memory after context compacting
Hi, I’m reaching out with an issue I hope you can help with.
I’m using OpenClaw very intensively, and I’m noticing that context compaction is triggered quite frequently - I’d say around 3 to 4 times per hour. This causes a serious problem for me, as I often lose valuable context during active sessions.
Would it be possible to implement a mechanism where OpenClaw continuously monitors context usage and, once it hits a certain threshold - say 80% - automatically flushes to memory and triggers compaction proactively?
This I think would help preserve context and avoid unnecessary loss during work.
I’d greatly appreciate your support on this.
I’m using OpenClaw very intensively, and I’m noticing that context compaction is triggered quite frequently - I’d say around 3 to 4 times per hour. This causes a serious problem for me, as I often lose valuable context during active sessions.
Would it be possible to implement a mechanism where OpenClaw continuously monitors context usage and, once it hits a certain threshold - say 80% - automatically flushes to memory and triggers compaction proactively?
This I think would help preserve context and avoid unnecessary loss during work.
I’d greatly appreciate your support on this.
The AI that actually does things. Emails, calendar, home automation - all from your favorite chat app. New shell, ready to help. The lobster way.
83,815Members
Resources
Recent Announcements
Similar Threads
Was this page helpful?
