third-party-chat-history-storage

A tutorial for saving an AI agent's conversation history in external storage instead of keeping it only in memory or in the underlying AI service.

In plain words
What is it for?
It explains how to create a custom ChatMessageStore for Microsoft's Agent Framework and connect it to a ChatClientAgent, including an in-memory vector store example.
Why use it?
It lets applications retain chat messages using their own storage approach when the default history handling is not suitable.

Agent for Codex

Install

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.

agentmods
npx agentmods add agents/managedcode/prompterone/third-party-chat-history-storage
Clone the repo
git clone --depth 1 https://github.com/managedcode/PrompterOne

Made for: Codex.

Per session 16 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 4,040 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00016 $0.04040
Opus 5 $0.00008 $0.02020
Sonnet 5 $0.00003 $0.00808
Haiku 4.5 $0.00002 $0.00404

Measured 2d ago against content hash 4d3ac7c10a78, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

third-party-chat-history-storage 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

.codex/skills/dotnet-microsoft-agent-framework/references/official-docs/tutorials/agents/third-party-chat-history-storage.md · 464 lines

How it starts

The opening of the file, as written. The whole thing — 464 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Storing Chat History in 3rd Party Storage

::: zone pivot="programming-language-csharp"

This tutorial shows how to store agent chat history in external storage by implementing a custom ChatMessageStore and using it with a ChatClientAgent.

By default, when using ChatClientAgent, chat history is stored either in memory in the AgentThread object or the underlying inference service, if the service supports it.

Where services do not require chat history to be stored in the service, it is possible to provide a custom store for persisting chat history instead of relying on the default in-memory behavior.

Prerequisites

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

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

In addition, you'll use the in-memory vector store to store chat messages.

dotnet add package Microsoft.SemanticKernel.Connectors.InMemory --prerelease

Create a custom ChatMessage Store

To create a custom ChatMessageStore, you need to implement the abstract ChatMessageStore class and provide implementations for the required methods.

Message storage and retrieval methods

The most important methods to implement are:

  • InvokingAsync - called at the start of agent invocation to retrieve messages from the store that should be provided as context.
  • InvokedAsync - called at the end of agent invocation to add new messages to the store.

InvokingAsync should return the messages in ascending chronological order (oldest first). All messages returned by it will be used by the ChatClientAgent when making calls to the underlying xref:Microsoft.Extensions.AI.IChatClient. It's therefore important that this method considers the limits of the underlying model, and only returns as many messages as can be handled by the model.

Read the full file on GitHub · 464 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. 2d ago First seen · 464 lines · 16 tokens per session scan A 4d3ac7c10a78

Subscribe to this mod's changes

third-party-chat-history-storage is an agent published in the GitHub repository managedcode/PrompterOne (42 stars, last pushed 3mo ago), licensed MIT. It adds 16 tokens to every session and 4,040 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.