No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is qiaomu-tab safe to install? View the security audit →
乔木Tab / Qiaomu Tab 把 Chrome 新标签页换成一个安静、漂亮、本地优先的个人工作台。 Chrome 的默认新标签页太像一块广告牌，书签栏又总是越堆越乱。乔木Tab 想做的是另一种入口：打开浏览器时，先看到时间、今天要做的事、常用网站、最近访问、便签、天气和音乐，而不是再被一堆噪音拖走注意力。 它不是一个需要注册登录的云端效率系统。核心数据优先留在本机，界面克制，中文体验友好，适合把浏览器首页整理成一个每天都会用的轻量工作台。 为什么想装它 第一眼是安静的。 大字号时间、细腻壁纸和浅淡卡片，让新标签页像一张干净桌面，而不是入口堆栈。 常用入口更顺手。 搜索框可以搜网站、历史和收藏，也可以按需切换本地搜索、网页搜索和 AI 入口。 浏览记录不是流水账。 最近访问会自动按常见使用场景整理，找回刚看过的页面更快。 待办、便签、番茄钟放在刚好够用的位置。 不抢戏，但你需要的时候就在首页。 本地优先。 自定义网站、待办、便签、设置和缓存保存在浏览器本地；不要求账号，不把你的工作台变成另一个 SaaS。 中文用户不用将就。 中文界面、中文天气、微信文章标题优化、常见中文网站图标都做了适配。 一屏里有什么 内置一个小型
| Stars | 52 |
| Forks | 18 |
| Language | JavaScript |
| Category | AI Tool |
| License | MIT |
| Quality Score | 58.8579794984007/100 |
| Open Issues | 1 |
| Last Updated | 2026-06-03 |
| Created | 2026-05-26 |
| Platforms | browser, node |
| Est. Tokens | ~14k |
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qiaomu-tab is A calm, local-first Chrome MV3 new tab dashboard. It is categorized as a AI Tool with 52 GitHub stars.
qiaomu-tab is primarily written in JavaScript.
You can find installation instructions and usage details in the qiaomu-tab GitHub repository at github.com/joeseesun/qiaomu-tab. The project has 52 stars and 18 forks, indicating an active community.
qiaomu-tab is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to qiaomu-tab on Agent Skills Hub include claude-code-voice-skill, maui-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: