Skill UI

This utility automates the creation of a complete, production-ready Model Context Protocol (MCP) server project using Java. It generates full source code templates, including configuration, tool handling, resource definitions, and prompt logic. The generator provides robust setup for both Maven and Gradle, ensuring the resulting backend service is structured, scalable, and ready for deployment with support for reactive streams and optional Spring Boot integration.

A comprehensive guide to creating production-grade Product Requirements Documents (PRDs). This skill helps bridge the gap between vague business concepts and concrete technical specifications for modern software systems and AI features. It enforces a structured workflow, ensuring all necessary components—from user stories and success KPIs to technical architecture and risk analysis—are defined.

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.

This tool scaffolds a complete, production-ready Model Context Protocol (MCP) server project written in Rust. It utilizes the official `rmcp` SDK to ensure full compatibility. The generated structure includes modules for handling logic, defining tools, managing prompts, and providing resources. Users can configure different transports (stdio, SSE, HTTP) and immediately run the server for integration testing or production use.

A comprehensive guide detailing how to configure and manage GitHub's secret scanning feature. This skill covers enabling Secret Protection, setting up push protection to block leaked credentials before they reach the repository, defining custom regex patterns, and providing workflows for triaging alerts and resolving blocked pushes (including using git rebase or bypassing protections). Essential for maintaining secure code repositories and complying with security standards.

This comprehensive guide provides a detailed framework for authoring effective and structured SKILL.md files for AI coding agents. It covers best practices for structuring content, including frontmatter fields, defining natural language triggers, establishing core principles, and incorporating advanced elements like decision trees and verification checklists, ensuring agents receive clear, actionable, and consistent technical guidance.

This expert tool guides users through rigorous statistical analysis, specializing in A/B testing, hypothesis testing, and interpreting experimental results. It helps define sample sizes, executes appropriate tests (Z-test, T-test, Chi-square), and critically distinguishes between 'statistical significance' and 'practical significance' to ensure data-driven decision-making for product and business strategy.

A comprehensive tool that analyzes existing codebases to generate detailed, definitive architectural blueprints. It automatically detects technology stacks, identifies architectural patterns (e.g., Microservices, Clean Architecture), and documents implementation details, including dependency flow, cross-cutting concerns (security, logging), and data models. This ensures architectural consistency, aids in onboarding new team members, and guides future development efforts.

This comprehensive guide provides step-by-step instructions for setting up a development environment to use AWS CDK (Cloud Development Kit) with Python. It covers installing prerequisites (Node.js, AWS CLI), initializing a CDK project, managing Python dependencies, and mastering the full deployment workflow, enabling users to define and deploy scalable AWS infrastructure as code.

This skill guides users on setting up and running LLM-as-judge evaluations using Arize. It covers defining evaluators (including prompts, classification choices, and models) and executing tasks against real data spans or experiments. It supports key metrics like hallucination, faithfulness, and correctness, and facilitates continuous monitoring for comprehensive LLM performance analysis.

This agent guides users in selecting the optimal Azure role assignment that strictly adheres to the principle of least privilege. Given a set of desired permissions, it utilizes specialized tools to either identify a suitable built-in role or generate a custom role definition. Finally, it provides actionable code snippets, including CLI commands and Bicep templates, ensuring proper and secure role assignment.

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).