Skill UI

Conducts STRIDE-A threat modeling on repositories or systems, running either a full single-pass analysis with architectures, DFDs, prioritized findings, and executive assessments, or an incremental update that compares a baseline report to the current code and highlights deltas.

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.

This guide provides a comprehensive template and best practices for updating technical specification files. It ensures that the resulting documentation is structured, unambiguous, and highly optimized for consumption by Generative AI models. Use this process when refining system requirements, updating interfaces, or documenting architectural changes to maintain machine-readable standards.

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.

Cirq is an open-source framework from Google Quantum AI used for designing, simulating, optimizing, and running quantum circuits. It supports NISQ circuit development, noise modeling, and compilation for various quantum hardware backends, including Google Quantum AI, IonQ, and AQT. It is essential for quantum algorithm research and hardware characterization.

A versatile, hardware-agnostic quantum computing framework designed for training quantum circuits and building hybrid quantum-classical models. It provides automatic differentiation, supporting advanced applications in Quantum Machine Learning, Quantum Chemistry (VQE), and variational algorithms, while ensuring portability across major quantum hardware backends (IBM, Google, etc.).

The Hugging Face Transformers library is a comprehensive toolkit providing access to thousands of pre-trained models across diverse domains including Natural Language Processing (NLP), Computer Vision, Audio, and Multimodal tasks. It enables developers to easily load models, perform high-level inference (e.g., text generation, classification, QA), and fine-tune models on custom datasets using streamlined APIs like Pipelines and the Trainer class. Ideal for building advanced, state-of-the-art AI applications.

A comprehensive guide for configuring and managing Claude API access across disparate environments (Development, Staging, Production). This skill details how to implement isolated API keys, model selection strategies, and crucial spend controls using Anthropic Workspaces, ensuring secure and reliable deployment pipelines for AI applications.

This guide details advanced strategies for optimizing Claude API usage to reduce latency and cost. Techniques covered include prompt caching (significant cost reduction), strategic model selection (Haiku, Sonnet, Opus) based on task complexity, implementing streaming for perceived speed, and managing token limits. Use this guide when building high-performance, cost-efficient LLM applications that interact with large language models.

A comprehensive guide and framework for implementing Role-Based Access Control (RBAC) for Apple Notes in multi-user enterprise environments. It details account separation techniques, folder-based permission models, and MDM enforcement strategies to secure sensitive organizational data within macOS automation scripts. Ideal for IT professionals and developers managing corporate data compliance.