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/multimodalgit 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 | $0.00008 | $0.01697 |
| Opus 5 | $0.00004 | $0.00848 |
| Sonnet 5 | $0.00002 | $0.00339 |
| Haiku 4.5 | $0.00001 | $0.00170 |
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.
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]
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.
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.
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 · 231 lines · 8 tokens per session scan A 75c9da8e726b
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.
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.