memory-pollution-detection

Memory pollution occurs when auto-generated non-durable outputs accumulate in agent memory, cluttering recall and degrading decision quality. You detect it by scanning memory stores for entries that lack durable instructional or factual domain value.

Yes, safe pruning of agent memory uses a targeted cleanup workflow to isolate and validate entries before removal. This prevents the deletion of durable instructions, decisions, or facts while removing only polluted memory rows.

Prevent polluted memory previews from contaminating durable context by applying targeted cleanup to runtime recall and memory stores. This isolates polluted auto-generated learnings before they impact the broader durable context.

The best way to identify non-durable learnings in agent memory is using a lightweight classifier and guided tests. These tools locate and validate polluted memory entries while preserving useful domain knowledge in the memory stores.