Skill UI

A comprehensive methodology for pinpointing the root cause of complex bugs, regressions, or unexpected behavior in large codebases. Techniques include binary search debugging, Git bisect for tracking regressions across commits, strategic data/control flow logging, component isolation, and advanced breakpoint strategies (conditional breakpoints, watch expressions). Ideal for scenarios where the bug source is unclear or difficult to reproduce.

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 skill helps developers accurately find and explore the correct Windows API for specific platform capabilities, such as file access, camera usage, notifications, or UI controls. It searches a comprehensive local cache of WinMD metadata, providing full technical details including methods, properties, events, and enumeration values for APIs sourced from the Windows Platform SDK and WinAppSDK. It is indispensable when building complex features requiring deep integration with the Windows operating system.

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.

A comprehensive skill designed to convert vague ideas, initial concepts, or high-level requirements into structured, detailed, and approved technical specifications. It enforces a rigorous, multi-step workflow, guiding users through context exploration, proposing multiple architectural trade-offs, and iteratively refining the design until a complete specification document is ready for the implementation phase.

This guide outlines a rigorous, technical framework for receiving and responding to code review feedback. It emphasizes that code review is a technical assessment, not an emotional exchange. Users learn how to verify assumptions, ask clarifying questions, professionally refute incorrect suggestions, and implement changes iteratively, ensuring code quality and architectural integrity.

This guide details advanced techniques for searching cricket matches by leveraging precise numerical scoring data. Instead of broad terms, users should utilize specific details—such as team totals (e.g., 168/9), runs off balls, wickets taken, or over details—combined with the match type and year to create highly targeted search queries. This method significantly improves search accuracy and efficiency when researching sports statistics.

This guide provides techniques for conducting effective crime investigations in non-English speaking countries (e.g., Thailand, Malaysia, Latin America). It teaches investigators to move beyond generic English searches by incorporating local language terms, specific regional place names, and local media terminology to find comprehensive and relevant information.

This technique is used when the required answer in a case query is not directly stated but must be deduced by following a sequence of connected roles, people, or events. It involves mapping complex relationships, such as Victim -> Defendant -> Lawyer -> Witness, to trace indirect connections and reach the final piece of information. Ideal for advanced investigative research and deep knowledge graph traversal.

This technique guides users on decomposing multi-constraint questions, especially in the domain of football trivia or historical research. Instead of searching all criteria simultaneously, it instructs users to rank constraints by distinctiveness (e.g., specific match results first, then historical milestones). By performing incremental, cascading searches, the system dramatically narrows down the result set, leading to more accurate information retrieval.

This skill guides the systematic process of identifying and verifying candidate football entities (players or clubs). Use it when initial search results suggest a lead, or when the question provides enough detailed constraints (e.g., nationality, era, league) to hypothesize a candidate. The technique involves constructing targeted name-based searches and cross-checking every constraint (birth year, career timeline, etc.) against the found profile to ensure accuracy.

This technique allows users to locate game developers or projects indirectly by searching for highly distinctive biographical details. Instead of relying on game databases, it leverages unique phrases, historical events, or personal lifestyle details found in interviews, blogs, or conference talks. It is invaluable when the developer's identity is obscured, requiring deep research using exact-match queries on obscure information.