Skill UI

Translates every approval request, error, and technical output from Copilot CLI into clear, jargon-free English with color-coded risk cues, definitions, and step-by-step commentary for non-technical stakeholders so they always understand what happens and why.

The Phoenix CLI is a powerful tool for debugging complex LLM and agent workflows. It allows users to fetch detailed traces, spans, and sessions, analyze errors, and structure findings using open and axial coding techniques. It is essential for investigating complex LLM failures, building robust failure taxonomies, and guiding the next steps in application evaluation after initial instrumentation.

Generates detailed prompts to document end-to-end application workflows by auto-detecting architectures, stacks, entry points, services, data access, error handling, and tests across .NET, Java/Spring, React, microservices, and other tech stacks.

Analyzes Copilot guidance files and repository docs to craft structured README.md content, detailing the project purpose, architecture, technology stack, workflows, coding standards, testing approach, and contributing advice for fellow developers.

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 skill aggregates and summarizes the latest news from multiple authoritative Chinese sources across various categories, including Politics, Finance, Society, World, Tech, Sports, and Entertainment. It utilizes web browsing tools to open specified URLs, take content snapshots, and extract key headlines and detailed summaries, providing the user with a concise, structured report.

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.

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.

Convert a natural-language project specification into a runnable starter repository by parsing intents, planning architecture, and generating real code plus CI/env files for any tech stack.

Tracks every code change via structured JSON records, enforces a lifecycle state machine, and maintains session handoff context with scripts for init/create/update/status/resume/close/export workflows.

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.