> ## Documentation Index
> Fetch the complete documentation index at: https://docs.rkat.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Memory And Compaction

> The long-horizon conversation model: context compaction plus semantic recall.

Meerkat handles long-running conversations with two related but distinct systems:

* **context compaction**
* **semantic memory**

Compaction keeps the active session within practical context limits.
Memory gives the agent a way to retrieve discarded context later.

## Why this is a concept

This is not just an implementation detail or optional addon. It shapes how Meerkat thinks about:

* long-lived sessions
* multi-turn work
* what stays in immediate context
* what becomes retrievable context

## Mental model

```text theme={null}
conversation grows
  -> compaction rebuilds active history
  -> discarded content can be indexed
  -> agent recalls via memory_search when needed
```

## What this concept owns

* immediate-context vs retrievable-context distinction
* semantic recall as a tool-driven capability
* the idea that long-horizon work is part of the session model, not external state glued on later

## See also

* [Sessions](/concepts/sessions)
* [Tools](/concepts/tools)
* [Memory guide](/guides/memory)