Borrowing it
Nothing to install: this file belongs to managedcode/dotPilot. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/managedcode/dotPilot/main/.codex/skills/dotnet-microsoft-agent-framework/references/official-docs/tutorials/agents/run-agent.mdgit clone --depth 1 https://github.com/managedcode/dotPilotWrote 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.
[](https://agentmods.dev/agents/managedcode/dotpilot/run-agent)<a href="https://agentmods.dev/agents/managedcode/dotpilot/run-agent"><img src="https://agentmods.dev/badge/agents/managedcode/dotpilot/run-agent/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.
<a href="https://agentmods.dev/agents/managedcode/dotpilot/run-agent"><img src="https://agentmods.dev/badge/agents/managedcode/dotpilot/run-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00012 | $0.02081 |
| Opus 5.5 | $0.00005 | $0.00832 |
| Sonnet 5.5 | $0.00002 | $0.00416 |
| Haiku 4.5 | $0.00001 | $0.00208 |
Grade A, and why
run-agent 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.
This is a copy
100% identical to run-agent — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 264 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create and run an agent with Agent Framework
::: zone pivot="programming-language-csharp"
This tutorial shows you how to create and run an agent with Agent Framework, based on the Azure OpenAI Chat Completion service.
[!IMPORTANT] Agent Framework supports many different types of agents. This tutorial uses an agent based on a Chat Completion service, but all other agent types are run in the same way. For more information on other agent types and how to construct them, see the Agent Framework user guide.
Prerequisites
Before you begin, ensure you have the following prerequisites:
- .NET 8.0 SDK or later
- Azure OpenAI service endpoint and deployment configured
- Azure CLI installed and authenticated (for Azure credential authentication)
- User has the
Cognitive Services OpenAI UserorCognitive Services OpenAI Contributorroles for the Azure OpenAI resource.
[!NOTE] Microsoft Agent Framework is supported with all actively supported versions of .NET. For the purposes of this sample, we recommend the .NET 8 SDK or a later version.
[!IMPORTANT] This tutorial uses Azure OpenAI for the Chat Completion service, but you can use any inference service that provides a xref:Microsoft.Extensions.AI.IChatClient implementation.
Install NuGet packages
To use Microsoft Agent Framework with Azure OpenAI, you need to install the following NuGet packages:
dotnet add package Azure.AI.OpenAI --prerelease
dotnet add package Azure.Identity
dotnet add package Microsoft.Agents.AI.OpenAI --prerelease
Create the agent
- First, create a client for Azure OpenAI by providing the Azure OpenAI endpoint and using the same login as you used when authenticating with the Azure CLI in the Prerequisites step.
- Then, get a chat client for communicating with the chat completion service, where you also specify the specific model deployment to use. Use one of the deployments that you created in the Prerequisites step.
- Finally, create the agent, providing instructions and a name for the agent.
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.
- 1mo ago First seen · 264 lines · 12 tokens per session scan A 5ba32b7af1a7
run-agent is an agent published in the GitHub repository managedcode/dotPilot (25 stars, last pushed 6mo ago), licensed MIT. It adds 12 tokens to every session and 2,081 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to run-agent, differing in 0 lines, and is treated as a copy.
Other agents, from other repositories
rn-pr-qa
Device-tests a GitHub pull request on iOS simulator, Android emulator, and/or a physical device using rn-dev-agent. Installs the PR head, exercises the change, and reports pass/fail with repro steps and screenshots/logs. PARENT-SESSION-ONLY: requires MCP tools (cdp, device, rnsession) — do NOT spawn via Task tool, run…
design-builder
Use this agent for building production-ready prototypes and implementations from design specs — assembling components into full pages, wiring up interactions, integrating with APIs, setting up project scaffolding, and bridging the gap between design decisions and working software. Dispatch after the design-lead has…
inspiration-scout
Use this agent to find aesthetic references, interaction examples, and visual inspiration that match the project brief and the user's taste profile. Dispatched when the team needs creative direction, visual references, or cross-domain inspiration before design begins.
world-agent
A world-state and turn-management agent for the Kagurajima setting. It sends each turn to the active character agents, combines their results, and closes the turn with the final story.
drift-agent
A cause-and-effect calculator for alternate timelines. When a player changes a past event, it estimates how much the world diverges and whether events are likely to return to their previous path.
services-training-specialist
Technical training and certification with focus on Build customer competence.