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Flagged: sudo usage. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 59 |
| Forks | 8 |
| Language | Python |
| Category | AI Tool |
| License | MIT |
| Quality Score | 57/100 |
| Last Updated | 2026-10-23 |
| Created | 2026-10-05 |
| Platforms | cli, python |
| Est. Tokens | ~16k |
laya-opencv 原名 laya-workbench（Laya 工作台）。 中文 | English 判定模型的本地工作台和一键安装包，支持 Windows 和 Linux，界面有中文和英文两个版本。2.0 起加入视觉检测：用 OpenCV 看图和测量，用判定模型下结论，可以用在农业和质检场景。 Laya 和 TypeSafe 的 Jev 都是判定模型：给它一段素材（state）和几道题，它返回每道题的概率分布，而不是生成文本。这个项目把本地 Laya 的安装、启动和一个网页工作台打包在一起，同一份请求可以发给本地模型，也可以发给远程的 Jev 接口。 判定模型只读文本，看不了图。视觉检测的做法是把两者接成一条流水线： 上图是「只按规则裁决」模式下的钢管质检，图片是程序合成的示例图。 功能 一键安装：自动建虚拟环境，按显卡情况安装 PyTorch 和...
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: