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Jev — stefafafan

Go Unix CLI that pipes state on stdin into one Jev question — noul, choice, or score — across TypeSafe, Cloudflare, and Vercel providers, printing machine-readable JSON and signaling success by exit code.

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13
Language
Go
License
MIT
Published by
Community
Author
stefafafan
Last verified
Oct 2026

stefafafan/jev

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An unofficial, provider-neutral Unix client for Jev from TypeSafe AI. Written in Go.

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1
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 Jev — mayank953.

About this project

An unofficial, provider-neutral Unix client for Jev from TypeSafe AI. Written in Go. Use stefafafan/setup-jev to install a released jev binary on a GitHub Actions runner. For a working CI example, see this repository's pr-risk.yml workflow. It sends a pull request diff to Jev through Cloudflare and applies a corresponding merge-risk label. Set credentials for your favorite provider: Then pipe state into one question:

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

Highlights

  • State always comes from stdin with one question per run: noul for yes/no, choice with repeated --option flags, score with ordered --level flags.
  • Works with TypeSafe, Cloudflare Workers AI, and Vercel AI Gateway via env keys, keeping Jev primitive fields and token usage in JSON output.
  • Built for pipes and CI: stdout holds only the result, diagnostics go to stderr, and jq can gate on thresholds like noul probability.
  • Ships a setup-jev GitHub Action plus a PR-risk workflow that sends a diff through Cloudflare and applies a merge-risk label.

Watch out

Unofficial client; it reports a judgment and leaves thresholds and policy to downstream code. 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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From the Jev guides

Original write-ups on what this entry is for.

Closed weights have not stopped the ecosystem from rebuilding the shape in the open. API-compatible servers, retrained heads on small models, and inference-time tricks that skip generation entirely.
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