function-tools

A tutorial for giving an AI agent custom functions it can call while working. It uses C# and an Azure OpenAI chat-based agent as the example.

In plain words
What is it for?
Use it to add custom code actions to a compatible agent, such as looking up data or performing an application operation. The tutorial also explains which agent type supports caller-provided functions.
Why use it?
An agent cannot perform application-specific actions unless those actions are exposed to it as functions. This explains how to turn a C# method into a callable function.

Agent for Codex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/managedcode/prompterone/function-tools
Clone the repo
git clone --depth 1 https://github.com/managedcode/PrompterOne

Made for: Codex.

Per session 9 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,732 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00009 $0.01732
Opus 5 $0.00005 $0.00866
Sonnet 5 $0.00002 $0.00346
Haiku 4.5 $0.00001 $0.00173

Measured yesterday against content hash 78205f72ff74, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

function-tools scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

2 near-identical copies found in the catalogue:

.codex/skills/dotnet-microsoft-agent-framework/references/official-docs/tutorials/agents/function-tools.md · 197 lines

How it starts

The opening of the file, as written. The whole thing — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Using function tools with an agent

[!NOTE] The live Learn page for this legacy tutorial path now resolves to the canonical tools article at https://learn.microsoft.com/agent-framework/agents/tools/function-tools. This local file keeps the historical path so existing references inside the skill catalog remain stable.

This tutorial step shows you how to use function tools with an agent, where the agent is built on the Azure OpenAI Chat Completion service.

::: zone pivot="programming-language-csharp"

[!IMPORTANT] Not all agent types support function tools. Some might only support custom built-in tools, without allowing the caller to provide their own functions. This step uses a ChatClientAgent, which does support function tools.

Prerequisites

For prerequisites and installing NuGet packages, see the Create and run a simple agent step in this tutorial.

Create the agent with function tools

Function tools are just custom code that you want the agent to be able to call when needed. You can turn any C# method into a function tool, by using the AIFunctionFactory.Create method to create an AIFunction instance from the method.

If you need to provide additional descriptions about the function or its parameters to the agent, so that it can more accurately choose between different functions, you can use the System.ComponentModel.DescriptionAttribute attribute on the method and its parameters.

Here is an example of a simple function tool that fakes getting the weather for a given location. It is decorated with description attributes to provide additional descriptions about itself and its location parameter to the agent.

using System.ComponentModel;

[Description("Get the weather for a given location.")]
static string GetWeather([Description("The location to get the weather for.")] string location)
    => $"The weather in {location} is cloudy with a high of 15°C.";

When creating the agent, you can now provide the function tool to the agent, by passing a list of tools to the AsAIAgent method.

Read the full file on GitHub · 197 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 197 lines · 9 tokens per session scan A 78205f72ff74

Subscribe to this mod's changes

function-tools is an agent published in the GitHub repository managedcode/PrompterOne (42 stars, last pushed 3mo ago), licensed MIT. It adds 9 tokens to every session and 1,732 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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