PrompterOne: Agent for Claude Code

.codex/skills/dotnet-microsoft-agent-framework/references/official-docs/tutorials/agents/images.md

images is an agent for Claude Code, Codex from managedcode/PrompterOne. It costs 8 tokens per session (933 once invoked), scanned A, original, MIT.

A tutorial showing how to send images to an AI agent along with text so the agent can inspect their contents.

In plain words
What is it for?
Use it to build a .NET agent that receives an image URL and answers questions about what the image contains.
Why use it?
It explains the message format needed when an agent must use both written instructions and visual information.

Agent for Claude CodeCodex

Written for Codex and Claude Code: installed under .codex/, but also a Claude Code subagent (agents/*.md).

This is managedcode/PrompterOne's own configuration. It tells Claude Code and Codex how to work on PrompterOne itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything PrompterOne configures →

Reuse

Borrowing it

Nothing to install: this file belongs to managedcode/PrompterOne. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/managedcode/PrompterOne/main/.codex/skills/dotnet-microsoft-agent-framework/references/official-docs/tutorials/agents/images.md
Clone the repo
git clone --depth 1 https://github.com/managedcode/PrompterOne

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for images

README.md
[![agentmods](https://agentmods.dev/badge/agents/managedcode/prompterone/images/github.svg)](https://agentmods.dev/agents/managedcode/prompterone/images)
Your own site
<a href="https://agentmods.dev/agents/managedcode/prompterone/images"><img src="https://agentmods.dev/badge/agents/managedcode/prompterone/images/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for images

Your own site · 80×15
<a href="https://agentmods.dev/agents/managedcode/prompterone/images"><img src="https://agentmods.dev/badge/agents/managedcode/prompterone/images.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
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 933 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00008 $0.00933
Opus 5.5 $0.00003 $0.00373
Sonnet 5.5 $0.00002 $0.00187
Haiku 4.5 $0.00001 $0.00093

Measured 1mo ago against content hash fa9ecb4ee8cb, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

images 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 1mo 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

  • images — 100% identical, 0 lines differ
.codex/skills/dotnet-microsoft-agent-framework/references/official-docs/tutorials/agents/images.md · 131 lines

How it starts

The opening of the file, as written. The whole thing — 131 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.

Prerequisites

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

::: 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 AzureOpenAIClient(
    new Uri("https://<myresource>.openai.azure.com"),
    new AzureCliCredential())
    .GetChatClient("gpt-4o")
    .AsAIAgent(
        name: "VisionAgent",
        instructions: "You are a helpful agent that can analyze images");

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.

Console.WriteLine(await agent.RunAsync(message));

This will print the agent's analysis of the image to the console.

::: zone-end ::: zone pivot="programming-language-python"

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 agent that is able to analyze images.

import asyncio
from agent_framework.azure import AzureOpenAIChatClient
from azure.identity import AzureCliCredential

agent = AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
    name="VisionAgent",
    instructions="You are a helpful agent that can analyze images"
)

Read the full file on GitHub · 131 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. 1mo ago First seen · 131 lines · 8 tokens per session scan A fa9ecb4ee8cb

Subscribe to this mod's changes

images is an agent published in the GitHub repository managedcode/PrompterOne (45 stars, last pushed 5mo ago), licensed MIT. It adds 8 tokens to every session and 933 once invoked, about $0.0000 per session on Opus 5.5. 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.

Related

Other agents, from other repositories