Skill UI

This comprehensive guide details how to optimize the Replit development environment. It covers setting up run commands, implementing hot reloading for various languages (Node.js, Python), configuring ports, managing development vs. production databases, and leveraging the Replit Agent for powerful AI-assisted coding. Use this guide when setting up a new project or refining your entire dev workflow.

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 details essential patterns for building fault-tolerant and highly available Replit applications. It covers handling cold starts, implementing graceful shutdowns (via SIGTERM), and crucially, migrating persistent application state from ephemeral local filesystems to robust external storage (like Replit KV or Object Storage). Essential for production-grade deployments.

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.

This guide provides a comprehensive, environment-aware setup for Sentry in local development workflows. It details how to correctly route development events to separate DSNs, enable verbose debugging, and maximize data capture rates (e.g., setting sample rates to 1.0). Users learn to use `startSpan` for performance profiling and ensure that sensitive credentials are safely managed outside of source control.

A comprehensive guide and setup for building a fast, reliable local development workflow for language learning applications. It includes setting up mock tutor responses for offline testing, generating audio test fixtures using TTS, and implementing a debug mode for detailed pronunciation scoring analysis. Ideal for engineers setting up a new Speak-based integration or refining existing test pipelines.

This guide outlines essential security best practices for integrating the Speak API. It covers critical areas like securing API keys using secrets managers, ensuring audio data privacy by deleting local files, and maintaining compliance with major regulations such as COPPA and FERPA. Use this knowledge when building production-ready, secure language learning applications.

Automate the entire Supabase development lifecycle within CI/CD pipelines using GitHub Actions. This tool links projects, validates database migrations, deploys Edge Functions, generates TypeScript types, and runs comprehensive tests against local Supabase instances. Essential for maintaining robust code quality and ensuring schema consistency before deployment.

This comprehensive guide details the complete workflow for setting up and maintaining a local Supabase development environment. It utilizes Docker and the Supabase CLI to run the entire full-stack service (Postgres, Auth, Storage, etc.) locally. It guides developers through initialization, creating version-controlled migrations using diff, seeding data, and performing clean database resets, ensuring local iteration accurately mirrors production capabilities.

Enables Trigger.dev-based background jobs, AI workflows, and scheduled or batch async execution with a TypeScript-first SDK, durable retries, and built-in integrations while matching production behavior through the local CLI.

This guide establishes a fast, reproducible local development workflow for GPU workloads using Vast.ai. It covers key practices such as testing Docker images locally (in CPU mode), mocking external APIs like Vast.ai, and implementing robust unit and integration tests. This is essential for minimizing cloud GPU costs and accelerating the iteration cycle for complex AI/ML projects.

This guide details how to set up a full local development loop for applications deployed to Vercel. It covers using `vercel dev` to emulate serverless functions, managing environment variables, and implementing hot reloading. It provides step-by-step instructions for local testing of API routes and frontends, ensuring a fast and accurate iteration cycle before production deployment.