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None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
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 | 99 |
| Forks | 25 |
| Language | Swift |
| Category | AI Tool |
| Quality Score | 55/100 |
| Open Issues | 1 |
| Last Updated | 2026-06-10 |
| Created | 2026-06-09 |
| Est. Tokens | ~17k |
QMPrompter / 乔木提词器 QMPrompter is a small, personal iOS teleprompter app for speaking to camera. It keeps the script on screen, uses the front camera as a live preview background, and can follow your speech so the current line stays near a comfortable reading position. 乔木提词器是一款自用 iOS 提词器。它把文稿显示在摄像头预览之上，适合对着镜头练习表达、录制口播或直播前试讲。当前版本专注于提词和预览，不录制视频。 Status: early self-use version.
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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: