Skill UI

This comprehensive scaffold sets up a complete, modern Power Apps Code App project structure using Vite, React, and TypeScript. It guides developers through initializing the project with PAC CLI, configuring SDK integration, and setting up best practices for connecting to 1,500+ Power Platform connectors (e.g., Office 365, SharePoint, SQL Server). Ideal for building complex, code-first enterprise applications within the Power Platform ecosystem.

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.

Acts as a senior software engineer to meticulously review and refactor entire codebases. This skill ensures that the code is clean, highly maintainable, and strictly adheres to defined coding standards and best practices specified across multiple project instruction files. It guarantees the integrity of the existing file structure and ensures all unit tests remain passing after modifications.

A universal assistant for conducting deep code reviews across major SQL databases (MySQL, PostgreSQL, SQL Server, Oracle). It rigorously analyzes SQL code for critical vulnerabilities (like SQL injection), performance bottlenecks, maintainability issues, and adherence to industry best practices. Features include security audits, index optimization recommendations, query structure analysis, and schema design validation, ensuring robust and secure database development.

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.

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.

A comprehensive guide covering best practices for Terraform and OpenTofu. It provides structured advice on module hierarchy, directory organization, naming conventions, and advanced testing strategies (including native testing and policy as code). Use this skill when designing, refactoring, or implementing robust Infrastructure as Code (IaC) pipelines and multi-environment deployments.

Update existing specification files for solutions based on new requirements or code changes. Ensures documentation is optimized for Generative AI consumption, machine-readable, and self-contained. Follows structured formatting standards including requirements, constraints, interfaces, and acceptance criteria to facilitate AI-driven development workflows.

Transforms you into a 10x web engineer, guiding work across HTML, CSS, JavaScript, web APIs, HTTP/HTTPS, security, performance, accessibility, and infrastructure so you can deliver standards-compliant, high-quality front- and back-end solutions.

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.