jev-job-hunter
这是 Kai 公开的项目资料。本站按原始来源展示项目信息，用中文说明适用场景和阅读边界；项目名、源帖与代码保持原样，便于逐项核对。
这条案例记录了什么
浏览器 Agent、Agent 评估
从当前页面允许的候选动作中选择下一步；浏览器工具负责执行。
社区公开项目或作者演示
原始来源：Original showcase by Kai。作者自述，本站未独立复现。
Kai
记录日期：2026-09-18。日期与身份应以原始资料为准。
原始演示视频
视频来自此案例记录的原始媒体；播放内容和作者声明不等于本站复现。
怎样核对这个项目
- 先打开原始来源，确认作者、日期与 Jev 在项目中的具体用途。
- 如果提供仓库，再检查代码、运行要求和许可证；仓库存在不代表本站已经运行成功。
- 对速度、成本、准确率和规模数字，查看原文的任务、环境和计算口径。
- 页面状态与候选动作是否同步。
- 失败、停止与人工接管条件。
- 权限和不可逆操作的独立审批。
- 是否有可观察的正确答案。
原始文字与技术细节
以下内容保留原语言，供核对事实。中文页的场景说明是阅读提示，不是逐句翻译或实测结论。
展开英文项目摘要与原帖
项目摘要
I rebuilt my job crawler with Jev. The task: start at a company's official homepage, find Careers, and identify jobs that match my profile. Before, with an LLM: ~5 minutes. After, with Jev: just over 20 seconds in my test. Every company organizes its website differently. Jev identifies the Careers entry point, chooses which links to follow, recognizes job pages, and scores each role against my profile. This is where Jev makes sense to me: automation that needs lots of small decisions, with faster responses and lower costs than calling an LLM at each step. Packaged it as a skill: jev-job-hunter. Demo below.
来源原文
I rebuilt my job crawler with Jev. The task: start at a company's official homepage, find Careers, and identify jobs that match my profile. Before, with an LLM: ~5 minutes. After, with Jev: just over 20 seconds in my test. Every company organizes its website differently. Jev identifies the Careers entry point, chooses which links to follow, recognizes job pages, and scores each role against my profile. This is where Jev makes sense to me: automation that needs lots of small decisions, with faster responses and lower costs than calling an LLM at each step. Packaged it as a skill: jev-job-hunter. Demo below.
原记录的限制
- Task accuracy is bounded by the precision of the defined candidate choices
- Third-party external dependencies and network latency may affect total workflow duration