Skill UI

This skill provides expert guidance on creating, reviewing, and managing production-grade AWS infrastructure using Terraform. It focuses on best practices for reusable module design, robust remote state management (S3 + DynamoDB), and adhering to modern HashiCorp Configuration Language (HCL) patterns like using 'for_each'. Ideal for teams building or auditing complex, scalable AWS environments.

Expert in implementing Infrastructure as Code (IaC) using Terraform across multi-cloud environments, including AWS, Azure, and GCP. Specializes in creating reusable, modular components, advanced state management (backends, locking, migrations), ensuring security best practices, and developing robust, production-grade cloud infrastructure pipelines.

This skill provides robust guidelines and patterns for managing environment variables and sensitive credentials securely. It is designed to ensure that secrets, API keys, and other confidential information are never accidentally exposed or logged in Claude sessions, terminal outputs, development logs, or version control commits (like Git). Use this skill when handling sensitive data in development workflows to maintain maximum security.

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 to installing and configuring the Vast.ai Command Line Interface (CLI) and REST API access. This skill is used for setting up new cloud integrations, managing API keys, and initializing access to GPU compute instances from the Vast.ai marketplace. It provides steps for CLI authentication, environment variable setup, and implementing a Python client for resource management.

This guide details how to implement environment isolation (dev, staging, prod) for GPU cloud deployments on Vast.ai. It uses environment variables and configuration classes to enforce separate API keys, budget caps, instance limits, and GPU whitelists for each deployment tier, ensuring efficient resource management and cost control.

This comprehensive guide outlines security best practices for utilizing Vast.ai's cloud environment. It covers secure API key management, hardening SSH access to GPU instances, implementing proper data cleanup before instance destruction, and adhering to robust network security protocols. Use this when setting up, auditing, or deploying sensitive AI/ML workloads on shared cloud hardware.

This guide provides comprehensive methods for deploying, promoting, and managing Vercel applications in production environments. It covers advanced strategies like instant rollback, controlled rolling releases (canary deployments), multi-region function configuration, and integrating with headless CMS via deploy hooks. Use this when you require robust CI/CD practices, high availability, and predictable production traffic management.

Provides a comprehensive, production-ready reference architecture for building complex applications on Vercel using Next.js and TypeScript. It covers modern best practices, including layered directory structure, secure typed environment variable management (Zod), lazy database singleton implementation, API route patterns, and essential Edge Middleware for authentication and routing. Use this guide when starting a new Vercel project or standardizing existing application infrastructure.

This skill guides users through implementing comprehensive security measures for Vercel deployments. It covers best practices for secret management (using sensitive environment variables), configuring critical HTTP security headers (such as CSP and HSTS), protecting preview environments, and enforcing robust access control for API routes and deployment tokens.

This guide outlines best practices for configuring IDEs and AI context management across complex, multi-service monorepos. It is essential for onboarding new teams, standardizing coding standards, and ensuring consistent development workflows for services across multiple deployment environments (Development, Staging, Production). Focuses on architectural rules, shared settings, and environment-specific deployment context.

A comprehensive guide for managing secrets and environment variables throughout the entire development lifecycle, from local development to production. This skill covers secret leak auditing (detecting committed credentials), implementing robust rotation workflows, and integrating with industry-leading secret stores like HashiCorp Vault, AWS Secrets Manager, and Azure Key Vault. Essential for hardening CI/CD pipelines and ensuring compliance.