Skill UI

Tracks every code change via structured JSON records, enforces a lifecycle state machine, and maintains session handoff context with scripts for init/create/update/status/resume/close/export workflows.

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 CLI for managing the entire lifecycle of Windows applications. It handles initialization, building, packaging into MSIX, signing, debugging, and advanced UI automation via Microsoft UI Automation. Supports multiple modern frameworks including .NET, C++, Electron, Rust, and Flutter, streamlining the deployment process to the Microsoft Store.

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 skill guides users on operating the FrontendIntegration resources and the associated frontend-forge extension using kubectl. It covers the full lifecycle management: creating FI from complete YAML, updating status, enabling/disabling, troubleshooting build output, and managing the extension's installation plan. Ideal for DevOps engineers responsible for robust CI/CD pipeline management.

This comprehensive skill guides users through the entire lifecycle management of KubeSphere extensions. It covers extension discovery, dependency resolution, version verification, and executing controlled installations, upgrades, or uninstalls using the InstallPlan mechanism. It is essential for maintaining a stable and complex multi-component Kubernetes cluster environment.

A comprehensive coach guiding developers through the entire SaaS lifecycle: from initial idea and scaffolding (Next.js) to building MVP features, integrating AI, setting up authentication, implementing payment systems (Stripe/LemonSqueezy), and achieving global deployment (Cloudflare/Vercel). Focuses on pragmatic, 'ship first' architecture decisions for solo developers and indie hackers.

A comprehensive guide and SDK wrapper for utilizing the Adaptyv Bio Foundry API. This skill enables users to design, submit, monitor, and retrieve results for various protein characterization assays, including binding (BLI/SPR), thermostability, and expression. Users can programmatically manage the entire experimental lifecycle using Python.

This comprehensive tool guides the systematic creation of detailed technical specifications. It orchestrates the entire design lifecycle, including context loading, deep discovery and analysis (tailored for new features, extensions, or simple additions), synthesis using established design principles, and generating a boundary-first, structured design draft. Ensures all requirements are mapped to explicit technical components.

This skill provides an interactive, comprehensive quality review for technical design documents. It systematically validates a feature's readiness for implementation by assessing critical issues, identifying strengths, and providing a clear GO/NO-GO decision with actionable next steps. Ideal for ensuring architectural soundness and catching risks early in the development lifecycle.

A comprehensive guide covering the entire lifecycle of building VS Code extensions, from initial scaffolding to successful Marketplace publication. Learn best practices for Webviews, TreeViews, testing, packaging, and troubleshooting, ensuring compatibility with the latest APIs.

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.