Sniff Test
prose linter that asks Jev ten `Boolean` questions per paragraph (stacked hedges, restating closers, not-X-but-Y turns, naked cost figures) at a 0.7 threshold; CLI, pre-commit hook, GitHub Action and Claude Code skill; measured 182 ms median and 1 of 54 clean paragraphs flagged against 37 for Haiku 4.5.
它做什么判断
CHOICE
Picks one option from a fixed set
SCORE
Rates against ordered levels
NOUL
Answers a yes / no question
Inferred from this project's own one-line summary in the community list — it reads as a SCORE + NOUL decision. Read the source to confirm.
SCORE 调用长什么样
这是该提问类型的通用骨架,不是这个项目的真实代码。
from typesafe import TypeSafe
ts = TypeSafe()
result = ts.evaluate(
state=candidate,
questions={
"relevance": {
"type": "score",
"levels": ["low", "medium", "high"],
"instructions": "How relevant is this to the query?",
}
},
)
if result["relevance"] >= 0.7:
keep(candidate)更多校验与防护栏项目
jev-reviewstaged code-review workflow and local dashboard where Jev gates each review stage before a change advances.is-maliciousasks Jev `Noul` checks about source and build files, escalates suspicious chunks for a second pass, and returns implicated files and lines before execution.pi-jevadds a measured tool-call gate to the Pi coding agent so risky calls are checked by Jev before execution.OpenWorkwires Jev into its eval testkit as a verification judge so agent-produced work is gated by typed verdicts rather than a text model.