Tutorials Agentic AI with .NET Tutorial

Native Functions as Tools

Native Functions as Tools: free step-by-step lesson with examples, common mistakes, and interview tips — part of Agentic AI with .NET Tutorial on Toolliyo Academy.

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Agentic AI with .NET Tutorial · Lesson 14 of 120

Native Functions as Tools

Foundations & SKTools & RAGProduct & OpsProjects

Foundations & SK · 1 — Agent basics · ~6 min · Semantic Kernel

What is this?

Native functions are C# methods you expose to the model as tools. The model proposes a call; your code runs the method and returns a result.

Why should you care?

This is how agents fetch orders, create tickets, or search docs without inventing data.

See it live — copy this example

Use .NET 8+. Run Semantic Kernel samples in a console or Web API. Keep API keys in user secrets or environment variables — never in source.

using System.ComponentModel;
using Microsoft.SemanticKernel;

public class OrdersPlugin
{
    [KernelFunction, Description("Get order status by id")]
    public string GetStatus([Description("Order id")] string orderId)
        => $"Order {orderId}: Shipped"; // replace with real service
}

// builder.Plugins.AddFromType<OrdersPlugin>();

What happened?

  • KernelFunction marks a tool.
  • Description helps the model choose it.
  • You still enforce auth in the method body.

Practice next

  1. Add OrdersPlugin to a kernel.
  2. Invoke the function directly from C# first.
  3. Then let a prompt request the status.
  4. Add GetCustomerOrders(customerId).
  5. Return a short summary string only.

Remember

Native functions = real C# tools. Descriptions guide tool choice. Validate inputs in code.

Order tool

Support agent must not invent shipment status.

Outcome: Status comes from GetStatus only.

Interview prep for this lesson

Practice these questions aloud after reading—each links to a full structured answer.

Junior Detailed
Explain Concepts in the context of Agentic AI with .NET.
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define Concepts…
Mid Detailed
What are common mistakes teams make with LLMs when using Agentic AI with .NET?
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define LLMs in p…
Senior Detailed
How would you debug a production issue related to RAG in a Agentic AI with .NET application?
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define RAG in pl…
Mid Detailed
Compare two approaches to Ethics—when would you choose each?
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define Ethics in…
Junior Detailed
Describe a real-world scenario where Production mattered in a Agentic AI with .NET project.
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define Productio…
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Agentic AI with .NET Tutorial
Course syllabus

Agentic AI with .NET Tutorial

Agentic Foundations
Semantic Kernel
.NET AI Wiring
Framework Choices
RAG & Memory
Tools & Automation
Multi-Agent Patterns
ASP.NET Core Integration
Security & Governance
Cloud & Operations
Advanced Agent Behavior
Capstone Projects
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