Use for all Blender work. Default code-first execution, local QA and bounded Jev diagnostic advice.
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Use when a transcript has to be cut to a fixed size and you must choose which turns go. Jev marks each turn keep, summarize or drop. Measured: it does not make a handoff better.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Jev cannot write a summary. It can mark each turn of a transcript:
It judges a long turn on its first 350 and last 350 characters, redacted, 40 turns per request, and sees no other turn while it does.
This skill used to say a handoff written from Jev's digest "stops losing the one line that mattered". We measured that on seven real sessions and 104 recall questions (scorecard) and it was wrong:
| the writer reads | capsule | recall alone | with one search of the old session |
|---|---|---|---|
| Jev's digest | 400 words | 37.5% | 68.3% |
| the plain last 24,000 characters | 400 words | 48.1% | 68.3% |
| the whole dialogue | 1,200 words | 58.7% | 75.0% |
| nothing: no handoff at all | 56.7% |
Jev's marks did beat the same marks handed out by recency (11 questions to 4), so the judgement is real. The digest built around it clips every other turn to 400 characters, and that cost more than the judgement earned. Nous Research found the same shape with a different Jev design (hermes-agent PR 116246).
So, for a handoff:
session_search(query="..."), then session_search(session_id=..., around_message_id=...). Passing query together with session_id ignores the query.The hermes-handoff plugin does all four. HANDOFF_JEV=1 puts the Jev pre-pass back if you want to compare on your own sessions with evals/compaction/run_eval.py.
When the size is fixed and something has to go: a small local writer, a context you cannot grow, a digest for a person to skim. There, choosing turns with Jev beat choosing them by recency.
Get the transcript as a list of {role, content} messages. On Hermes: hermes sessions export --session-id <id> --format jsonl -.
Select:
Hermes: call jev_compact_select with messages.
Anywhere else:
jev compact-select --digest < transcript.json # {"messages":[...]} or a bare list
Write from digest. [KEEP VERBATIM] lines go in unchanged. [background] lines are clipped already; treat them as context, not as the record.
The digest is cut to its last 24,000 characters by default, oldest first, keep lines included. Pass a larger limit if early keep lines matter.
keep_last); system messages are always kept.summarize. That is a worse input than the plain transcript, so on status: "fail_open" use the plain transcript instead.status: "partial" means some batches answered and some did not; the ids in unjudged sat at the summarize default with nobody judging them. Treat it like fail_open unless unjudged is short and you can see it does not cover the turns you care about. It used to report ok in this case, so one good batch hid every failed one.should_compact is arithmetic, not a model call: compact at 60% of the window, urgently at 85%. Do not ask a model whether the window is full.
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Use for all Blender work. Default code-first execution, local QA and bounded Jev diagnostic advice.
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Use when driving a web page in a browser — clicking, typing, navigating, logged-in or JS-rendered pages. Jev picks each step from the elements observed, under a host allowlist and a step budget.
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Use when driving a desktop GUI through a computer-use driver — windows, menus, native apps, OS dialogs. You build a table of safe actions; Jev picks the next one in about 0.4 seconds.
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Use when a task is already judged hard — pick which paid frontier seat takes it, then keep Jev watching the delegated run so it interrupts you only when the run needs a decision.
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Use on a mailbox export to sort mail into needs reply, updates, promotional, sales and spam — which messages are addressed to the person at all. For a support queue use jev triage.
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Use on passages a search just returned (memory, vault, session history, wiki, web) before reading them in. Jev ranks them, drops the irrelevant, and flags prompt injection hidden in the text.
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