Session Pruning

Session Pruning

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 touching your conversation messages.

Info

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

1. Wait for the cache TTL to expire (default 5 minutes).
2. Find old tool results (user and assistant messages are never touched).
3. Soft-trim oversized results — keep the head and tail, insert ....
4. Hard-clear the rest — replace with a placeholder.
5. Reset the TTL so follow-up requests reuse the fresh cache.

Smart defaults

OpenClaw auto-enables pruning for Anthropic profiles:

Profile type	Pruning enabled	Heartbeat
OAuth or setup-token	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

• Compaction — summarization-based context reduction
• Gateway Configuration — all pruning config knobs (contextPruning.*)