Skill UI

This tool helps developers run comprehensive test suites using pytest and generates detailed code coverage reports. It identifies specific lines of code that have not been covered by tests, guiding developers to improve test quality until 100% coverage is achieved. Use it to ensure robust and reliable software.

Transforms shorthand, quasi-code, or fuzzy natural-language notes into production-ready implementations, bridging collaborators with different expertise and ensuring robust, expert-quality output.

This skill serves as a comprehensive index for the built-in QA Agent, mapping user topics and keywords (such as installation, configuration, skills, or memory) directly to specific QwenPaw official documentation paths and relevant source code entry points. It drastically reduces the need for blind searching by providing a structured guide, ensuring the QA Agent reads the most accurate and relevant files first.

Automates the creation of copy-paste ready implementation documentation by parsing a PR plan, extracting numbered steps, and emitting precise, executable markdown files with file paths, code blocks, and verification checklists for every action.

A comprehensive, five-stage methodology for reviewing code quality. This process systematically checks for requirements compliance, logical correctness, code maintainability, test coverage, and critical security/performance vulnerabilities. It provides actionable feedback categorized by severity (Blocker, Major, Minor, Nit), ensuring high standards for all merged code.

A comprehensive tool that analyzes complex codebases to generate detailed, structured architectural blueprints. It automatically detects and documents the entire technology stack, including primary languages (.NET, Java, Python, etc.), dependencies, versions, licensing, and implementation patterns. The output provides actionable documentation covering coding conventions, usage examples (API, data access), and visual architecture maps, ensuring consistency across guided software development projects.

This skill rigorously audits UI code against established design system conventions, focusing on adherence to design tokens, component ergonomics, accessibility standards, and mobile UX best practices. It ensures that the implementation is consistent with the defined style guide, providing a structured verdict and concrete, actionable fixes.

This skill guides the systematic process of converting vague ideas or initial requirements into complete, detailed, and approved technical specifications. It enforces a structured workflow, including context exploration, iterative questioning, proposing multiple options with trade-offs, and creating documented blueprints. Critically, it ensures that no implementation or code writing occurs until the design has been fully vetted and formally approved by the user.

A comprehensive guide on conducting effective and professional code reviews, tailored for domestic team cultures. It teaches techniques like using suggestions instead of commands, framing feedback as questions, implementing clear severity levels, and maintaining proper mixed Chinese/English annotation standards. Essential for improving code quality while preserving team harmony.

This technique helps locate video games when the primary information provided is not the game title, but rather indirect clues about the game's developing company. Clues can include the company's name meaning, founder background, corporate history, or foundation activities. You must first decode these clues to identify the company, and then search the company's associated game catalog.

This skill systematically analyzes an existing codebase to generate seven comprehensive technical documents. It covers the technology stack, architectural patterns, directory structure, coding conventions, external integrations, testing strategies, and technical concerns. It is invaluable for new team members onboarding, conducting project audits, or creating a complete, verifiable system knowledge base.

This guide provides comprehensive troubleshooting for common issues encountered when converting Figma designs to code using the Anima SDK. It covers authentication failures (Figma/Anima tokens), specific node/file lookup errors, code rate limits, and output quality problems, helping developers ensure accurate and robust code generation.