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.
npx agentmods add agents/managedcode/dotnet-skills/structured-outputsgit clone --depth 1 https://github.com/managedcode/dotnet-skillsWhat 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.
| Model | Per session | Once 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 |
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.
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
ChatClientAgentsupports 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]
DefaultAzureCredentialis 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.
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.
- 2d ago First seen · 484 lines · 9 tokens per session scan A 5001baa2f454
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.
Other agents, from other repositories
observability
Prometheus-metrikker, OpenTelemetry-tracing, Grafana-dashboards og varsling.
research-agent
Utforsker kodebaser, undersøker problemer og samler kontekst før implementering.
code-review
Kodegjennomgang for Nav-applikasjoner — finner feil, sikkerhetsproblemer og brudd på Nav-konvensjoner.
rust-agent
Idiomatisk Rust-utvikling med cargo, clippy, error handling, async/tokio, unsafe og testing.
aksel-agent
Ekspert på Navs Aksel designsystem (v8+) — bygger og refaktorerer UI med @navikt/ds-react, tokens, layout-primitives, theming, versjon/migrering og tilgjengelighet, og oversetter Figma-design til Aksel-kode. Drevet av aksel-builder-skillen og Aksel MCP som fasit.
MAF Migration Agent
Use when migrating a .NET codebase to Microsoft Agent Framework (MAF) 1.3.0. Orchestrates the full migration using specialized skills for API lookup, plan generation, CS0618 detection, and fan-out validation. Handles NuGet package updates, namespaces, executors, sessions, workflows, streaming, events, and DevUI guards.