dotnet-microsoft-extensions-ai

Integrate provider-agnostic AI abstractions into .NET applications.

466|35|Updated Mar 15, 2026
One-click install
npx skills add https://github.com/managedcode/dotnet-skills --skill dotnet-microsoft-extensions-ai
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: dotnet-microsoft-extensions-ai
Source: https://github.com/managedcode/dotnet-skills/tree/main/skills/dotnet-microsoft-extensions-ai
Command: npx skills add https://github.com/managedcode/dotnet-skills --skill dotnet-microsoft-extensions-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses the challenge of integrating AI capabilities into .NET applications without vendor lock-in, ensuring clean abstractions and testability.

Core Features & Use Cases

  • Provider-Agnostic AI: Use IChatClient and embedding abstractions that work with any AI provider.
  • Middleware Support: Easily add logging, caching, and telemetry to your AI interactions.
  • Testability: Mock AI clients for robust unit and integration testing.
  • Use Case: Develop a .NET application that can seamlessly switch between Azure OpenAI and a local AI model for chat completions, all while logging every interaction for auditing purposes.

Quick Start

Integrate provider-agnostic AI abstractions into your .NET application by referencing the Microsoft.Extensions.AI package.

Frequently Asked Questions about dotnet-microsoft-extensions-ai

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I avoid vendor lock-in when integrating AI chat clients in .NET?

Provider-agnostic AI abstractions in .NET prevent vendor lock-in by using interfaces like IChatClient, allowing you to switch between AI providers seamlessly without rewriting application code.

What's the best way to add logging and telemetry to .NET AI interactions?

Adding logging and telemetry to .NET AI interactions is best achieved using middleware composition, which intercepts requests to provide caching, telemetry, and auditing without altering core client logic.

Can I mock AI clients for unit testing in a .NET application?

Yes, you can mock AI clients for unit testing in .NET. Provider-agnostic abstractions enable testable implementations, allowing you to simulate chat completions and embedding responses reliably.

How do I switch between Azure OpenAI and a local AI model in .NET?

Switching between Azure OpenAI and a local AI model in .NET is done using provider-agnostic abstractions. The IChatClient interface standardizes integration, enabling seamless provider switching.

Does Microsoft.Extensions.AI support embedding abstractions for .NET applications?

Yes, Microsoft.Extensions.AI supports embedding abstractions for .NET applications. These provider-agnostic interfaces facilitate clean integration of embeddings alongside chat clients.

When do I need provider-agnostic AI abstractions in my .NET application?

You need provider-agnostic AI abstractions in .NET when standardizing AI provider integration, avoiding vendor lock-in, and ensuring testability across multiple chat completion and embedding services.