Skill UI

This skill acts as a Senior Solutions Architect and Tech Consultant for AI projects. It diagnoses a workspace—determining if it is a pure new project or an evolving system. It analyzes the existing stack and pain points to chart the optimal technical roadmap, generating detailed backlogs and implementation plans to ensure scalable, high-quality development.

This skill acts as a specialized domain intelligence strategist, capable of analyzing specific industry niches (e.g., Fintech, HealthTech). It goes beyond general functionality to inject crucial domain-specific knowledge, mandatory regulatory compliance (like HIPAA or GDPR), and industry-leading UX/UI patterns. Essential for ensuring the product is optimized for its vertical market.

This skill provides a comprehensive framework for performing end-to-end UI testing and verification on Android emulators. It guides users through systematic processes including device calibration, UI element discovery using uiautomator, performing complex interactions (tap, swipe, input), and robust reporting via visual screenshots and logcat analysis. Ideal for ensuring the stability and functional correctness of React Native or native Android applications.

Acts as a specialized System Engineer responsible for designing, drafting, and deploying new functional skills into a repository. It ensures that all new skills strictly adhere to the Diamond Standard and follow rigorous deployment protocols, generating necessary documentation (READMEs) and registry entries.

This skill enhances research query formulation by translating vague, colloquial, or generalized descriptions into precise, standard academic terminology. When initial search terms are broad (e.g., "conjugal happiness"), this technique suggests multiple plausible academic synonyms (e.g., "marital satisfaction," "relationship quality"). By improving the precision of the search query and incorporating structured constraints (like keywords, years, or sample sizes), it significantly boosts the relevance and effectiveness of academic paper retrieval.

This skill is designed to translate vague, colloquial, or descriptive biological details (such as behaviors, appearances, or cultural uses) into precise scientific or common species names. It is essential for constructing effective search queries in biological databases when the question does not use formal taxonomic names. By accurately identifying candidate species names from descriptive clues, users can drastically improve search relevance and accuracy.

A comprehensive guide and toolkit for performing End-to-End (E2E) testing on native Windows desktop applications (WPF, WinForms, Win32, Qt) using pywinauto and the Windows UI Automation (UIA) API. Covers setup, locator strategies, and page object modeling for robust desktop automation.

A comprehensive framework for performing end-to-end (E2E) testing on various Windows native desktop applications. It utilizes pywinauto and the Windows UI Automation (UIA) API, supporting major frameworks including WPF, WinForms, Win32/MFC, UWP, and Qt. This skill helps automate complex GUI interactions, making it ideal for CI/CD integration and building robust desktop test suites.