structured-outputs

A guide to making an AI agent return data in a defined structure, such as a record with fields for a person’s name, age, and occupation. This is called a structured output.

In plain words
What is it for?
Use it to define an output type and configure a compatible ChatClientAgent with Azure OpenAI or Azure AI Projects.
Why use it?
It makes agent responses easier for programs to validate and use than free-form text, when the selected chat client supports the feature.

Agent

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/dotnet-skills/structured-outputs
Clone the repo
git clone --depth 1 https://github.com/managedcode/dotnet-skills
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 3,917 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 $0.03917
Opus 5 $0.00005 $0.01959
Sonnet 5 $0.00002 $0.00783
Haiku 4.5 $0.00001 $0.00392

Measured 2d ago against content hash 5001baa2f454, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

structured-outputs 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 2d ago.

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.

catalog/Frameworks/Microsoft-Agent-Framework/skills/microsoft-agent-framework/references/official-docs/agents/structured-outputs.md · 484 lines

How it starts

The opening of the file, as written. The whole thing — 484 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Producing Structured Outputs with Agents

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

This tutorial step shows you how to produce structured outputs with an agent, where the agent is built on the Azure OpenAI Chat Completion service.

[!IMPORTANT] Not all agent types support structured outputs natively. The ChatClientAgent supports structured outputs when used with compatible chat clients.

Prerequisites

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

Define a type for structured outputs

First, define a type that represents the structure of the output you want from the agent.

public class PersonInfo
{
    public string? Name { get; set; }
    public int? Age { get; set; }
    public string? Occupation { get; set; }
}

Create the agent

Create a ChatClientAgent using the Azure AI Projects Client.

using System;
using Azure.AI.Projects;
using Azure.Identity;
using Microsoft.Agents.AI;

AIAgent agent = new AIProjectClient(
    new Uri("<your-foundry-project-endpoint>"),
    new DefaultAzureCredential())
        .AsAIAgent(
            model: "gpt-4o-mini",
            name: "HelpfulAssistant",
            instructions: "You are a helpful assistant.");

[!WARNING] DefaultAzureCredential is convenient for development but requires careful consideration in production. In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid latency issues, unintended credential probing, and potential security risks from fallback mechanisms.

Structured outputs with RunAsync<T>

The RunAsync<T> method is available on the AIAgent base class. It accepts a generic type parameter that specifies the structured outputs type. This approach is applicable when the structured outputs type is known at compile time and a typed result instance is needed. It supports primitives, arrays, and complex types.

Read the full file on GitHub · 484 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. 2d ago First seen · 484 lines · 9 tokens per session scan A 5001baa2f454

Subscribe to this mod's changes

structured-outputs is an agent published in the GitHub repository managedcode/dotnet-skills (477 stars, last pushed 2d ago), licensed MIT. It adds 9 tokens to every session and 3,917 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.