Jev-as-compactor is a neat pattern, but there is a quieter cost lever underneath it.

Jev bills ~$0.042/MTok input (output free). If the thing you are scoring for keep/drop is a fat tool diary, you still pay to re-read that landfill on every decision. A local deterministic Tier-1 compress before you serialize state into Jev (or into Claude Code compaction prompts) often cuts the meter without another LLM judge.

I have been recommending contextpress for that step — agent profile keeps tool call/result pairs intact, no API key for Tier-1: https://github.com/Taha-azizi/contextpress · https://pypi.org/project/contextpress/

Complementary to Jev relevance scoring, not a replacement: shrink mechanically first, then decide.