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

# Compaction

# Context Window & Compaction

Every model has a **context window** (max tokens it can see). Long-running chats accumulate messages and tool results; once the window is tight, OpenClaw **compacts** older history to stay within limits.

## What compaction is

Compaction **summarizes older conversation** into a compact summary entry and keeps recent messages intact. The summary is stored in the session history, so future requests use:

* The compaction summary
* Recent messages after the compaction point

Compaction **persists** in the session’s JSONL history.

## Configuration

Use the `agents.defaults.compaction` setting in your `openclaw.json` to configure compaction behavior (mode, target tokens, etc.).
Compaction summarization preserves opaque identifiers by default (`identifierPolicy: "strict"`). You can override this with `identifierPolicy: "off"` or provide custom text with `identifierPolicy: "custom"` and `identifierInstructions`.

## Auto-compaction (default on)

When a session nears or exceeds the model’s context window, OpenClaw triggers auto-compaction and may retry the original request using the compacted context.

You’ll see:

* `🧹 Auto-compaction complete` in verbose mode
* `/status` showing `🧹 Compactions: <count>`

Before compaction, OpenClaw can run a **silent memory flush** turn to store
durable notes to disk. See [Memory](/concepts/memory) for details and config.

## Manual compaction

Use `/compact` (optionally with instructions) to force a compaction pass:

```
/compact Focus on decisions and open questions
```

## Context window source

Context window is model-specific. OpenClaw uses the model definition from the configured provider catalog to determine limits.

## Compaction vs pruning

* **Compaction**: summarises and **persists** in JSONL.
* **Session pruning**: trims old **tool results** only, **in-memory**, per request.

See [/concepts/session-pruning](/concepts/session-pruning) for pruning details.

## OpenAI server-side compaction

OpenClaw also supports OpenAI Responses server-side compaction hints for
compatible direct OpenAI models. This is separate from local OpenClaw
compaction and can run alongside it.

* Local compaction: OpenClaw summarizes and persists into session JSONL.
* Server-side compaction: OpenAI compacts context on the provider side when
  `store` + `context_management` are enabled.

See [OpenAI provider](/providers/openai) for model params and overrides.

## Tips

* Use `/compact` when sessions feel stale or context is bloated.
* Large tool outputs are already truncated; pruning can further reduce tool-result buildup.
* If you need a fresh slate, `/new` or `/reset` starts a new session id.