Skill UI

This comprehensive index provides access to 32 production-ready, specialized engineering skills. It covers the entire development lifecycle, including system architecture, frontend, backend, DevOps, security operations, AI/ML, and data engineering. It is designed to guide users in selecting and loading only the specific module needed, ensuring focused expertise for complex tasks.

Guides building secure production-grade Electron desktop apps with isolated renderer processes, hardened IPC via preload bridges, packaging through electron-builder, code signing, and full auto-update workflows.

Opinionated Docker development assistant that analyzes Dockerfiles, docker-compose setups, multi-stage builds, and container security to shrink images, speed builds, and enforce production-ready practices when users need optimized containers.

A comprehensive strategy for regression testing in AI-assisted development. It focuses on identifying systematic blind spots, such as schema inconsistencies between sandbox and production paths, and integrating automated bug checks into the development workflow. This guide teaches how to build robust, database-free API tests to ensure code quality when AI models contribute to the codebase.

This skill guides the implementation of automated security scanning for Infrastructure as Code (IaC) templates using industry-leading tools like Checkov and tfsec. It focuses on integrating security checks into CI/CD pipelines to detect misconfigurations (e.g., public buckets, open ports) in Terraform, CloudFormation, and Kubernetes manifests before they reach production, thereby enforcing policy-based governance and securing the development lifecycle.

A comprehensive multi-agent feedback loop inspired by Generative Adversarial Networks (GANs), designed to build complex, production-ready applications. It separates generation from evaluation, using a 'ruthlessly strict' evaluator (QA) to drive continuous iteration. This process ensures high design quality, robust functionality, and originality, overcoming the limitations of single-agent self-critique. Ideal for full-stack feature development and complex product specification implementation.

This skill manages comprehensive software development life cycle operations—including issue triage, PR reviews, version releases, bug fixing, and marketing content generation. It operates using a parallel "agent army" of dynamic agents (10-20 per task), requiring the user to adopt an Engineering Manager (EM) mindset. Key principles involve rigorous citation checking (anti-hallucination) and applying multiple roles (Product Owner, Open Source Contributor, Architect) simultaneously to ensure robust, safe, and user-centric outcomes across all platforms.

This tool analyzes specification files to extract all defined requirements and cross-references them with the current codebase implementation status. It systematically checks for unimplemented features, searches existing GitHub issues to prevent duplicates, and automatically generates detailed issues using a standardized feature request template. It is essential for robust product management, ensuring every defined requirement is tracked and scheduled for development.

This generator provides a comprehensive, production-ready template for building a Model Context Protocol (MCP) server using Kotlin. It sets up the full Gradle structure, integrates essential dependencies (MCP SDK, Ktor, Coroutines), and includes robust placeholders for custom tools, error handling, and testing, accelerating the development of context-aware backend services.

This tool generates a complete, production-ready project scaffold for a Model Context Protocol (MCP) server written in Ruby. It includes the necessary file structure, gem dependencies, Rake tasks, and boilerplate code for defining tools, prompts, and resources, accelerating backend development for AI applications.

The GitHub Copilot SDK empowers developers to embed advanced, agentic AI workflows directly into their proprietary applications. It provides a programmatic interface to Copilot's production-tested agent runtime, allowing you to define complex agent behaviors, manage tool invocation, process file edits, and implement real-time streaming responses. Ideal for building custom, highly intelligent tools and automating complex tasks across multiple languages (Python, TypeScript, Go, .NET).

A comprehensive scaffold generator for building Model Context Protocol (MCP) servers using TypeScript and Node.js. This tool provides a complete, production-ready boilerplate, including proper project structure, dependency management (e.g., @modelcontextprotocol/sdk, zod), and implementation details for tools and resources. It supports both HTTP and stdio transport mechanisms, ensuring type safety, robust error handling, and best practices for modern backend development.