Skill UI

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.

Synchronizes mature lessons from a domain-specific memory file into the matching instruction file inside VS Code, letting you choose global or workspace scope so you can preserve knowledge, cut redundancy, and finalize updates in a controlled merge process.

A Socratic mentoring workflow that coaches junior developers and AI newcomers through questions, encouraging reflection, Copilot-assisted loops, and safe learning practices without handing out solutions.

A comprehensive guide for creating, updating, refactoring, and reviewing solutions built on the Microsoft Agent Framework. This skill provides unified best practices for both .NET and Python environments, serving as a modern successor to Semantic Kernel and AutoGen. It emphasizes adherence to the latest official documentation, async patterns, robust error handling, and structured agent/workflow orchestration for complex AI applications.

Reads `.agent.md` or `.prompt.md` files, assesses task complexity, tooling, and requirements, then recommends the most cost-efficient GitHub Copilot model(s) (e.g., GPT-5, Claude Sonnet) with rationale for users across different subscription tiers and priorities.

This tool searches the current repository and lists all pull requests assigned to the user. It provides comprehensive details for each PR, including its purpose and scope. The output is highly functional, highlighting pending review status, detailing any failed checks (with suggested fixes), and offering to automatically request a Copilot review to maintain continuous development flow. Ideal for daily workflow status checks.

Provides operation-aware guidance for configuring n8n nodes, highlighting property dependencies, required fields, and when to use different get_node detail levels during workflow setup and troubleshooting.

This guide provides proven architectural patterns for building complex, reliable, and scalable workflows using n8n. It covers core patterns like Webhook processing, HTTP API integration, database synchronization, AI agent design, and scheduled tasks. Learn how to select the right pattern and utilize advanced components for robust automation.

Guides creation or updates of object-oriented component documentation by analyzing code or existing docs, then applying C4/Arc42/IEEE templates to capture architecture, interfaces, and quality traits.

Automates Outlook mail, calendar, contacts, folders, and attachments through the Rube MCP-powered Composio toolkit, letting you orchestrate KQL/OData searches and event/contact management once connections and tool schemas are established.

A structured methodology for coordinating multiple, simultaneous investigation threads to determine the root cause of complex system failures, performance regressions, or integration bugs. This skill decomposes a large problem into independent tracks (e.g., database, application code, infrastructure), assigns ownership, and manages structured sync points (Continue/Pivot/Converge) to converge on a solution faster than serial debugging. Essential for high-stakes production incident response.

Phoenix Evals lets teams build evaluators for AI/LLM apps by wiring deterministic code with LLM nuance, running Python or TypeScript workloads, validating against humans, and iterating through error analysis, RAG, and production workflows.