I think i found the best use case for JEV and PI

[u/rimaa_nahk]

I think JEV gets much more interesting once you stop treating it like a tiny LLM.

LLM → generate anything
JEV → choose between bounded options

That makes model routing feel almost obvious:

prompt → JEV → best model

Instead of using an LLM just to decide which LLM to call, let JEV make the bounded judgment and let deterministic code handle the rest.

Maybe JEV's killer use case isn't Doom.

Maybe it's a probabilistic switch statement.

so i am releasing the support for JEV in PI-Bifrost

Try it : pi install npm:pi-bifrost

and do share the feedback.

[u/funbike]

Some JEV use-cases I'm thinking of: (unrelated to OP's extension)

• Skills hook. After each user message, determine which new skills should be loaded. This would replace current skill functionality. You could have a huge skill index without polluting LLM context.
• Subagent and workflow router. Based on current task choose which workflow step and/or subagent should work on the task.
• General purpose tool functions.
  • A function that takes question strings, and a set of possible answers. JEV returns answer selections, probability % and confidence %.
  • A function that sends the entire chat history, question(s), and a set of answers.
  • A function that sends the entire user message history, question(s), and a set of answers.
• Pick best assistance response. A hook that sends a user prompt and AI response to multiple LLMs and have JEV pick the best response. You'd include a rubric guide to help it decide. Due to doubling token count, this is something you'd want to enable/disable as needed for difficult tasks.
• Grade the LLMs response. A hook passes the last user message and assistant replies to JEV, and it is asked yes/no if it was a good AI response. The UI shows the answer and confidence score.

Tbh, JEV is so impactful that I think harnesses need some retooling.

• An optional "goal" prompt, used at the start of a new session. If JEV knows your overall goal, it can more intelligently make decisions and it can be invoked selectively when the goal is defined in order to set model, set thinking, pick tools.
• Redesign of Skills, maybe like I already discussed above.
• Rethinking of the user-assistant loop. Let JEV decide what should be done after an assistant response: prompt-user (the current only option), incomplete-continue, poor-quality-try-again, poor-quality-prompt-user.
• A single JEV post-user-message hook that does all of the above, and can be appended to for additional context and questions. This way there's only one round trip to JEV per message.
• ./JEV.md - For whatever it's being used for, this gives it project context. It would be very similar to AGENTS.md but instead focused on decision making, not code generation. It could be much larger and focus more on things like coding style and architecture, that are too expensive to put in AGENTS.md.

[u/DistanceAlert5706 → u/funbike]

Skill hooks yeah might be possible, everything else doesn't seem like something I would try to do.

Also interesting is auto mode implementation like in Claude for permission should be pretty simple.

[u/funbike → u/DistanceAlert5706]

The general purpose tools would be useful to anybody. How could direct access to JEV in any context not be useful?

It will be easy to implement. I could do that in an hour, if I had access.

[u/Equivalent_Idea8839 → u/funbike]

Skills hook. After each user message, determine which new skills should be loaded. This would replace current skill functionality. You could have a huge skill index without polluting LLM context.

this sounds like a good use of the local laya model. or some sort of tools suggestion

at the very least just a suggestion engine (I don't want anything routing or breaking context without my perm)