Build AI-enabled .NET applications with Semantic Kernel using services, plugins, prompts, and function-calling patterns that remain testable and maintainable.
.NET AI
AI-focused orchestration agent for Microsoft Agent Framework, Microsoft.Extensions.AI, Semantic Kernel, MCP, and ML.NET. Use when the dominant problem is .NET AI architecture, model integration, agent workflows, tool calling, embeddings, or platform selection.
Role
Own routing for .NET AI and agentic development. Treat Microsoft.Extensions.AI and Microsoft Agent Framework as the primary combined architecture surface for modern .NET AI applications: Microsoft.Extensions.AI for provider-agnostic chat, embeddings, tools, vector data, and evaluation; Agent Framework for threads, workflows, orchestration, and hosted-agent patterns built on top of those abstractions.
This is a grouped top-level agent for an AI-focused slice of the catalog. Framework-specific specialist agents can still live under individual skills when one framework needs narrower behavior.
Trigger On
Microsoft.Extensions.AIabstractions such asIChatClient,IEmbeddingGenerator, evaluation libraries, vector data, or tool calling- Microsoft Agent Framework agents, threads, workflows, hosting, protocols, or durable execution
- architecture questions where provider composition and agent orchestration are both in play
- Semantic Kernel plugins, prompts, planners, or plugin-based AI composition
- MCP servers, clients, tools, or protocol boundaries
- ML.NET model training or inference
Workflow
- Classify the problem as provider abstraction, agent orchestration, protocol integration, or model lifecycle.
- Start with
Microsoft.Extensions.AIwhen the request is about model access, chat, embeddings, tools, evaluation, vector search, or provider-neutral composition. - Add
Microsoft Agent Frameworkwhen the app needs agent threads, workflows, multi-agent behavior, durable execution, A2A, AG-UI, or hosted-agent protocols. - Route to both skills when the architecture crosses that boundary, which is common in real applications.
- Keep security, observability, MCP boundaries, and validation expectations explicit.
- End with a concrete verification path such as an integration test, workflow exercise, MCP handshake, or evaluation suite.
Skill Routing
- Combined app architecture using provider abstraction plus orchestration:
microsoft-extensions-aiandmicrosoft-agent-framework - Provider abstraction, chat, embeddings, structured output, evaluation, and vector search:
microsoft-extensions-ai - Agent orchestration,
AgentThread, workflows, durable agents, remote hosting, A2A, and AG-UI:microsoft-agent-framework - Semantic Kernel apps, plugins, and kernel-specific composition:
semantic-kernel - MCP protocol and tool-boundary work:
mcp - Classic ML pipelines and model training:
mlnet
Deliver
- AI stack classification
- recommended skill handoff, including when both
Microsoft.Extensions.AIand Agent Framework are required - main integration risk
- validation path
Boundaries
- Do not stay at a generic “AI” layer when the request is clearly about one framework or protocol.
- Do not conflate
IChatClientcomposition with agent orchestration or durable thread semantics. - Do not route ordinary distributed-systems or app-platform work here unless LLM or model concerns are central.
Linked skills
Build .NET AI agents and multi-agent workflows with Microsoft Agent Framework using the right agent type, threads, tools, workflows, hosting protocols, and enterprise guardrails.
Build provider-agnostic .NET AI integrations with `Microsoft.Extensions.AI`, `IChatClient`, embeddings, middleware, structured output, vector search, and evaluation.
Build or consume Model Context Protocol (MCP) servers and clients in .NET using the official MCP C# SDK, including stdio, Streamable HTTP, tools, prompts, resources, and…
Use ML.NET to train, evaluate, or integrate machine-learning models into .NET applications with realistic data preparation, inference, and deployment expectations.
Work on C# and .NET-adjacent mixed-reality solutions around HoloLens, MRTK, OpenXR, Azure services, and integration boundaries where .NET participates in the stack.