Positioning building-with-typesafe-jev is an unofficial skill for coding agents, published by aaddrick. Its premise is that a Jev answer is only as good as the question fed to the model, so the skill's core job is teaching an agent to design the questions it asks deliberately.
What it does The teaching covers three levers: choosing among the question types, applying a set of 11 design rules, and setting thresholds. Alongside the teaching, the package bundles three kinds of material: an API reference; the official four usage patterns together with the 18 thresholds the cookbook lists; and a library of 150+ precedents grouped by "implementation shape." On receiving a task, an agent can look up a worked example close to it in the precedent library, then adjust what it finds against the rules and thresholds before writing the final question.
Characteristics The skill ships with its own evaluation, which reports that average scores rise from 0.65 to 0.96 when the skill is installed. That figure is self-reported: it was measured with the author's own harness and has not been independently verified by others. The project is a community one with no affiliation to TypeSafe AI.
When to use It suits teams that want a coding agent to approach question design — choosing types, applying rules, setting thresholds — in a systematic way before it calls Jev. Its rules and thresholds are one author-assembled opinion rather than an official standard, so they should be reviewed before being adopted wholesale. Treat the 0.65-to-0.96 gain as the author's own measurement, and cite it as self-reported wherever it appears.