"Use this agent when you need to build complete features spanning database, API, and frontend layers together as a cohesive unit. Specifically:\\n\\n<example>\\nContext: User wants to build a new user authentication system for a web application that requires database schema, API endpoints, and frontend forms.\\nuser: \"Build a complete user registration feature with PostgreSQL schema, Node.js API endpoints, and React forms including validation and error handling.\"\\nassistant: \"I'll implement this as a full-stack feature. Let me start by analyzing the existing database schema, then design the API contracts, and finally build the React components with proper integration and testing across all layers.\"\\n<commentary>\\nThis is a core fullstack-developer use case: new feature that touches all stack layers requires coordinated development from database to UI. The agent needs context on existing patterns and must ensure type-safety and consistency across all three layers.\\n</commentary>\\n</example>\\n\\n<example>\\nContext: Existing backend API needs frontend implementation along with database optimization to support a new real-time dashboard.\\nuser: \"We have the API endpoints ready, but need to build the React dashboard UI and optimize the database queries for real-time data streaming.\"\\nassistant: \"I'll examine your API structure and database schema, then build the React components with WebSocket integration for real-time updates, and optimize the queries for performance. This ensures the frontend, API, and database work together seamlessly.\"\\n<commentary>\\nWhen an incomplete feature chain exists (missing frontend or backend) and requires end-to-end integration testing, use the fullstack developer to coordinate across all layers and ensure optimal data flow, caching, and performance.\\n</commentary>\\n</example>\\n\\n<example>\\nContext: Refactoring payment processing system to change from polling to event-driven architecture across all layers.\\nuser: \"Refactor our payment system from polling the database to an event-driven model using WebSockets and message queues, affecting database design, API middleware, and frontend state management.\"\\nassistant: \"I'll redesign the database schema for event sourcing, implement the API event handlers and WebSocket server, rebuild the frontend state management for real-time updates, and ensure proper error recovery across the entire flow.\"\\n<commentary>\\nUse the fullstack developer for complex architectural changes that require synchronized updates across database design, API patterns, and frontend state management. The agent's cross-layer perspective prevents silos and ensures consistent implementation.\\n</commentary>\\n</example>\\n\\n<example>\\nContext: User wants to add a semantic search feature powered by AI to an existing product catalog.\\nuser: \"Add AI-powered semantic search to our product catalog using embeddings and a vector database.\"\\nassistant: \"I'll design the full pipeline: generate and store embeddings in pgvector via a background job, expose a /search API route using the Anthropic SDK for query embedding, stream results to the React frontend with useChat, and add an evaluation harness to measure retrieval quality.\"\\n<commentary>\\nAI feature work spanning embedding ingestion, RAG pipeline, streaming API, and frontend integration requires coordinated fullstack development. The agent ensures data flow, latency, and prompt versioning are handled coherently across all layers.\\n</commentary>\\n</example>"
fullstack-developer — Agent | الأطلس
"Use this agent when you need to build complete features spanning database, API, and frontend layers together as a cohesive unit. Specifically:\\n\\n<example>\\nContext: User wants to build a new user authentication system for a web application that requires database schema, API endpoints, and frontend forms.\\nuser: \"Build a complete user registration feature with PostgreSQL schema, Node.js API endpoints, and React forms including validation and error handling.\"\\nassistant: \"I'll implement this as a full-stack feature. Let me start by analyzing the existing database schema, then design the API contracts, and finally build the React components with proper integration and testing across all layers.\"\\n<commentary>\\nThis is a core fullstack-developer use case: new feature that touches all stack layers requires coordinated development from database to UI. The agent needs context on existing patterns and must ensure type-safety and consistency across all three layers.\\n</commentary>\\n</example>\\n\\n<example>\\nContext: Existing backend API needs frontend implementation along with database optimization to support a new real-time dashboard.\\nuser: \"We have the API endpoints ready, but need to build the React dashboard UI and optimize the database queries for real-time data streaming.\"\\nassistant: \"I'll examine your API structure and database schema, then build the React components with WebSocket integration for real-time updates, and optimize the queries for performance. This ensures the frontend, API, and database work together seamlessly.\"\\n<commentary>\\nWhen an incomplete feature chain exists (missing frontend or backend) and requires end-to-end integration testing, use the fullstack developer to coordinate across all layers and ensure optimal data flow, caching, and performance.\\n</commentary>\\n</example>\\n\\n<example>\\nContext: Refactoring payment processing system to change from polling to event-driven architecture across all layers.\\nuser: \"Refactor our payment system from polling the database to an event-driven model using WebSockets and message queues, affecting database design, API middleware, and frontend state management.\"\\nassistant: \"I'll redesign the database schema for event sourcing, implement the API event handlers and WebSocket server, rebuild the frontend state management for real-time updates, and ensure proper error recovery across the entire flow.\"\\n<commentary>\\nUse the fullstack developer for complex architectural changes that require synchronized updates across database design, API patterns, and frontend state management. The agent's cross-layer perspective prevents silos and ensures consistent implementation.\\n</commentary>\\n</example>\\n\\n<example>\\nContext: User wants to add a semantic search feature powered by AI to an existing product catalog.\\nuser: \"Add AI-powered semantic search to our product catalog using embeddings and a vector database.\"\\nassistant: \"I'll design the full pipeline: generate and store embeddings in pgvector via a background job, expose a /search API route using the Anthropic SDK for query embedding, stream results to the React frontend with useChat, and add an evaluation harness to measure retrieval quality.\"\\n<commentary>\\nAI feature work spanning embedding ingestion, RAG pipeline, streaming API, and frontend integration requires coordinated fullstack development. The agent ensures data flow, latency, and prompt versioning are handled coherently across all layers.\\n</commentary>\\n</example>"