Skill UI

Guides architects through Dataverse SDK use cases by analyzing requirements, designing data models, selecting integration patterns, and producing production-ready Python code with best practices.

Creates a production-ready Model Context Protocol server in Go by scaffolding modules, tools, resources, configuration, README guidance, and basic tests built around the official GitHub SDK for rapid setup.

This tool generates a complete, production-ready PHP Model Context Protocol (MCP) server project. It automatically scaffolds the entire structure, including tools, resources, prompts, and comprehensive tests, utilizing the official PHP SDK. It provides a standardized, robust starting point for developers building AI-integrated backend services in PHP.

Creates a production-ready Swift MCP Server project using the official MCP Swift SDK, wiring ServiceLifecycle, logging, tool/resource/prompt handlers, and tests so you can quickly spin up a Model Context Protocol server with a standard directory layout.

This structured prompt guides an AI model to proactively analyze a user's question and systematically list all necessary files for accurate answering. It forces the AI to categorize required context into 'Must See' (critical), 'Should See' (helpful), 'Already Have,' and 'Uncertainties.' Ideal for complex coding tasks, debugging, or feature implementation that spans multiple codebase files.

This comprehensive guide serves as a technical reference for migrating applications from the Universal Windows Platform (UWP) framework to the modern WinUI 3 / Windows App SDK. It details crucial API changes, including namespace updates, window management (CoreWindow to AppWindow), threading models (CoreDispatcher to DispatcherQueue), and best practices for dialogs and background tasks. Essential for developers updating legacy UWP codebases.

This tool generates canonical, submit-ready FrontendIntegration YAML from a simplified, single-menu authoring model. It is ideal for converting preliminary configurations (like those derived from a CRD) into the full, structured YAML required for deploying frontend integrations, ensuring all fields and placements are correctly mapped.

This resource provides production-ready architectural patterns for integrating Anthropic's Claude models using TypeScript and Python. It covers robust client wrappers, managing multi-turn conversations, enforcing structured JSON output via prefilling, and implementing multi-tenant architectures. Essential for building reliable, enterprise-grade AI applications.

This skill automatically converts structured data specifications (such as CSV, JSON schemas, SQL DDL, or Protobuf definitions) into functional, production-ready code. It generates complete models, validation logic, full CRUD API endpoints, and unit tests in multiple languages (Python, TypeScript, Go, etc.), significantly reducing boilerplate coding time and ensuring type safety.

A comprehensive guide to advanced, production-ready LLM inference using LangChain 1.0. This skill addresses common pitfalls and bugs when integrating multiple providers (Claude, GPT-4o, Gemini), covering issues like structured output reliability, correct streaming token accounting, and robust handling of complex AIMessage content blocks. It teaches best practices for model initialization, provider routing, and version-safe code implementation.

Search, read, and monitor arXiv papers through a Model Context Protocol server. Supports abstracts, LaTeX source sections, citation graphs, local storage, and topic watches.

This comprehensive skill transforms raw game concepts into fully actionable, structured Unity development projects. It guides users through a five-phase pipeline, generating detailed Game Design Documents (GDDs), technical scene blueprints, core system architectures, and ready-to-use AI prompts for assets (3D models, textures, music, SFX). Ideal for concept validation and starting a complex game project from scratch.