Session pruning trims old tool results from the context before each LLM
call. It reduces context bloat from accumulated tool outputs (exec results, file
reads, search results) without rewriting normal conversation text.
Pruning is in-memory only — it does not modify the on-disk session transcript.
Your full history is always preserved.
Why it matters
Long sessions accumulate tool output that inflates the context window. This
increases cost and can force compaction sooner than
necessary.
Pruning is especially valuable for Anthropic prompt caching. After the cache
TTL expires, the next request re-caches the full prompt. Pruning reduces the
cache-write size, directly lowering cost.
How it works
- Wait for the cache TTL to expire (default 5 minutes).
- Find old tool results for normal pruning (conversation text is left alone).
- Soft-trim oversized results — keep the head and tail, insert
....
- Hard-clear the rest — replace with a placeholder.
- Reset the TTL so follow-up requests reuse the fresh cache.
Legacy image cleanup
OpenClaw also builds a separate idempotent replay view for sessions that
persist raw image blocks or prompt-hydration media markers in history.
- It preserves the 3 most recent completed turns byte-for-byte so prompt
cache prefixes for recent follow-ups stay stable.
- In the replay view, older already-processed image blocks from
user or
toolResult history can be replaced with
[image data removed - already processed by model].
- Older textual media references such as
[media attached: ...],
[Image: source: ...], and media://inbound/... can be replaced with
[media reference removed - already processed by model]. Current-turn
attachment markers stay intact so vision models can still hydrate fresh
images.
- The raw session transcript is not rewritten, so history viewers can still
render the original message entries and their images.
- This is separate from normal cache-TTL pruning. It exists to stop repeated
image payloads or stale media refs from busting prompt caches on later turns.
Smart defaults
OpenClaw auto-enables pruning for Anthropic profiles:
| Profile type | Pruning enabled | Heartbeat |
|---|
| Anthropic OAuth/token auth (including Claude CLI reuse) | Yes | 1 hour |
| API key | Yes | 30 min |
If you set explicit values, OpenClaw does not override them.
Enable or disable
Pruning is off by default for non-Anthropic providers. To enable:
{
agents: {
defaults: {
contextPruning: { mode: "cache-ttl", ttl: "5m" },
},
},
}
To disable: set mode: "off".
Pruning vs compaction
| Pruning | Compaction |
|---|
| What | Trims tool results | Summarizes conversation |
| Saved? | No (per-request) | Yes (in transcript) |
| Scope | Tool results only | Entire conversation |
They complement each other — pruning keeps tool output lean between
compaction cycles.
Further reading