Skill UI

Maps out a complete topical authority structure by defining a pillar page, generating prioritized cluster articles (8-15), building a detailed internal link map, and performing a content gap analysis. This skill is essential for comprehensive SEO content strategy, ensuring all written content supports a core topic and identifies untapped AEO opportunities.

Create, update, and connect nodes/edges inside Obsidian .canvas files, enabling structured mind maps, flowcharts, and visual canvases by validating IDs, spacing, and JSON integrity.

This skill analyzes Azure resource groups in depth, identifying all resources, their configurations, and complex interdependencies. It maps relationships—including network connections, data flows, and managed identities—to generate comprehensive, detailed Mermaid architecture diagrams. Use this when you need a clear, structured visualization and full documentation of an Azure environment's topology.

Generates Excalidraw diagrams from natural language prompts, covering flowcharts, relationship maps, mind maps, architecture, data flow, swimlane, class, sequence, and ER diagrams for communicating processes and systems.

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.

A comprehensive tool for managing website SEO sitemaps. It can validate existing XML sitemaps against Google's latest best practices, checking for broken URLs, outdated dates, and structural issues. Alternatively, it can guide the user through generating a new, optimized sitemap structure and XML file, ensuring all critical pages are indexed correctly for search engines.

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.

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.

DeepTools is a comprehensive command-line toolkit for processing and analyzing high-throughput sequencing data. It supports workflows for ChIP-seq, RNA-seq, ATAC-seq, and other NGS experiments. Core capabilities include converting BAM files to normalized coverage tracks (bigWig), performing quality control (QC), sample correlation analysis, and generating publication-quality visualizations, such as heatmaps and profile plots across genomic regions.

A powerful Python library that extends pandas to enable complex spatial operations on vector geometric data. It supports reading and writing diverse formats, including Shapefile, GeoJSON, and GeoPackage. Users can perform advanced GIS tasks such as spatial joins, buffering, overlay analysis, calculating areas, managing Coordinate Reference Systems (CRS), and generating interactive choropleth maps, making it essential for geographic data science projects.

DeepXiv provides a structured and progressive method for accessing open-access academic literature. Instead of forcing the download of entire papers, it allows users to search by topic or ID and progressively read content—from brief overviews and metadata maps to specific sections. This is ideal for researchers who need layered paper access, trend analysis, or quick, targeted knowledge retrieval without overwhelming context.

This skill provides real-time monocular depth estimation using advanced models like Depth Anything v2. It transforms live camera feeds by generating colorized depth maps, enabling depth overlays and detailed scene understanding. Crucially, it supports a 'privacy mode' that anonymizes visual identities by using depth-only transformation, preserving only the spatial layout and movement patterns for secure monitoring purposes. Optimized for both CoreML on macOS and PyTorch on other platforms.