found the perfect use case for @typesafeai Jev: instant compaction in 2026, why is compaction still a summarization prompt? Jev can make it instant by scoring every tool call and dropping what’s irrelevant
State
How to shape what Jev evaluates: a string, a named object, or an array of messages. Every question in a request sees the same state and is evaluated independently.
- Category
- Practices & Patterns
- Published by
- TypeSafe AI
- Author
- —
- Added
- 2026-09-20
Highlights
- A string is one message or passage; an object adds named fields; an array models a message sequence.
- Objects are recommended for most requests so each part of the state has a descriptive name.
- One request pairs one state with one or more questions, mixing Choice, Score, and Noul freely.
Quickstart
{
"ticket": {
"subject": "Duplicate charge",
"messages": [
{"from": "customer", "text": "I was charged twice for order A-104. Please refund the duplicate."},
{"from": "support", "text": "We are checking the charges."}
]
}
}Watch out
Jev accepts text only, and packing in large amounts of unrelated detail causes context rot, so trim state to what the question needs.
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Instant compaction with Jev
A Claude session from 1M to 86K tokens
This is actually insane. This uses @typesafeai Jev model, as a plugin in Claude to review all the un-nesseasary tool calls, and it takes 1s to run! Like, literally, 1 second to take my Claude session from nearly 1M to ... 86K tokens! 😮 Ask your claude to install it and be Show more
found the perfect use case for @typesafeai Jev: instant compaction in 2026, why is compaction still a summarization prompt? Jev can make it instant by scoring every tool call and dropping what’s irrelevant
