Skill UI

This guide provides a detailed template and directive for generating machine-readable, deterministic implementation plans. It is designed for complex software development tasks, such as adding new features, refactoring existing code, or designing system architecture. The output ensures that all steps are atomic, measurable, and structured for autonomous execution by AI agents or human teams, minimizing ambiguity and dependency.

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.

A comprehensive workflow designed for Product Managers and technical leads to systematically identify, prioritize, and document missing features in a software project. It guides users through project understanding, gap analysis, applying a scoring matrix for prioritization, developing detailed Minimum Viable Product (MVP) specifications, and structuring the output as actionable development issues (e.g., GitHub Issues) with dependency mapping and workload optimization.

A comprehensive toolkit designed to automate core Shopify operations via Rube MCP. It provides structured workflows for managing all key aspects of an e-commerce store, including products (listing, creation), orders (tracking, retrieval), customers, collections, and inventory levels. Utilizes direct tool calls for listing, searching, and bulk operations, making it ideal for integrating complex business logic into automated systems.

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.

Guides designers through using the Penpot MCP tools to craft professional UI/UX for web, mobile, and desktop apps, covering workflows, design systems, accessibility checks, and setup/troubleshooting steps for the Penpot MCP server.

A sophisticated, file-based system designed for organizing and tracking complex, multi-step projects. It utilizes structured Markdown files (task_plan.md, progress.md, findings.md) to maintain a complete record of plans, research findings, and progress updates. Ideal for project analysis, workflow management, and ensuring data integrity throughout the planning lifecycle.

Provides systematic Power BI performance troubleshooting guidance covering model optimization, DAX design, report layout, and capacity diagnostics, plus tool-driven measurement tips for faster page loads, interactions, and query execution.

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.