# AppitStudio/awesome-jev

> A curated directory of resources and runnable examples for Jev, TypeSafe AI's System One model that returns typed choices, scores, and probabilities from state and questions. Aimed at developers who want to learn Jev and find ready-made apps and patterns.

- Magnitude: 1.5 out of 10 — Steady
- Stars: 83 total · +0 stars today, ≈ 2 by evening
- Star trust: star growth looks organic
- Category: AI agents · Language: Python · Created: 2026-09-18 · Last push: 2026-09-24
- GitHub: https://github.com/AppitStudio/awesome-jev · Page: https://gitnova.dev/en/r/AppitStudio/awesome-jev

## Useful for

- Run an offline example workflow with synthetic responses without an API key
- Pick a decision pattern (Choice, Score, Noul) for your task
- Install the agent skill and have a coding agent scaffold a starter for your stack

## Why it’s here

- 0 stars so far today, about 2 expected by the end of the day.
- The repository is 6 days old and already has 83 stars. With less than two weeks of history, there's no usual pace to compare the spike against yet.
- Top new repositories this week: #199.
- Recent forks include notable developers: @MaTriXy (218 followers), @valentynkit (214 followers).

## Star trust

Star growth looks organic.

Star-trust labels are heuristics based on the repository’s behavior, not a check of every stargazer.

## Numbers

- Forks: 14
- Issues and pull requests: 441
- Watchers: 0
- Average over the last week: 12 per day
- Usual pace: too little history (under two weeks)
- Stars in the last hour (measured): 0

## Stars per day, last 12 days (oldest → newest, today is partial)

2026-09-13 … 2026-09-24: 0, 0, 0, 0, 0, 1, 54, 10, 9, 6, 3, 0

## Spotted in now

- Top new repositories this week: #199

## Similar by description

1. **AnotiaWang/awesome-jev** — 3.1 · Early signal · Learning & lists · +0 stars today, ≈ 21 by evening
   A curated list of applications, libraries, and resources for Jev, TypeSafe's System One model that evaluates typed questions against a state and returns structured answers with probabilities.
   Full card: https://gitnova.dev/en/r/AnotiaWang/awesome-jev.md
2. **hellogumbo/awesome-jev** — 3.3 · Early signal · Learning & lists · JavaScript · +0 stars today, ≈ 17 by evening
   A directory of projects built on Jev, TypeSafe AI's System One model that takes a state plus typed questions and returns answers with calibrated probabilities. Includes SDKs, integrations, demos, and articles.
   Full card: https://gitnova.dev/en/r/hellogumbo/awesome-jev.md
3. **kraayenjon/awesome-jev** — 2.5 · Early signal · Learning & lists · +0 stars today, ≈ 9 by evening
   A curated list of resources for Jev, TypeSafe AI's System One model that returns typed decisions (Choice, Score, Noul) with calibrated probabilities instead of generated text. Aimed at developers integrating Jev into code.
   Full card: https://gitnova.dev/en/r/kraayenjon/awesome-jev.md
4. **yibie/awesome-jev** — 5.0 · Peaking · Learning & lists · Python · +0 stars today, ≈ 112 by evening
   A curated list of public projects, integrations, and discussions built on Jev — TypeSafe AI's System One model for typed decisions (choice, score, boolean with confidence).
   Full card: https://gitnova.dev/en/r/yibie/awesome-jev.md
5. **valentynkit/awesome-jev-typesafe** — 1.3 · Cooling · Learning & lists · JavaScript · +0 stars today, ≈ 2 by evening
   A curated list of projects and resources around TypeSafe's Jev, a model that takes state and returns typed answers (probabilities, choices, scale positions) instead of text.
   Full card: https://gitnova.dev/en/r/valentynkit/awesome-jev-typesafe.md

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Magnitude (0–10) measures how fast and how unusually interest in a repository is growing right now. It is not a quality score.
Days are UTC. “So far today” is a fact; “expected by the end of the day” is a forecast.
Summaries and use cases are written by an LLM (DeepSeek V4.1 Flash) from the README and may be inaccurate: verify specific claims (benchmarks, speed, hardware) in the repository itself.
Data as of 2026-09-24 03:33 UTC, updated every 30 minutes.