Skill UI

An expert specialist for rigorous visual validation, focusing on UI testing, design system compliance, and WCAG accessibility verification. This skill systematically analyzes visual evidence for cross-platform consistency, pixel-perfect accuracy, and adherence to modern design standards, utilizing principles from visual regression testing and comprehensive QA methodologies.

This skill acts as an expert test automation specialist, capable of analyzing source code across multiple languages (Python, JavaScript, TypeScript, etc.). It generates comprehensive, maintainable unit test suites using best practices, maximizing code coverage, and specifically targeting edge cases and exception handling. Use it to ensure high code quality and structural consistency.

Automates creation of unittest-based test suites by guiding developers through industry best practices for unit and integration testing, mocking, and framework setup while validating outputs against common standards.

This guide details how to integrate Vast.ai's GPU provisioning capabilities into automated CI/CD pipelines, such as GitHub Actions. It enables developers to run GPU-accelerated tests, model benchmarks, and validations automatically. Key features include robust instance lifecycle management (provisioning, running, and cleanup) and advanced cost-control mechanisms (e.g., setting budget limits) to ensure reliable and efficient testing in a cloud environment.

A comprehensive guide demonstrating the full lifecycle of GPU resource utilization on Vast.ai. This includes searching for available hardware using CLI and REST APIs, provisioning a dedicated GPU instance (e.g., using PyTorch images), connecting via SSH, running deep learning workloads, and finally, securely destroying the instance to stop billing. Ideal for testing cloud integration or managing ML compute pipelines.

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.

Comprehensive guide for creating, managing, and automating preview deployments on Vercel. Learn how to utilize both the CLI and REST API to deploy unique, temporary environments for specific branches or pull requests. This is essential for pre-production testing, integrating into CI/CD pipelines, and sharing stable preview URLs with stakeholders before merging to main.

A comprehensive guide to building and deploying Vercel Edge Functions. These functions run on Vercel's global Edge Network (V8 isolates), providing ultra-low latency and zero cold starts. Learn how to use Web Standard APIs for critical tasks such as authentication, geolocation routing, A/B testing, and high-performance API middleware, drastically improving application speed and user experience.

This comprehensive guide provides a step-by-step walkthrough for deploying a minimal, functional full-stack application to Vercel. It covers setting up both static HTML landing pages and robust serverless API routes using TypeScript. This skill is ideal for beginners starting new Vercel projects, testing deployment pipelines, or learning the core patterns of modern serverless function implementation.

This guide provides comprehensive methods for load testing and capacity planning of Vercel serverless deployments. Learn how to use professional tools like k6 and autocannon to simulate realistic traffic spikes, measure latency (P95, P99), analyze cold start impact, and tune concurrency settings (Fluid Compute) to ensure optimal application performance and scalability under heavy load.

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.

This comprehensive checklist is designed for ensuring flawless deployments to Vercel's production environment. It guides users through every critical stage: pre-deployment verification (environment variables, testing), secure promotion and API deployment, domain configuration, post-deployment health checks, and immediate rollback procedures. Use this guide whenever preparing for a major launch or implementing go-live procedures to minimize production risks.