Skill UI

A comprehensive guide to selecting the optimal architecture for Replit applications. It compares three scaling models—single-file scripts (prototypes), modular apps (MVPs), and multi-service systems (large scale)—to help developers choose the correct database, storage, and deployment strategy as their project grows.

This comprehensive workflow guides developers through building a production-ready, full-stack web application entirely within the Replit environment. It covers setting up the entire architecture, including Express/Flask backend logic, robust PostgreSQL database integration for persistent data, implementing secure user authentication using Replit Auth, and managing file uploads via Object Storage. It is the definitive guide for launching a complex, scalable SaaS project from scratch.

This guide identifies and explains common anti-patterns and critical pitfalls encountered when building applications on the Replit platform. Topics include data persistence, secret management, networking bindings, and environment configuration. Use this resource when conducting code reviews, onboarding new developers, or auditing existing Replit applications for best practices.

A comprehensive guide for migrating existing applications from platforms like Heroku, Railway, Vercel, and local development environments to Replit. It covers critical steps such as converting configuration files (Procfile to .replit), adapting to Replit's Nix-based system, and performing database migrations (PostgreSQL, MongoDB). Essential for developers upgrading or moving their deployment stack.

This guide teaches developers how to implement robust rate limiting and handle resource quotas for applications hosted on Replit. It covers monitoring Key-Value database usage, implementing middleware for API rate limiting (using Express), and utilizing exponential backoff and request queuing patterns to ensure application stability and prevent service degradation when hitting resource limits (e.g., 429 errors).

This guide provides production-ready coding patterns for interacting with various built-in Replit services. It covers best practices for setting up singleton clients, implementing robust error handling, and creating type-safe wrappers for Key-Value Database, Object Storage, PostgreSQL, and Auth middleware. Ideal for developers building complex Replit integrations or establishing standardized data access layers.

Guides API developers through building request body validators, following best practices for REST, GraphQL, and OpenAPI workflows, and generating production-ready code plus validations.

This workflow guides developers through the systematic process of requesting and acting upon code reviews. It emphasizes the core principle of reviewing early and often, providing structured inputs (commits, requirements, implemented features) via a subagent to catch technical issues, ensure compliance with requirements, and maintain high code quality before merging.

Guides API developers through automatic response schema generation, offering best practices, code/configuration samples, and validation to keep REST, GraphQL, or OpenAPI responses compliant.

This skill provides comprehensive patterns for data handling and integration with Retell AI. It is designed for developers building advanced voice agents, automating phone calls, or working with complex telephony systems. The guide covers SDK usage, agent listing, and robust error handling, ensuring reliable implementation of voice AI applications.

This guide provides comprehensive instructions on installing the Retell AI SDK (for both Node.js and Python) and configuring the API key. It is essential for developers building advanced voice agents, integrating phone call automation, or working with any telephony-based AI application using the Retell platform.

This skill provides implementation patterns for developing local voice agents and automating phone calls using the Retell AI SDK. It guides developers through the necessary steps for integrating complex real-time voice interactions, telephony platforms, and building automated customer service agents, ensuring robust development and error handling practices.