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 →
by hahadu4520 · Codex Skill · ★ 6
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is newcut-video-clipping-skill safe to install? View the security audit →
Open-source Codex skill for semantic Chinese video clipping with hooks, captions, cleanup, and FFmpeg rendering
| Stars | 6 |
| Forks | 0 |
| Language | JavaScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 61.8910902030585/100 |
| Last Updated | 2026-07-12 |
| Created | 2026-07-12 |
| Platforms | cli, codex, node |
| Est. Tokens | ~13k |
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newcut-video-clipping-skill is Open-source Codex skill for semantic Chinese video clipping with hooks, captions, cleanup, and FFmpeg rendering. It is categorized as a Codex Skill with 6 GitHub stars.
newcut-video-clipping-skill is primarily written in JavaScript. It covers topics such as ai-video, asr, codex-skill.
You can find installation instructions and usage details in the newcut-video-clipping-skill GitHub repository at github.com/hahadu4520/newcut-video-clipping-skill. The project has 6 stars and 0 forks, indicating an active community.
newcut-video-clipping-skill is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to newcut-video-clipping-skill on Agent Skills Hub include skills, HappyHorse-1.0-API, Ultimate-AI-Media-Generator-Skill. 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: