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Found 245 Skills
Comprehensive Next.js development skill covering App Router, Server Components, data fetching, routing patterns, API routes, middleware, and full-stack Next.js applications
Use when creating Nuxt modules: (1) Published npm modules (@nuxtjs/, nuxt-), (2) Local project modules (modules/ directory), (3) Runtime extensions (components, composables, plugins), (4) Server extensions (API routes, middleware), (5) Releasing/publishing modules to npm, (6) Setting up CI/CD workflows for modules. Provides defineNuxtModule patterns, Kit utilities, hooks, E2E testing, and release automation.
Nest.js framework expert specializing in module architecture, dependency injection, middleware, guards, interceptors, testing with Jest/Supertest, TypeORM/Mongoose integration, and Passport.js authentication. Use PROACTIVELY for any Nest.js application issues including architecture decisions, testing strategies, performance optimization, or debugging complex dependency injection problems. If a specialized expert is a better fit, I will recommend switching and stop.
Build MCP servers in Python with FastMCP to expose tools, resources, and prompts to LLMs. Supports storage backends, middleware, OAuth Proxy, OpenAPI integration, and FastMCP Cloud deployment. Prevents 30+ errors. Use when: creating MCP servers, or troubleshooting module-level server, storage, lifespan, middleware, OAuth, background tasks, or FastAPI mount errors.
Backend development specialist covering API design, database integration, microservices architecture, and modern backend patterns. Use when user asks about API design, REST or GraphQL endpoints, server implementation, authentication, authorization, middleware, or backend service architecture. Do NOT use for database-specific schema design or query optimization (use moai-domain-database instead) or frontend implementation (use moai-domain-frontend instead).
Guide for Vercel AI SDK v6 implementation patterns including generateText, streamText, ToolLoopAgent, structured output with Output helpers, useChat hook, tool calling, embeddings, middleware, and MCP integration. Use when implementing AI chat interfaces, streaming responses, agentic applications, tool/function calling, text embeddings, workflow patterns, or working with convertToModelMessages and toUIMessageStreamResponse. Activates for AI SDK integration, useChat hook usage, message streaming, agent development, or tool calling tasks.
Implements secure authentication patterns including login/registration, session management, JWT tokens, password hashing, cookie settings, and CSRF protection. Provides auth routes, middleware, security configurations, and threat model documentation. Use when building "authentication", "login system", "JWT auth", or "session management".
Implements role-based access control with permission matrix, route guards, policy functions, and UI permission hints. Provides middleware/guards, helper utilities, test suggestions, and permission checking patterns. Use when building "RBAC", "permissions", "access control", or "authorization".
High-performance structured JSON logging for Node.js. Use when building production APIs that need fast, structured logs for observability platforms (Datadog, ELK, CloudWatch). Provides request logging middleware, child loggers for context, and sensitive data redaction. Choose Pino over console.log for any production TypeScript backend.
Backend development expert including server architecture, middleware, and data handling
Guides the agent through scaffolding and building FastAPI applications, including project structure, API routes, request/response models, path and query parameters, dependency injection, middleware, error handling, and boilerplate generation. Triggered when the user asks to "scaffold a FastAPI project", "create a FastAPI app", "add an API endpoint", "create a router", "add middleware", "implement dependency injection", "handle errors", "set up CORS", "create background tasks", "implement WebSocket", "structure a FastAPI project", "generate boilerplate", or "add authentication".
LangChain workflows for `create_agent`, LCEL chains, `bind_tools`, middleware, and structured output with production-safe orchestration. Use when implementing or refactoring LangChain application logic in Python or TypeScript.