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/prompterone/multi-turn-conversationgit clone --depth 1 https://github.com/managedcode/PrompterOneWhat 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 | $0.00011 | $0.01318 |
| Opus 5 | $0.00005 | $0.00659 |
| Sonnet 5 | $0.00002 | $0.00264 |
| Haiku 4.5 | $0.00001 | $0.00132 |
Grade A, and why
multi-turn-conversation 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 yesterday.
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.
Copies of this mod
2 near-identical copies found in the catalogue:
- multi-turn-conversation — 100% identical, 0 lines differ
- multi-turn-conversation — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Multi-turn conversations with an agent
This tutorial step shows you how to have a multi-turn conversation with an agent, where the agent is built 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
For prerequisites and creating the agent, see the Create and run a simple agent step in this tutorial.
::: zone pivot="programming-language-csharp"
Running the agent with a multi-turn conversation
Agents are stateless and do not maintain any state internally between calls. To have a multi-turn conversation with an agent, you need to create an object to hold the conversation state and pass this object to the agent when running it.
To create the conversation state object, call the GetNewThreadAsync method on the agent instance.
AgentThread thread = await agent.GetNewThreadAsync();
You can then pass this thread object to the RunAsync and RunStreamingAsync methods on the agent instance, along with the user input.
Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.", thread));
Console.WriteLine(await agent.RunAsync("Now add some emojis to the joke and tell it in the voice of a pirate's parrot.", thread));
This will maintain the conversation state between the calls, and the agent will be able to refer to previous input and response messages in the conversation when responding to new input.
[!IMPORTANT] The type of service that is used by the
AIAgentwill determine how conversation history is stored. For example, when using a ChatCompletion service, like in this example, the conversation history is stored in the AgentThread object and sent to the service on each call. When using the Azure AI Agent service on the other hand, the conversation history is stored in the Azure AI Agent service and only a reference to the conversation is sent to the service on each call.
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.
- yesterday First seen · 127 lines · 11 tokens per session scan A 8e20515f4eb5
multi-turn-conversation is an agent published in the GitHub repository managedcode/PrompterOne (42 stars, last pushed 3mo ago), licensed MIT. It adds 11 tokens to every session and 1,318 once invoked, about $0.0001 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.
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