Skill UI

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 comprehensive automation toolkit manages core Bitbucket functionalities, including repositories, workspaces, pull requests, and issues. It enables programmatic control over development workflows—from creating and reviewing pull requests to listing repos, tracking issues, and managing workspace members. Essential for integrating CI/CD pipelines and streamlining the entire software development lifecycle.

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).

This guide outlines the structure and content guidelines for an AGENTS.md file. This file serves as a comprehensive 'README for agents,' providing detailed, technical context and operational instructions (such as setup, development workflow, testing procedures, and code style) that enable advanced AI coding agents to interact with and understand a codebase effectively. It greatly complements traditional READMEs by focusing purely on machine-readable technical requirements.

This comprehensive guide provides a complete, step-by-step workflow for setting up a modern Spring Boot Java project from scratch. It covers downloading the project template, configuring multiple data sources (PostgreSQL, Redis, MongoDB), integrating API documentation (SpringDoc), and orchestrating a full, containerized service environment using Docker Compose. Ideal for complex, enterprise-level application development.

FAF Expert is an advanced tool for creating standardized, persistent context for complex software projects. It uses the IANA-registered FAF format to transform codebases into AI-intelligent assets. Use it for multi-AI workflow management (Claude, Gemini, etc.), enterprise-grade deployment, and standardizing project context across development lifecycles.

A comprehensive guide for creating, updating, refactoring, and reviewing solutions built on the Microsoft Agent Framework. This skill provides unified best practices for both .NET and Python environments, serving as a modern successor to Semantic Kernel and AutoGen. It emphasizes adherence to the latest official documentation, async patterns, robust error handling, and structured agent/workflow orchestration for complex AI applications.

This tool searches the current repository and lists all pull requests assigned to the user. It provides comprehensive details for each PR, including its purpose and scope. The output is highly functional, highlighting pending review status, detailing any failed checks (with suggested fixes), and offering to automatically request a Copilot review to maintain continuous development flow. Ideal for daily workflow status checks.

This skill provides structured procedures for managing NuGet packages in .NET projects and solutions. It strictly enforces the use of the `dotnet` CLI for adding, removing, and updating dependencies, prioritizing project integrity. It guides users through a mandatory workflow for version updates, including version verification and running `dotnet restore`, ensuring a stable and consistent development environment.

A file-based system designed to organize and track the progress of complex, multi-stage tasks, perfect for extensive research or detailed project development. It uses persistent Markdown files (task_plan.md, progress.md, findings.md) as a 'desktop memory' to maintain state and context across sessions. Supports automatic session recovery and structured workflow tracking, making it invaluable for large-scale, multi-tool usage projects.

This micro-prompt guides AI agents to adopt the mindset of an interactive programmer. It emphasizes using the REPL (Read-Eval-Print Loop) for systematic system exploration and modification, treating the system state as the ultimate source of truth. It also reminds the agent to utilize structural editing tools and maintain todo lists, significantly improving the accuracy and efficiency of the development workflow in live coding environments.

Analyzes and generates a self-contained, explorable HTML report detailing usage metrics for Claude Code sessions. It tracks token consumption (input/output), subagent usage, skill calls, and cache efficiency across specified time ranges. This tool helps developers visualize resource waste and pinpoint areas for workflow optimization, ensuring cost-effective and efficient AI development cycles.