Skill UI

This tool enables deep inspection and validation of web applications by connecting to the browser's DevTools Protocol (MCP). It allows agents to perform tasks like DOM inspection, capturing console logs, monitoring network requests, profiling performance, and taking screenshots in a live environment. Essential for debugging UIs, validating API integrations, and performing end-to-end automated testing.

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 skill guides the generation of a complete, production-ready Model Context Protocol (MCP) server using C# and .NET. It covers advanced architectural patterns, including Host builder setup, proper dependency injection, structured logging, and implementing robust functional tools. Ideal for developers building sophisticated AI agents or backend services that require standardized communication and tool invocation capabilities.

A comprehensive guide and set of tools for programmatically building, scaffolding, and deploying Power Automate cloud flows using the FlowStudio MCP server. It guides agents through the entire workflow, including checking for existing flows, resolving connection references, defining actions, and final deployment/testing, all without needing to open the portal.

This skill provides comprehensive tools to download, export, and deeply inspect existing Arize traces and spans. It is essential for understanding the full execution flow of complex LLM applications, debugging runtime errors, and performing root-cause analysis. Users can retrieve detailed data filtered by Trace ID, Span ID, or Session ID, enabling thorough analysis of conversational or multi-step agent behaviors.

This agent guides users in selecting the optimal Azure role assignment that strictly adheres to the principle of least privilege. Given a set of desired permissions, it utilizes specialized tools to either identify a suitable built-in role or generate a custom role definition. Finally, it provides actionable code snippets, including CLI commands and Bicep templates, ensuring proper and secure role assignment.

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).

Use terminal commands to discover, list, create, edit, move, copy, enable/disable, and delete AI agent skills across 11 tools, handling format conversions and scope overrides between global and project configurations.

A comprehensive guide for developers to build advanced, declarative agents for Microsoft 365 Copilot. This skill details the integration process using a Model Context Protocol (MCP) server, allowing the agent to connect with external systems, select tools, and handle complex authentication (OAuth 2.0/SSO). You will learn to generate key JSON manifests required for deployment.

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.

This micro-prompt guides AI agents to adopt the mindset of an interactive programmer. It emphasizes using the REPL (Read-Eval-Print Loop) for systematic system exploration and modification, treating the system state as the ultimate source of truth. It also reminds the agent to utilize structural editing tools and maintain todo lists, significantly improving the accuracy and efficiency of the development workflow in live coding environments.

A powerful command-line interface for managing and synchronizing AI skills and agents across dozens of AI tools (e.g., Claude, Cursor). It provides a unified source of truth for skill deployment, handling global and project-specific configurations. Use it to install, sync, update, discover, and audit complex AI workflows, including managing structured extras (rules, commands) and custom content transformations via extensions.