Skill UI

A comprehensive skill set for mastering enterprise-grade Scala development. Expertise covers functional programming, distributed systems, and big data processing using technologies like Pekko, Akka, Spark, ZIO, and Cats Effect. Ideal for designing and implementing resilient, scalable microservices based on Domain-Driven Design principles.

This skill provides comprehensive guidelines for architecting and developing high-quality, maintainable software. It is deeply rooted in Clean Architecture and Domain-Driven Design (DDD) principles. It covers best practices for code decomposition, naming conventions, separation of concerns, and avoiding common anti-patterns. Use this skill when designing, analyzing, or developing complex, domain-specific software systems.

A comprehensive guide to modern utility-first CSS using Tailwind CSS v4 principles. Covers the shift to CSS-first configuration, utilizing CSS variables for design tokens, implementing advanced container queries, and mastering responsive, dark mode, and complex layout patterns (Grid/Flex). Essential for building modern, component-driven UIs efficiently.

This skill helps developers adhere to Test-Driven Development (TDD) principles by generating comprehensive, failing unit and integration tests. It is specifically designed for the 'Red' phase, ensuring that expected behaviors, edge cases (null, boundary values), and error handling are rigorously defined before any implementation code is written. It forces the definition of the 'what' before the 'how'.

This skill guides developers through advanced, safe, and systematic code refactoring using Test-Driven Development (TDD) principles. It provides a comprehensive workflow encompassing pre-assessment, detecting code smells, applying major design patterns (SOLID, Factory, Strategy), optimizing performance, and ensuring safety through rigorous, incremental testing. Use this when improving code structure, restructuring large components, or updating legacy systems while guaranteeing functional integrity and maintainability.

This skill acts as a specialized tutorial engineering specialist, transforming raw, complex technical concepts or codebases into structured, progressive, and engaging educational content. It applies pedagogical design principles, such as progressive disclosure, spaced repetition, and hands-on exercises, to create documentation, courses, and onboarding materials that teach users how to build, debug, and optimize, rather than just referencing information.

An expert-level skill set covering the entire spectrum of user-centered design. Mastery includes building scalable design systems using atomic principles and design tokens, conducting deep user research (usability testing, persona creation), ensuring WCAG accessibility compliance, and managing cross-platform implementation (web, mobile, desktop). Ideal for developing complex, inclusive, and highly structured digital products.

An expert specialist for rigorous visual validation, focusing on UI testing, design system compliance, and WCAG accessibility verification. This skill systematically analyzes visual evidence for cross-platform consistency, pixel-perfect accuracy, and adherence to modern design standards, utilizing principles from visual regression testing and comprehensive QA methodologies.

This comprehensive guide outlines the core principles for developing immersive Virtual and Augmented Reality (VR/AR) applications. It covers critical aspects such as platform selection (Quest, ARKit, ARCore), mandatory performance metrics (FPS, frame budget), user comfort techniques (motion sickness prevention), and best practices for spatial interaction and world design. Essential reading for engineers building next-generation spatial computing experiences.

Generates high-fidelity mobile and web UI/UX mockups with atomic design principles, responsive layouts, and accessible design tokens via muapi.ai for product requirements that need professional wireframes or design systems.

An expert guide for planning, designing, and implementing statistically rigorous A/B tests and product experiments. It covers core principles like formulating strong hypotheses, selecting primary/guardrail metrics, calculating sample sizes, and analyzing results to drive actionable business insights.

This comprehensive guide outlines best practices for building reliable and robust AI agent harnesses. It covers optimizing action spaces, defining structured tools, managing observation formats, and implementing essential error recovery contracts. Use these principles to dramatically improve agent completion rates, manage context budgets effectively, and transition AI prototypes into stable, production-grade autonomous systems.