Skill UI

This skill focuses on building production-quality, accessible, and responsive user interfaces. It involves creating components, implementing layouts, and managing state while adhering to design systems and WCAG standards. The goal is to avoid generic AI aesthetics and ensure the UI looks like it was built by a professional engineer. It covers component architecture, state management strategies, and design system adherence for high-quality web applications.

A comprehensive guide for designing, implementing, and reviewing scalable microservices using gRPC in Go. It covers critical best practices including structured protobuf organization, implementing interceptors for cross-cutting concerns, managing connection deadlines, handling standardized gRPC status codes, and ensuring graceful shutdown for robust distributed systems.

This skill guides developers in writing robust and defensive Go code. It addresses common pitfalls that lead to runtime panics and silent data corruption, such as nil map writes, slice backing array aliasing, silent numeric truncation (int64 to int32), and inaccurate float comparisons. Use this when designing highly reliable Go systems that must withstand typical programmer errors and maintain data integrity.

A comprehensive skill guide for designing, implementing, and running robust End-to-End (E2E) and integration tests in Flutter projects using Patrol 4.x. Use this to validate complex user journeys, capture UI regressions, and test native interactions (permissions, system dialogs) across multiple platforms (Android, iOS, Web).

This skill generates highly structured DESIGN.md files, acting as a semantic design system for Google Stitch. It translates complex, anti-generic frontend principles—including typography, color calibration, component behavior, and motion physics—into actionable, natural-language rules. Use it as the single source of truth to guide AI in generating premium, non-clichéd, professional user interfaces.

This advanced prompt acts as a structured guide for generating comprehensive, enterprise-grade technical implementation plans. It forces the detailed breakdown of a feature based on a PRD, covering system architecture (Mermaid diagrams), database schema design, API specifications, frontend component hierarchy, and deployment strategies, all while adhering to a monorepo structure. Ideal for large-scale SaaS development.

This comprehensive guide covers best practices for building robust database systems. It teaches crucial concepts like schema normalization, effective indexing strategies, selecting the right database (e.g., SQLite vs PostgreSQL) and ORM, and optimizing queries to prevent common performance issues like N+1 problems. It emphasizes making context-aware architectural decisions.

A comprehensive methodology guiding technical professionals through the design process before coding. It helps structure complex features by producing detailed design documents, including system overviews, data models, API specifications, multiple trade-off analyses, and implementation plans, ensuring robustness and clarity from the start.

Catalogs 42 cloud-agnostic design patterns that architects can apply when designing, reviewing, or operating distributed systems to boost reliability, performance, messaging, security, and deployment outcomes.

A comprehensive guide for engineers, architects, and DevOps teams on implementing General Data Protection Regulation (GDPR) best practices. This skill covers Privacy by Design, data minimization, purpose limitation, retention policies, secure API design, and compliant logging practices. Use it when handling any personal data, designing new features, or reviewing systems for data privacy compliance.

This skill provides comprehensive guidelines and techniques for safe code refactoring. It focuses on improving code structure, readability, and maintainability without altering the external behavior or functionality of the system. Learn to address common code smells, such as long methods, duplicated logic, god objects, and primitive obsession, using established design patterns and best practices. It emphasizes that refactoring should be gradual, test-driven, and methodical.

This guide maps user questions and topics (e.g., configuration, memory, skills, CLI) to specific, relevant documentation paths and source code entry points within the QwenPaw ecosystem. It is designed for built-in QA Agents to eliminate aimless searching, ensuring the agent reads the most accurate files to provide comprehensive and precise answers about the system's features.