The guardrail example is the part I'd push on. Using Jev to judge whether a finished tool result is still relevant only works as a guardrail if the state it's scoring is honest, and tool output is exactly the kind of state that isn't always honest. A manipulated or adversarial tool result could carry language engineered to read as "relevant" to whatever schema the guardrail is scoring against, and the "doesn't treat state as hostile" nuance you already flagged for accuracy applies with extra weight here, not just for ordinary task quality. With an LLM judge you at least sometimes get a chain of reasoning you can inspect for something off; with Jev you get a probability and nothing else to look at, so there's less surface to catch the manipulation on. Doesn't undercut the speed/cost case for routing or triage, but I'd want a second, cheap sanity check in front of anything sitting between untrusted output and the rest of an agent loop rather than trusting the score alone.
The guardrail example is the part I'd push on. Using Jev to judge whether a finished tool result is still relevant only works as a guardrail if the state it's scoring is honest, and tool output is exactly the kind of state that isn't always honest. A manipulated or adversarial tool result could carry language engineered to read as "relevant" to whatever schema the guardrail is scoring against, and the "doesn't treat state as hostile" nuance you already flagged for accuracy applies with extra weight here, not just for ordinary task quality. With an LLM judge you at least sometimes get a chain of reasoning you can inspect for something off; with Jev you get a probability and nothing else to look at, so there's less surface to catch the manipulation on. Doesn't undercut the speed/cost case for routing or triage, but I'd want a second, cheap sanity check in front of anything sitting between untrusted output and the rest of an agent loop rather than trusting the score alone.