jev-judgment-designlisted
Install: claude install-skill shimo4228/claude-harness
# Jev judgment design
Jev answers closed questions with probabilities and does not write prose. Moving an LLM pipeline's judgments to Jev makes them cheap
and parallel, but Jev answers only within the state it is handed. This skill owns the design of that state and of the side that
decides accept/reject from the answers. The general design guidance for Jev (state / instructions / criteria, choosing Choice, Noul,
or Score, no-match, set thresholds on your own data) is canonical in plugin skill `typesafe:typesafe-ai`, so read that
first and read only the judgments layered on top here.
Sources: the implementation in jev-research-pipeline (https://github.com/shimo4228/jev-research-pipeline) and the article
"Moving the research judgments I left to an LLM to Jev, a judgment-only model"
(https://zenn.dev/shimo4228/articles/jev-research-judgment-offload, scheduled for publication 2026-09-25).
## 1. Move only closed judgments
Move to Jev the judgments whose answer can be stated as a yes/no probability, one pick from a set of options, or a point on a graded
scale. Keep work with an open-ended answer shape, such as where to search next or how to write, with the LLM. After the move, watch the
instrument "number of LLM judgments during a run", not "number of questions to Jev" — Jev's question count may grow by as many
judgments as were moved.
## 2. Put what the judgment is made against into state
"Is it relevant" lets through anything that shares vocabulary when the comparison targe