you can also use Jev to cut costs and token usage!

Used Jev to compact shell and large file output before it reaches the LLM, cutting token usage and cost across the rest of the conversation.
The original post
you can also use Jev to cut costs and token usage! make your agents more efficient by compacting shell and large file output before it reaches the LLM passing only necessary tokens to the model and carrying fewer tokens through the rest of the conversation
Engagement when collected
Numbers are a snapshot taken from X when the case was added to the library (schema v1, collected 2026-09-19); they will not match today.
Where this case fits
Filed under agents & workflows. In the pattern Jev is built for, the model answers a bounded question per step — and ordinary code acts on the answer, because the answer is already a value rather than a paragraph. Other posts in the same family are on the agents & workflows page.
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Last updated: 2026-09-22 · sources & corrections · every card links to its author's original post