Jev Use

io.github.shitianfang由 GitHub 账号 shitianfang 发布v0.8.0更新于 Oct 24, 2026

Typed yes/no, pick-one and score judgments from Jev in one batched call; typed escalation back.

已验证STDIO仅桌面开发者工具AI 与机器学习

概览

AI 生成的概览

本地 MCP 服务器，把批量的是/否、单选和评分判断交给 Jev，返回带置信度和升级标记的结构化答案。

可以做什么
  • 批量提出结构化问题（check、pick、rate），获得带置信度和升级标记的答案
  • 把无需文字输出的快速决策交给 Jev 判断，而不是让模型逐条生成
  • 对 Jev 无法或不应决定的事项返回带类型的升级原因
  • 通过 PreToolUse 钩子拦截 shell 命令，拒绝危险命令并给出理由
  • 在发送被拦截的操作前剥离其中的凭据
  • 通过命令行完成安装、启动服务和连接诊断
适用场景
适合代理需要大量无需文字输出的小决策时，例如路由选择、通过/失败检查、风险评级、命令把关，希望比每次询问模型更快、更省 token。也可作为库在自有脚本中使用。
运行要求
通过 npx 从 npm 包 jev-use 在本地运行（需要 Node.js）。需在代理运行环境中设置一个服务商密钥：TYPESAFE_API_KEY、OPENROUTER_API_KEY 或 AI_GATEWAY_API_KEY；JEV_BACKEND=mock 可无密钥本地试运行。安装命令会接入 Claude Code、Codex 和 pi。
安装前请注意
除非使用 mock 后端，判断状态会发送给所配置的第三方服务商。命令把关会检查 shell 命令，发送前会剥离凭据，但仍需留意传入的状态内容。安装命令会修改代理的配置文件。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Jev Use，将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only，通过 STDIO。 STDIO 服务会启动本地进程，因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

jev-use

English | 简体中文

The best way for Claude Code, Codex, and pi to work with Jev: hand the tasks that need no text output to Jev — faster steps, fewer tokens, tasks done sooner and better.

It makes the LLM and Jev true collaborators: when content needs to be written, the LLM takes over; when a step just needs a fast decision, Jev executes it.

Demos — real runs, 1× speed

Directions task: Jev clicks, the LLM types — 10 decisions (p50 274 ms) · 4 writes; Jev rejects a wrong route, the LLM rewrites
[OpenStreetMap directions: Jev picks controls in green, the LLM types the locations in blue; a wrong 1809km geocode is rejected by Jev and repaired by the LLM, ending on the real 3.7km walking route]		Context compaction — 200 messages judged in 7 calls, one LLM paragraph replaces the dropped pile; recall 3/3
[A real transcript fills the context window to 94%; Jev tints each message keep or drop, the LLM's summary paragraph replaces the dropped block, the window falls to 44% and three recall checks pass]
Pong: ball speed = decision latency — 86 Jev decisions in 20 s vs 6 (haiku) and 3 (gemini) called the usual way; enum-constrain both and the gap is 3×
[Three Pong lanes replaying a live run at 1x: the Jev ball sweeps the field at ~224ms per decision while the LLM balls crawl]		Gate every shell command — dangerous ones denied in ~230 ms with a reason, zero LLM tokens
[A 24-command dev session gated at 1x: dangerous commands denied at confidence 1.00, benign ones allowed]

Every demo is a rerunnable script in bench/examples/; all numbers, methodology, variance and caveats: bench/RESULTS.md · third-party measurements: docs/evidence.md.

Install

bash
npx -y jev-use install    # wires Claude Code, Codex, and pi — whichever it finds

Set one key in the environment your agent runs in (JEV_BACKEND=mock for a keyless dry run):

ProviderEnv var
TypeSafe directTYPESAFE_API_KEY
OpenRouterOPENROUTER_API_KEY
Vercel AI GatewayAI_GATEWAY_API_KEY

npx -y jev-use doctor checks the wiring. Judged state goes to the provider you configure; JEV_BACKEND=mock stays local. Plugin form with the routing skill and the PreToolUse gate: harness/claude-code · harness/codex.

Use as a library

npm i jev-use — zero runtime dependencies on the judgment path:

js
import { Jev, check, pick, rate } from "jev-use";
const jev = new Jev();
const { answers } = await jev.judge(state, {  next: pick("Next action?", { merge: "all green", rerun: "looks flaky", hold: "needs attention" }),  risk: rate("How risky?", ["routine", "worth a look", "incident"]),  passed: check("Did the run fully succeed?"),});// answers.next → { answer: "merge", confidence: 0.93, confidenceFrom: "reported", escalate: false }

Anything Jev can't or shouldn't decide comes back with escalate: true and a typed reason. Tools, verdict shape, escalation contract, CLI: docs/reference.md.

Small enough to read

FileJob
src/protocol.tsQuestions (check/pick/rate), verdicts, escalation reasons
src/dispatch.tsPre-call routing: what never reaches Jev
src/judge.tsscreen → backend → hand back what is unsure; gate
src/jev.tsThe Jev client over that engine
src/redact.tsCredentials stripped from a gated action before it is sent
src/backends/TypeSafe, OpenRouter, Vercel, mock adapters
src/server.tsThe two MCP tools
src/cli.tsinstall, serve, hook gate, doctor
skills/jev-use/SKILL.mdThe routing rules the agent follows

Development

console
$ npm run typecheck && npm test    # unit tests incl. per-provider wire fixtures$ npm run smoke                    # real MCP client ↔ built CLI over stdio$ node bench/run.mjs               # micro-benchmarks, your key and region

Substantially written with Claude Code (AI-assisted).

MIT © shitianfang

来源：README.md，提交 541c86c

工具

0
SourceWeft 尚未在沙箱中启动过该软件包，因此其工具未知。

版本历史

2
  1. v0.8.0最新Sep 22, 2026
  2. v0.7.1Sep 20, 2026

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