Skill UI

Automates CI/CD pipeline setup, from linting and type checks to integration, E2E, security, and deployment stages, plus feedback loops for AI agents and preview deployments.

This tool provides comprehensive automation capabilities for managing cloud infrastructure on the Render platform via Rube MCP. Users can list, filter, and browse various services (web services, static sites, etc.), manually trigger new deployments, and continuously monitor the deployment status (e.g., checking for 'live' status or catching 'build_failed' errors). It is essential for streamlining CI/CD pipelines, managing projects, and ensuring reliable, automated service updates without manual intervention.

Conducts a multistep preflight validation for Azure Bicep deployments, covering syntax checks, what-if previews, permission verification, and report generation so teams can confidently run azd or az deployments with known outcomes.

Automates repository, issue, PR, branch, and CI/CD operations through Rube MCP’s GitHub toolkit, enabling teams to programmatically manage workflows, reviews, searches, and deployments once the MCP and GitHub connections are active.

A comprehensive guide covering best practices for Terraform and OpenTofu. It provides structured advice on module hierarchy, directory organization, naming conventions, and advanced testing strategies (including native testing and policy as code). Use this skill when designing, refactoring, or implementing robust Infrastructure as Code (IaC) pipelines and multi-environment deployments.

A comprehensive automation toolkit designed to manage the entire Vercel deployment lifecycle and associated infrastructure. Users can programmatically monitor, trigger, and manage deployments, configure custom domains and DNS records, manage environment variables across multiple targets, and oversee project settings and project listings. Essential for implementing robust CI/CD pipelines and managing cloud infrastructure.

A comprehensive guide to setting up and managing Continuous Integration and Continuous Deployment (CI/CD) pipelines within KubeSphere. This tool integrates with Jenkins, supports both graphical editing and Jenkinsfile-based workflows, and enables automated deployments across multi-cluster environments using ArgoCD for GitOps management. Ideal for managing the full software delivery lifecycle.

This guide provides comprehensive instructions for setting up monitoring and observability for Qdrant deployments. It helps users track critical performance metrics, check system health, and diagnose complex production issues such as memory growth or slow query requests. Use cases include setting up Prometheus, Grafana, and implementing robust health checks.

This guide provides comprehensive strategies to significantly reduce spending on the Anthropic Claude API. Key techniques include model routing (selecting the most cost-effective model for the task), prompt caching for repeated prompts, using Message Batches for asynchronous tasks, and implementing real-time spend tracking and budget alerts. Essential for managing large-scale, high-cost AI deployments and optimizing cloud LLM expenditures.

Configure robust CI/CD pipelines for Apify Actor builds and deployments using GitHub Actions. This guide covers setting up unit tests on pull requests, running deep integration tests against the live Apify API, and automating the production deployment process upon merge. Ideal for maintaining reliable, high-quality scraping and automation projects.

A comprehensive guide detailing how to securely configure and manage Canva Connect API integrations across development, staging, and production environments. This resource covers environment strategy, best practices for OAuth credential management, secret handling (AWS, GCP, Vault), and implementing environment isolation guards to ensure secure and scalable deployments.

Automate the entire deployment lifecycle for ML inference services on CoreWeave GPU cloud. This workflow integrates unit testing, container image building (to GHCR), and rolling deployment to CoreWeave Kubernetes clusters via GitHub Actions. Ideal for ensuring stable, high-performance deployment of GPU-dependent models. Key features include validating GPU manifest requests and managing deployments using standard Kubernetes APIs.