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.
curl -O https://raw.githubusercontent.com/managedcode/PrompterOne/main/.codex/skills/dotnet-microsoft-agent-framework/references/official-docs/tutorials/agents/persisted-conversation.mdgit clone --depth 1 https://github.com/managedcode/PrompterOneWrote 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/prompterone/persisted-conversation)<a href="https://agentmods.dev/agents/managedcode/prompterone/persisted-conversation"><img src="https://agentmods.dev/badge/agents/managedcode/prompterone/persisted-conversation/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/prompterone/persisted-conversation"><img src="https://agentmods.dev/badge/agents/managedcode/prompterone/persisted-conversation.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 | $0.01327 |
| Opus 5.5 | $0.00005 | $0.00531 |
| Sonnet 5.5 | $0.00002 | $0.00265 |
| Haiku 4.5 | $0.00001 | $0.00133 |
Grade A, and why
persisted-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 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- persisted-conversation — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Persisting and Resuming Agent Conversations
::: zone pivot="programming-language-csharp"
This tutorial shows how to persist an agent conversation (AgentThread) to storage and reload it later.
When hosting an agent in a service or even in a client application, you often want to maintain conversation state across multiple requests or sessions. By persisting the AgentThread, you can save the conversation context and reload it later.
Prerequisites
For prerequisites and installing NuGet packages, see the Create and run a simple agent step in this tutorial.
Persisting and resuming the conversation
Create an agent and obtain a new thread that will hold the conversation state.
using System;
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
using OpenAI;
AIAgent agent = new AzureOpenAIClient(
new Uri("https://<myresource>.openai.azure.com"),
new AzureCliCredential())
.GetChatClient("gpt-4o-mini")
.AsAIAgent(instructions: "You are a helpful assistant.", name: "Assistant");
AgentThread thread = await agent.GetNewThreadAsync();
Run the agent, passing in the thread, so that the AgentThread includes this exchange.
// Run the agent and append the exchange to the thread
Console.WriteLine(await agent.RunAsync("Tell me a short pirate joke.", thread));
Call the Serialize method on the thread to serialize it to a JsonElement.
It can then be converted to a string for storage and saved to a database, blob storage, or file.
using System.IO;
using System.Text.Json;
// Serialize the thread state
string serializedJson = thread.Serialize(JsonSerializerOptions.Web).GetRawText();
// Example: save to a local file (replace with DB or blob storage in production)
string filePath = Path.Combine(Path.GetTempPath(), "agent_thread.json");
await File.WriteAllTextAsync(filePath, serializedJson);
Load the persisted JSON from storage and recreate the AgentThread instance from it. The thread must be deserialized using an agent instance. This should be the same agent type that was used to create the original thread. This is because agents might have their own thread types and might construct threads with additional functionality that is specific to that agent type.
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 · 179 lines · 12 tokens per session scan A 98487e5bb054
persisted-conversation is an agent published in the GitHub repository managedcode/PrompterOne (45 stars, last pushed 5mo ago), licensed MIT. It adds 12 tokens to every session and 1,327 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.
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