.
Expert GraphQL developer specializing in type-safe API development, schema design, resolver optimization, and federation architecture. Use when building GraphQL APIs, implementing Apollo Server, optimizing query performance, or designing federated microservices.
NestJS 11+ best practices for enterprise Node.js applications with TypeScript. Use when writing, reviewing, or refactoring NestJS controllers, services, modules, or APIs. Triggers on: NestJS modules, controllers, providers, dependency injection, @Injectable, @Controller, @Module, middleware, guards, interceptors, pipes, exception filters, ValidationPipe, class-validator, class-transformer, DTOs, JWT authentication, Passport strategies, @nestjs/passport, TypeORM entities, Prisma client, Drizzle ORM, repository pattern, circular dependencies, forwardRef, @nestjs/swagger, OpenAPI decorators, GraphQL resolvers, @nestjs/graphql, microservices, TCP transport, Redis transport, NATS, Kafka, NestJS 11 breaking changes, Express v5 migration, custom decorators, ConfigService, @nestjs/config, health checks, or NestJS testing patterns.
Ultimate 25+ years expert-level backend skill covering FastAPI, Express, Node.js, Next.js with TypeScript. Includes ALL databases (PostgreSQL, MongoDB, Redis, Elasticsearch), ALL features (REST, GraphQL, WebSockets, gRPC, Message Queues), comprehensive security hardening (XSS, CSRF, SQL injection, authentication, authorization, rate limiting), complete performance optimization (caching, database tuning, load balancing), ALL deployment strategies (Docker, Kubernetes, CI/CD), advanced patterns (microservices, event-driven, saga, CQRS), ALL use cases (e-commerce, SaaS, real-time, high-traffic), complete testing (unit, integration, E2E, load, security). Route protection, middleware, authentication implementation in PERFECTION. Use for ANY backend system requiring enterprise-grade security, performance, scalability, and architectural excellence.
Use this skill when designing distributed systems, architecting scalable services, preparing for system design interviews, or making infrastructure decisions. Triggers on load balancing, CAP theorem, sharding, replication, caching strategies, message queues, microservices architecture, database selection, rate limiting, and any task requiring high-level system architecture decisions.
Design durable workflows with Temporal for distributed systems. Covers workflow vs activity separation, saga patterns, state management, and determinism constraints. Use when building long-running processes, distributed transactions, or microservice orchestration.
GraphQL gives clients exactly the data they need - no more, no less. One endpoint, typed schema, introspection. But the flexibility that makes it powerful also makes it dangerous. Without proper controls, clients can craft queries that bring down your server. This skill covers schema design, resolvers, DataLoader for N+1 prevention, federation for microservices, and client integration with Apollo/urql. Key insight: GraphQL is a contract. The schema is the API documentation. Design it carefully.
Implement service mesh (Istio, Linkerd) for service-to-service communication, traffic management, security, and observability.
Create or evaluate an architecture decision record (ADR). Use when choosing between technologies (e.g., Kafka vs SQS), documenting a design decision with trade-offs and consequences, reviewing a system design proposal, or designing a new component from requirements and constraints.
Use to run AutoMagicCalib on local MP4s, RTSP, or the bundled sample dataset, and to deploy vss-auto-calibration when needed. Not for non-AMC calibration or runtime analytics.