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CommunityTools & Integrations73 starsVerified 2026-09-22

jev-lint

An ast-grep semantic linter where each rule is one natural-language question judged by Jev: 98 rules flag name/body drift, stale comments, weak tests, quiet failures, and commits whose diffs contradict their messages.

Open github.commizchi/jev-lint
Category
Tools & Integrations
Published by
Community
Author
mizchi
Added
2026-09-22
Tagscommunitytypescriptclicoding-agentlint

Highlights

  • Forty-seven questions ship, most asked in several languages, for 98 rules total, each with a cutoff and a score on its own fixtures.
  • Six findings over two example files cost a tenth of a cent; costs for larger runs are measured in docs/cost.md rather than extrapolated.
  • The key is read only from TYPESAFE_API_KEY or TYPESAFEAI_API_KEY in the environment, never from the config file.
  • jev-lint review judges only lines a diff touched; jev-lint commits judges each message against its diff and the repository's own AGENTS.md or CLAUDE.md.
  • The README says it is not for what compilers, type checkers, or ESLint already decide, and notes it is distinct from huntedman/JevLint.

Quickstart

bash
export TYPESAFE_API_KEY=YOUR_API_KEY
npx -y jev-lint check examples
npx jev-lint init
npx jev-lint check src --dry-run

Watch out

MIT-licensed; needs Node 24+ and npx plus a TypeSafe API key for model calls, though --dry-run, rules, replay, and cached CI runs work with no key.

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From the community

Posts from builders shipping with Jev right now.

Follow @typesafeai

Security decisions that fit Jev

Kostas
Kostas
@Kostastsale
·

This made me rethink where AI actually fits into security engineering. For purely engineering work, forget about ChatGPT or Claude. TypeSafe AI just released Jev, and I think it’s going to change how we build AI into security workflows. Instead of asking an LLM to “investigate Show more

TypeSafe AI
TypeSafe AI
@typesafeai

we are officially out of stealth! join the frontier and get access to Jev on our website (link on profile)

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Read 14 replies

A million judged questions

Inferring Jev's internals from 1,000 calls

iwashi / Yoshimasa Iwase
iwashi / Yoshimasa Iwase
@iwashi86
·

Jevの内部アーキテクチャを推測している技術記事(Jev’s Architecture Unmasked)からメモ。 ・本記事はJevのAPIを約1万回の呼び出して、内部構造を推測したもの ・従来の言語モデルを用いた分類やルーティングでは、トークンを1文字ずつ逐次生成するために膨大な無駄な計算コストが発生していた。 Show more

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Read 2 replies

The open System One roundup

小墨同学
小墨同学
@xiaomovps
·

Jev 发布没几天，开源社区已经开始疯狂复刻了🔥 最值得推荐的五个模型： 1、Laya 421M：原生决策模型，支持 Mac 2、Decider-2B：最像 Jev，基于 Qwen3.5 3、NanoJev 0.6B：专门的 Decision Head 4、Reflex：Qwen3.5 + Direct Logits 5、System-One 4B：专门做概率校准 Show more

小墨同学
小墨同学
@xiaomovps

Jev 刚发布没几天，开源社区就出现了同款🔥 Decider-2B模型，是基于 Qwen3.5-2B 做了特殊调整 它和 Jev 模型是一样的 只做选择 评分和判断 不是文本类的 LLM 模型 但两者还是有几个明显区别： 1、模型 Jev：闭源 System One Model Decider：Qwen3.5-2B，约 1.9B 参数，Apache 2.0 开源 2、价格

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Read 6 replies

The launch post

Trading bot, one decision per block