Skill UI

Detects TypeScript/JavaScript circular imports, visualizes dependency cycles with tools like madge, and offers strategies (shared interfaces, DI, dynamic/type-only imports, barrel restructuring) plus CI checks and ESLint rules for ongoing prevention.

Automatically checks application metrics such as load times, bundle sizes, and API responses against predefined performance budgets, surfacing regressions and preventing slippage before deployments—ideal for CI/CD workflows.

This comprehensive workflow guides users through the end-to-end process of utilizing cloud-based GPU computing resources on Vast.ai. It covers searching for ideal GPU offers based on specs and price, provisioning an instance, running complex training or inference jobs via SSH, collecting model artifacts, and crucially, destroying the instance to prevent unexpected billing. Ideal for deep learning training and research.

Implement robust, event-driven workflows for managing GPU resources on Vast.ai. Since native webhooks are unavailable, this skill uses Python polling to continuously monitor instance status changes (e.g., loading, running, exited). It enables complex automation tasks such as auto-recovering from spot preemption, handling lifecycle events, and tracking billing costs.

This comprehensive guide catalogs common anti-patterns and mistakes when deploying applications on Vercel. It covers critical architectural areas such as secret management (preventing key exposure), optimizing serverless function performance (cold start, timeouts), adhering to Edge Runtime standards, and resolving configuration errors. Use this skill for code reviews, security audits, and onboarding new developers to ensure best deployment practices.

Implement comprehensive guardrails for Vercel applications, covering the entire development lifecycle. This solution includes custom ESLint rules to prevent secret exposure, pre-commit hooks for credential scanning, and robust CI checks to validate vercel.json, ensure edge runtime compatibility, and monitor bundle size, guaranteeing high quality and secure deployments.

This guide provides comprehensive solutions for handling Vercel API rate limits (HTTP 429 errors). It covers implementing robust retry logic with exponential backoff for consuming Vercel's outbound APIs. Furthermore, it demonstrates how to configure Vercel's WAF rate limiting and custom edge configurations to protect your own deployed API endpoints, ensuring stability and preventing service abuse.

A comprehensive guide for implementing secure and reliable webhook endpoints to handle Vercel deployment lifecycle events. This skill covers signature verification (HMAC) to ensure security, processing key events (e.g., deployment.ready, deployment.error), and implementing idempotency to prevent duplicate actions. Ideal for building automated CI/CD integrations, status notifications, or custom project hooks that react to deployment changes in real-time.

This comprehensive guide outlines the core principles for developing immersive Virtual and Augmented Reality (VR/AR) applications. It covers critical aspects such as platform selection (Quest, ARKit, ARCore), mandatory performance metrics (FPS, frame budget), user comfort techniques (motion sickness prevention), and best practices for spatial interaction and world design. Essential reading for engineers building next-generation spatial computing experiences.

This skill enables comprehensive audit logging for Windsurf Enterprise deployments. It covers tracking of AI interactions, file access events, authentication changes, and overall configuration modifications. It is essential for maintaining strict compliance standards and performing detailed security audits, particularly when the user mentions audit or compliance keywords.

This skill enables AI-assisted debugging and comprehensive error analysis within the development environment. It utilizes Cascade to analyze complex error messages, stack traces, and surrounding code context to identify root causes. Use it when troubleshooting code or encountering runtime errors to receive detailed fix recommendations and prevention strategies.

This policy set establishes comprehensive guardrails for using AI coding assistants (like Windsurf/Cascade). It governs terminal commands, enforces workspace isolation (preventing access to secrets/credentials), and integrates CI/CD gates for code quality. Use this when setting up team development standards, mandatory code review policies for AI output, or implementing secure development pipelines.