Skill UI

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.

Defines Salesforce Lightning Web Component, Aura, and Visualforce quality/security standards covering SLDS 2 styling, accessibility (WCAG 2.1 AA), data access patterns, component communication rules, XSS/CSRF protections, view state management, and Jest testing requirements for guided UI development and reviews.

Installs npm packages inside virtiofs-mounted Docker workspaces by copying package files to a container-local ext4 directory, running npm ci there, and symlinking node_modules back so native binaries avoid virtiofs crashes.

This skill automates the entire process of creating and integrating a DingTalk application and binding a QwenPaw bot. It utilizes a headed browser mode and manages complex user flows, including pausing for manual login confirmation and ensuring all configuration changes are properly published. It supports customizing app details, uploading required images, and setting up the bot capability, making the setup process seamless and robust.

Reads and summarizes local text-based files such as Markdown, JSON, CSV, and source code, including quick type checks and smart tailing for big logs while skipping PDFs, images, and binaries.

Audits crawlability, metadata, structured data, Core Web Vitals, and content signals while planning keyword mapping, internal linking, and sitemap fixes so teams can steadily boost organic visibility.

Provides a comprehensive audit of content quality, focusing on E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) signals, readability, and structural integrity. Use this tool when reviewing content for SEO optimization, assessing academic citation readiness, or ensuring adherence to modern search engine and AI best practices.

This comprehensive tool provides real-time, live SEO data directly from the DataForSEO platform. It allows users to analyze live SERPs (Google, YouTube), conduct deep keyword research (volume, difficulty, intent), monitor backlink profiles, analyze competitor domains, and perform on-page content audits. It is crucial for digital marketers and content creators who need up-to-date metrics, especially for tracking AI visibility and LLM mentions, moving beyond static best practices.

A comprehensive guide to optimizing website content for modern AI search systems, including ChatGPT, Perplexity, and Google AI Overviews. It covers structural improvements, maximizing citability scores, incorporating multi-modal elements, building brand authority, and implementing technical standards like llms.txt and proper server-side rendering (SSR). Essential for maximizing organic reach in the LLM era.

A comprehensive tool for validating, generating, and auditing hreflang tags for multilingual and multi-regional websites. It checks critical SEO requirements, including self-referencing tags, bidirectional return links, proper x-default implementation, and adherence to ISO language/region codes. Use this when optimizing content for global audiences or ensuring Google correctly indexes all language versions.

Perform a comprehensive, deep-dive audit on a single URL, covering all critical aspects of Search Engine Optimization. Analysis includes on-page elements (title, headings, meta tags), content quality (readability, E-E-A-T), technical structure (schema, canonical, OG tags), image optimization, and core web vitals potential issues. Ideal for SEO audits and content quality checks.

Comprehensive audit covering all aspects of web technical SEO, including crawlability (robots.txt, sitemaps), indexability, security headers, and URL structure. It deeply analyzes Core Web Vitals (LCP, INP, CLS) and assesses complex rendering scenarios like JavaScript SEO and structured data implementation for optimal search engine visibility.