Skill UI

Develop robust, multi-channel enterprise agents designed for the Microsoft 365 ecosystem, including Teams and Copilot Studio. This SDK provides a comprehensive Python framework featuring aiohttp hosting, advanced AgentApplication routing, real-time streaming responses, and secure authentication via MSAL. Ideal for building sophisticated, production-grade bots and automation tools that integrate deeply with enterprise Microsoft services.

This comprehensive guide provides step-by-step instructions and complete code examples for setting up and configuring the MaintainX REST API. It covers best practices for generating API keys, setting up secure environment variables, and implementing robust client wrappers in both TypeScript and Python. Use this skill when integrating CMMS data (such as work orders, assets, and locations) into external applications.

Guide for building high-quality MCP servers that let LLMs interact with external APIs via workflow-focused tools, SDKs, validation, and error handling in Python or TypeScript.

This guide details the process of building Model Context Protocol (MCP) servers. These servers are crucial for enabling Large Language Models (LLMs) to interact with external APIs and services, facilitating complex, real-world task completion. It provides comprehensive coverage on architectural planning, choosing appropriate languages (Python, TypeScript, C#), and selecting transport mechanisms (HTTP, stdio) for robust integration within enterprise ecosystems like Azure and Foundry.

Used for building, debugging, and extending MCP servers and clients. This skill implements robust connections between AI systems and external tools/data sources using structured protocols like JSON-RPC 2.0. Expertise includes defining tool schemas (Zod/Pydantic), configuring transport layers (HTTP/SSE/stdio), and scaffolding full-stack projects in TypeScript or Python.

Automatically collects comprehensive diagnostic evidence for Mistral AI support tickets. This bundle includes environment details (OS, Node/Python versions), installed SDK versions, API connectivity test results, available models, and recent error logs. It is essential for reproducing and diagnosing persistent issues when contacting technical support.

This comprehensive guide provides minimal working examples for integrating with the Mistral AI API. It demonstrates core LLM functionalities including basic chat completion, streaming responses, multi-turn conversations, and generating structured JSON output. Use this guide when starting a new Mistral integration, testing API connections, or learning advanced AI patterns using TypeScript or Python.

This guide provides comprehensive instructions for installing and configuring the official Mistral AI SDK (for both Python and Node.js). It covers setting up API keys via environment variables, verifying the connection, and implementing secure credential storage using Secret Managers (GCP/AWS) for production environments. Ideal for starting any new Mistral AI project.

This guide provides production-ready patterns for integrating the Mistral AI SDK in both TypeScript and Python. It covers essential best practices such as singleton client management, handling structured JSON output, implementing streaming responses, concurrent asynchronous processing, and robust error handling with exponential backoff. Use this when establishing team coding standards or refactoring Mistral API usage.

Guides setting up modern Python projects with uv, ruff, ty, pytest, prek, and security checks, covering initialization, pyproject configuration, dependency and tool management, quick-start scripts, full project layout, and migrations from legacy tooling.

A comprehensive tool suite for Global Administrators to automate Microsoft 365 tenant setup, user lifecycle management, and security hardening. It provides PowerShell and Python generators for bulk user provisioning, implementing Conditional Access policies (MFA), running security audits, and ensuring compliance across Azure AD, Exchange Online, and Teams.

Guides writing Python code inside n8n Code nodes, covering recommended use cases, helper data access patterns, Beta vs Native modes, and webhook/data handling rules so you can safely script workflow transformations with Python.