jev-chat-jarvis-mac
Project / 项目 · In the catalogue / 在目录中查看
What Jev decides here · Jev 在这里做什么决定
Intent routing (意图路由), Content scoring (内容评分)
choice, score: text signal only: the cited file contains their request or answer shape 仅文本信号：引用的文件里出现了它们的请求或回答格式
a person read the call site 有人读过调用点 · · Cited file / 引用的文件: src/judge_jev.py
Summary · 摘要
微信消息意图识别悬浮窗（macOS）：看屏 + 本地小模型判断意图和风险，再按话术生成回复候选。纯只读、不注入微信。
微信消息意图识别悬浮窗（macOS）：看屏加本地小模型判断意图与风险，再生成回复候选。纯只读。机翻
Launches · 发布记录
Not launched yet. 还没有发布过。 Launch it / 发布它 ↗ · How a product launches / 怎样发布一个产品
Makers · Maker
Made this? Confirm or correct its entry / 这是你做的？确认或更正条目 ↗
The same form takes the product's one line and a demo link, in its maker's own words. 同一个表单也可以补上产品的一句话和演示链接，用 Maker 自己的话。
Badge for its README · README 徽章
[](https://kydlikebtc.github.io/awesome-jev/products/jev-chat-jarvis-mac.html)One line for the product's README, linked to this page. The picture says that it is listed; while it is on the launch board, that it is launching; after a week in the top three, its place. It is rebuilt with the site, so the line never needs changing. 放进产品 README 的一行，链接到本页。图片显示已收录；在发布榜上时显示正在发布；进过某周前三后显示名次。它随网站一起重建，这一行不用再改。
Also under this pattern · 同一模式的其他产品
TypeSafe AI n8n node
TypeSafe's own n8n community node. Evaluate asks Jev typed questions about each item and adds the answers; Route sends each item to an output by one answer, with a fallback output for low-confidence choices and an uncertain one between two noul thresholds. AI Agents can use it as a tool.
AutoGPT TypeSafe blocks
Seven production blocks — choice, score, yes/no, ask-many, route, pick-best, filter — with a UTF-8 byte budget, verbatim wire capture and eleven test files.
Airflow LLMBranchOperator with Jev
Turns downstream task ids into a choice option set, with a minimum-confidence gate that routes uncertain runs to a human.
Inbox Zero: seven email decisions
Seven distinct email decisions, each with its own separately chosen threshold, falling back to the normal LLM on any error.
jev-chat-jarvis
An Android reply co-pilot that judges intent, timing and risk from on-screen text, while separate models handle OCR and drafting.