Skill UI

This meta-skill set provides a structured framework covering the entire software development lifecycle (SDLC). It guides developers through every phase, from initial concept refinement and requirement specification to incremental implementation, testing, code review, and deployment. It enforces critical professional behaviors like surfacing assumptions, managing ambiguity, and maintaining scope discipline to ensure high-quality, robust engineering outcomes.

This framework provides a rigorous, multi-dimensional guide for conducting code reviews. It evaluates five critical axes: correctness, readability, architecture, security, and performance. Use this process before merging any code change, especially when reviewing PRs, refactoring, or evaluating code produced by AI agents, to ensure continuous improvement and maintain high code health.

This skill provides robust mechanisms to verify the integrity of AI agent plugins, tools, and dependencies. It generates deterministic SHA-256 manifests (INTEGRITY.json) for all components, allowing users to detect unauthorized modifications, track provenance, and ensure that deployed assets match their published versions. Use this during CI/CD pipelines, code review, and pre-production promotion to secure the entire agent ecosystem.

This guide details the process of creating and managing 'Agent Users' within Microsoft Entra ID. Agent Users are specialized identities that allow AI agents to function as digital workers, giving them user-level capabilities (e.g., accessing Exchange mailboxes or Teams) while maintaining robust security boundaries. It covers using the Microsoft Graph API and PowerShell to provision and configure these agents.

An advanced, AI-powered agent designed to generate comprehensive and workable unit tests for virtually any programming language (e.g., Python, C#, Java, Go, TypeScript). It operates via a sophisticated multi-agent pipeline (Research → Plan → Implement → Build → Test → Fix → Lint). This ensures generated tests are not only written following project conventions but also compile, pass all tests, and effectively improve code coverage.

This comprehensive guide provides a detailed framework for authoring effective and structured SKILL.md files for AI coding agents. It covers best practices for structuring content, including frontmatter fields, defining natural language triggers, establishing core principles, and incorporating advanced elements like decision trees and verification checklists, ensuring agents receive clear, actionable, and consistent technical guidance.

Checks AI agent implementations against the OWASP Agentic Security Initiative Top 10 risks, producing findings on controls, vulnerabilities, and recommendations for prompt injection, tool governance, escalation, logging, identity, policy, supply chain, and behavioral monitoring before production or audit.

Fetches real-time Azure retail prices from the public Azure Retail Prices API and guides credit estimations for Copilot Studio agents, covering compute, storage, networking, databases, AI, and Copilot billing scenarios.

Interactive training for the GitHub Copilot CLI with guided lessons, quizzes, scenario challenges, and a reference covering slash commands, shortcuts, agents, MCP, and configuration; say “cliexpert” to begin.

The GitHub Copilot SDK empowers developers to embed advanced, agentic AI workflows directly into their proprietary applications. It provides a programmatic interface to Copilot's production-tested agent runtime, allowing you to define complex agent behaviors, manage tool invocation, process file edits, and implement real-time streaming responses. Ideal for building custom, highly intelligent tools and automating complex tasks across multiple languages (Python, TypeScript, Go, .NET).

This skill provides advanced debugging capabilities for failing Power Automate cloud flows using the FlowStudio MCP server. Unlike the limited status codes from the standard Graph API, this tool gives agents deep, action-level inputs and outputs, allowing users to find the true root cause of failures. It is essential for diagnosing complex issues like expression failures, connector authentication errors, or internal run errors.

This is the foundational plumbing layer connecting AI agents to the Power Automate platform via FlowStudio MCP. It provides essential capabilities such as secure authentication setup, robust tool discovery (`list_skills`, `tool_search`), and handling complex, oversized API responses. It serves as the prerequisite layer for specialized workflow skills (e.g., building, debugging, monitoring).