multimodal

A guide to giving an AI agent images along with text so it can analyze visual content. It includes examples of sending image data to an agent in a C# application.

In plain words
What is it for?
It helps build image-aware agents, pass image URLs or content with messages, and choose credentials for Azure-based applications.
Why use it?
Text-only requests cannot provide the visual information needed to inspect images, screenshots, or other graphics.

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/multimodal
Clone the repo
git clone --depth 1 https://github.com/managedcode/dotnet-skills
Per session 8 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,697 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 $0.00008 $0.01697
Opus 5 $0.00004 $0.00848
Sonnet 5 $0.00002 $0.00339
Haiku 4.5 $0.00001 $0.00170

Measured 2d ago against content hash 75c9da8e726b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

multimodal 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/multimodal.md · 231 lines

How it starts

The opening of the file, as written. The whole thing — 231 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Using images with an agent

This tutorial shows you how to use images with an agent, allowing the agent to analyze and respond to image content.

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

Passing images to the agent

You can send images to an agent by creating a ChatMessage that includes both text and image content. The agent can then analyze the image and respond accordingly.

First, create an AIAgent that is able to analyze images.

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

[!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.

Next, create a ChatMessage that contains both a text prompt and an image URL. Use TextContent for the text and UriContent for the image.

ChatMessage message = new(ChatRole.User, [
    new TextContent("What do you see in this image?"),
    new UriContent("https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg", "image/jpeg")
]);

Run the agent with the message. You can use streaming to receive the response as it is generated.

Read the full file on GitHub · 231 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 · 231 lines · 8 tokens per session scan A 75c9da8e726b

Subscribe to this mod's changes

multimodal is an agent published in the GitHub repository managedcode/dotnet-skills (477 stars, last pushed 2d ago), licensed MIT. It adds 8 tokens to every session and 1,697 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.