Does the list tell me which of these projects are actually trustworthy?

No, and the README does not imply that. It says to check permissions and data handling before running a project and that source review is not a runtime test or a security audit. The one-line summaries record what each project claims to do, with no accuracy comparison, no maintenance signal and no licensing notes, so read it as a map of where to look and check the individual repositories yourself.

Two entries mention running Jev locally. What is actually documented about that?

Only the pointer. The getting-started section sends you to a separate guide for building a first typed classifier, for using Jev in an agent, and for exploring a local alternative, and a second file records setup, privacy and evidence limits for the selections. Those files are not part of the README, so what the local option involves is not described in what was read.

Are the videos and screenshots evidence that these projects work?

No. The README labels that section creator recordings and publisher previews and explicitly not independent benchmarks. One entry is a still rather than a video, another is a screenshot where Jev judges transcripts rather than video pixels, and the computer-use entry is described as real automation that needs desktop permissions, so none of it is a measured result you can rely on.

How current is the list, and does it say anything about dead links?

The captured README says nothing about refresh cadence, link checking or removal policy. It does split some entries into ones with creator context and a longer gallery of videos and attribution kept in separate files, but there is no statement about how often the list is revisited or what happens when a repository disappears, so you would need to check the repo history or ask the maintainer.

Where should I start reading?

Start with the 20-second quick-start in docs/DIRECTORY.md, then build a typed classifier, use Jev in an agent, or explore a local alternative. docs/START_HERE.md and the source notes in docs/REVIEWED.md record setup, privacy, and evidence limits.

Are the demos independent tests?

No. They are creator recordings and publisher previews, not independent benchmarks. Each entry links the original recording or post, and some entries explicitly note what they do not show, such as a screenshot rather than video or text rather than pixels.

CommunityJev Guides & Articles

Awesome Jev — Amal-David

Q: How is this list maintained?

It is a standard Awesome list that links to public sources. The README warns to check permissions and data handling before running any project, since source review is not a runtime test or a security audit.

A curated index of Jev projects grouped by category, with one sentence of intent per repository: demos, official SDKs and skills, browser and desktop automation, agent tooling, and apps and integrations.

See highlights

Open github.com

Stars: 235
Language: Python
License: CC0-1.0
Published by: Community
Author: Amal-David
Last verified: Oct 2026

Amal-David/awesome-jev

User repository on GitHub

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Jev demos, projects, SDKs and skills, with source links and a curated X gallery.

Forks: 20
Last pushed: Updated Oct 2026

Repo stats from the GitHub API, cached Oct 2026.

This is one of several Jev listings for the same project. The canonical entry is Awesome Jev — yibie.

About this project

Jev is TypeSafe's System One model for probability-based yes/no judgments, choices, and scores rather than generated text. Check permissions and data handling before running a project. Source review is not a runtime test or a security audit. Start with the quick-start example, then build a typed classifier, use Jev in an agent, or explore a local alternative. The source notes record setup, privacy, and evidence limits for the selections below.

Quoted from the project's README. Read the full README.

Tagscommunity jevbest

Works forJev for Classification Jev for Tool calling

Used inJev for Software & DevTools

Languages: Python

Highlights

Sections cover demos, SDKs and skills, browser and desktop tools, agent tools, and apps and integrations, each entry naming a repo and what it does.
Lists the official Python and JavaScript SDKs and a request-writing skill next to a Rust client and offline request linters.
States plainly that its demos are creator recordings and publisher previews, not independent benchmarks, and that source review is not a runtime test.
Deeper material sits in docs: one file records setup, privacy and evidence limits per selection, another walks through building a typed classifier.

Watch out

This is an index, not software, and the README says so: source review is not a runtime test or a security audit, and you are told to check permissions and data handling before running any listed project. Each entry is a single sentence, so accuracy comparisons, maintenance state, licensing and dependency versions are all absent. The captured README stops inside the apps and integrations section, so the games, independent models, reading and supporting-driver sections named in the contents were not available to read. Copy reviewed against the repository README on 2026-10-04, not from running it.

Questions about this entry

Short answers drawn from the linked project or page.

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