Awesome Jev usecases, trending daily.

Jev is TypeSafe's System One decision model: typed choices, scores, and calibrated probabilities in 70 to 500 milliseconds, with output tokens free. The ecosystem index passed a thousand projects in under two weeks, and the stars keep compounding. This wiki shows you the ones worth your time, what is moving, and what the independent tests actually found.

Independent. Not affiliated with TypeSafe AI. Updated 30 September 2026. Star counts read live from GitHub on 30 September; the project index is the 24 September directory refresh.

93kGitHub stars, ecosystem wide
1,094projects in the index
70-500 msper decision, per vendor
$0.042per MTok input, outputs free

New this week first seen between 24 and 30 September

The freshest entries that already prove something. Each links to its repository.

new building-with-typesafe-jev

Agent skill for writing Jev programs: typed questions, confidence gates, and when not to reach for it. 121 stars in four days.

new quicksilver

Claude Code skill that hands bulk judgment calls to Jev. Claims 86% fewer Claude tokens across a 12-task benchmark, self-reported.

new OneJev

A multimodal System One decision model, answering typed questions over image input rather than text alone.

new jevpipe

A Unix filter. Pipe anything in, get typed decisions out. The shell-pipeline mental model applied to a decision model.

new awesome-jev-security

Curated list of papers on the security, robustness, and safety of Jev and System One models. The failure-mode literature, gathered in one place.

new zh-decision-bench

First Chinese-language calibration benchmark for Jev-class decision models. Most calibration work is English-only, so the gap matters.

new jev-mail-filter

Gmail filters written in plain English and judged by Jev. The most literal reading of the whole idea, and it works.

new stefafafan/jev

Provider-neutral Unix client for the System One API, written in Go. Another entrant in the crowded-but-tiny Go SDK category.

new graphify-jev

Codebase knowledge graph with Jev-driven semantic navigation and no vector database, per the description.

new anofox-decide

DuckDB extension that evaluates natural-language predicates and answer sets with Jev. The SQL-with-judgment genre, still growing.

Browse by usecase

The full curated list lives on one page, sorted by what you are building.

What Jev is, in one table

One request carries any number of typed questions, evaluated in parallel against the same state. Your code owns the thresholds, the fallbacks, and every side effect.

PrimitiveYou declareIt returnsTypical use
Noul a yes/no statement a probability from 0 to 1 eligibility, membership, health checks
Choice a list of options, up to 255 selected option + probabilities + confidence routing, classification, matching
Score an ordered rubric, 2 to 10 levels weighted score + distribution + confidence severity, relevance, quality grading
Why the shape matters: a chat model returns prose you must parse before code can act. Jev cannot return a value outside your schema, so there is no parsing layer and no invented fields. It can still choose the wrong valid option, which is why every serious deployment measures its thresholds on its own data. Start with the getting started page, then read what the independent tests found.

Last updated 30 September 2026.