openclaw-openclaw/docs/concepts/session-pruning.md

summary, title, read_when

summary	title	read_when
Trimming old tool results to keep context lean and caching efficient	Session pruning	You want to reduce context growth from tool outputs You want to understand Anthropic prompt cache optimization

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

Pruning runs in cache-ttl mode, gated on both a time check and a context-size check:

1. Wait for the cache TTL to expire (default 5 minutes when set manually; see Smart defaults for the Anthropic auto-default). Before the TTL elapses, pruning is skipped entirely to preserve prompt-cache reuse for nearby turns.
2. Once the TTL has elapsed, estimate total context size against the model's context window. If the ratio is below softTrimRatio (default 0.3), skip pruning and keep the TTL clock running.
3. Soft-trim oversized tool results above the ratio: keep the head and tail (default 1500 chars each, capped at 4000 chars combined), insert ... in between.
4. If the ratio is still at or above hardClearRatio (default 0.5) and at least minPrunableToolChars (default 50,000) of prunable tool content remains, hard-clear those results: replace their content with a placeholder (default [Old tool result content cleared]).
5. Reset the TTL clock only when pruning actually changed the context, so follow-up requests reuse the fresh cache.

Two safety rules apply regardless of thresholds: the most recent keepLastAssistants assistant turns (default 3) are never pruned, and nothing before the session's first user message is ever pruned (protects bootstrap reads like SOUL.md/USER.md).

Only toolResult messages are eligible; normal conversation text is left alone. Use agents.defaults.contextPruning.tools.{allow,deny} to scope which tool names are prunable.

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. This count includes all completed turns, not just image-bearing ones, so text-only turns consume the window too.
• In the replay view, older already-processed image blocks from user or toolResult history are replaced with [image data removed - already processed by model].
• Older textual media references such as [media attached: ...], [Image: source: ...], and media://inbound/... are 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 above. It exists to stop repeated image payloads or stale media refs from busting prompt caches on later turns.

Smart defaults

The bundled Anthropic plugin auto-configures pruning and heartbeat cadence the first time it resolves an Anthropic (or Claude CLI) auth profile, but only for fields you have not already set explicitly:

Auth mode	contextPruning.mode	contextPruning.ttl	heartbeat.every
OAuth/token (including Claude CLI reuse)	cache-ttl	1h	1h
API key	cache-ttl	1h	30m

If you set agents.defaults.contextPruning.mode or agents.defaults.heartbeat.every yourself, OpenClaw does not override them. This auto-default only fires for Anthropic-family auth; other providers get pruning off unless you configure it.

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.*)

Related

• Session management
• Session tools
• Context engine