Tutorial

Session Pruning and Compaction in OpenClaw: Cost and Context Playbook

February 21, 20262 min readUpdated September 11, 2026By OpenClawBlog Team

Pruning and compaction trade context length for a smaller prompt. That can lower latency or provider cost, but it can also remove the exact instruction, file path, or approval detail that explains a later action. Choose the boundary from the workflow, not from a fixed token target.

What to keep

  • Keep the current task, constraints, and expected output.
  • Keep tool results that prove what changed or failed.
  • Keep a short pointer to older context instead of copying an entire transcript.

A support handoff may need more history than a short coding task. Review both paths with synthetic data before changing defaults on a shared Gateway.

openclaw gateway status
openclaw doctor

Measure the trade-off

  1. Run the same task with the current session policy.
  2. Record response quality, latency, provider usage, and the details a reviewer can still see.
  3. Change one threshold at a time.
  4. Repeat the test after an update because session behavior can change between releases.

The session pruning reference, session concepts, and token-use notes are the current sources for implementation details.

Reference Trail

Sources and further reading

  1. session pruning referencedocs.openclaw.ai
  2. session conceptsdocs.openclaw.ai
  3. token-use notesdocs.openclaw.ai
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