Skill UI

This tool generates a complete, production-ready PHP Model Context Protocol (MCP) server project. It automatically scaffolds the entire structure, including tools, resources, prompts, and comprehensive tests, utilizing the official PHP SDK. It provides a standardized, robust starting point for developers building AI-integrated backend services in PHP.

Guides a Power BI DAX expert through performance, readability, best-practice, and maintainability reviews; recommends variable reuse, context tuning, and error handling; then outputs an optimized formula plus justification for analytics models.

This tool acts as an expert prompt engineer, guiding users through a systematic discovery process to create highly structured, production-ready prompts for AI assistants like GitHub Copilot. It covers defining persona, specifying complex tasks, managing context variables, integrating tools, and enforcing strict output standards, ensuring the resulting prompt is comprehensive and actionable for advanced AI agents.

A comprehensive reference for diagnosing and fixing silent breaking changes in React 18 class components. This guide covers how React 18 automatically batches state updates in asynchronous contexts (e.g., setTimeout, Promises, async/await), providing patterns for handling state reads after awaiting, and offering guidance on when to correctly use `flushSync` versus refactoring.

This guide serves as a comprehensive reference for source-file migration patterns required when upgrading to React 19. It details critical API changes, such as updating `ReactDOM.render` to `createRoot().render()`, modernizing ref handling, and adjusting legacy context usage. It is essential for developers migrating large, existing React applications to ensure compatibility with the latest React standards.

Scans repository context and chat history to recommend awesome-copilot Custom Agent files that are missing or outdated locally, outlines relevance/rationale, and waits for user approval before installing or updating.

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 scaffold generator for building Model Context Protocol (MCP) servers using TypeScript and Node.js. This tool provides a complete, production-ready boilerplate, including proper project structure, dependency management (e.g., @modelcontextprotocol/sdk, zod), and implementation details for tools and resources. It supports both HTTP and stdio transport mechanisms, ensuring type safety, robust error handling, and best practices for modern backend development.

This structured prompt guides an AI model to proactively analyze a user's question and systematically list all necessary files for accurate answering. It forces the AI to categorize required context into 'Must See' (critical), 'Should See' (helpful), 'Already Have,' and 'Uncertainties.' Ideal for complex coding tasks, debugging, or feature implementation that spans multiple codebase files.

Guides Copilot through the WorkIQ CLI/MCP server to fetch live Microsoft 365 data—emails, meetings, docs, Teams chatter, and people info—providing context, summaries, blockers, and follow-up recommendations for planning or action.

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.

This guide outlines the structured methodology for initiating code reviews using a dedicated sub-agent. It dictates when (after completing tasks, implementing critical features, or before merging) and how to provide the necessary context (SHA hashes, implemented code, requirements) to ensure the work product is thoroughly evaluated. By adopting this process, developers can catch architectural flaws and bugs early in the development lifecycle, improving code quality and maintainability.