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 Agentchengfeng · Claude Skill · ★ 3.0k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is chengfeng-videocut-skills safe to install? View the security audit →
chengfeng-videocut-skills 给 Codex / Claude Code 用的口播视频剪辑 Skills 包。 这个项目把我的口播视频剪辑流程做成了一组可安装的 Skills:准备口播素材、拆分镜、看预览、导出竖屏成片。 它不是一个通用剪辑软件,也不是一键生成所有类型视频的工具。它聚焦一类很具体的内容:口播教程、产品演示、知识讲解、结果展示。 核心思路是:把视频剪辑从“人在时间线上操作”,变成“Agent 可以读写的工作流”。人只需要看页面、提修改意见、确认结果。 官方来源 本项目由 chengfeng / AI产品自由 原创并维护。 原始仓库: 如果你使用、转载、翻译、二次发布或改造成自己的 Skill,请保留原作者、原始仓库链接、 和 。 一句话安装 默认安装到: 只安装到 Codex: 只安装到 Claude Code: 指定目录: 这个 npm 包只是一个很小的安装器。真正的 Skills 源码在 GitHub,每次安装都会从这里拉取最新版本: 最短使用方式 准备口播素材: 做口播成片: 推荐输入结构 做成片时,把文件放在同一个项目目录: 只要有 和
| Stars | 3,016 |
| Forks | 388 |
| Language | JavaScript |
| Category | Claude Skill |
| License | Apache-2.0 |
| Quality Score | 58.4560199024289/100 |
| Open Issues | 20 |
| Last Updated | 2026-09-20 |
| Created | 2026-01-14 |
| Platforms | claude-code, node |
| Est. Tokens | ~14k |
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chengfeng-videocut-skills is 用 Claude Code Skills 做的视频剪辑 Agent. It is categorized as a Claude Skill with 3.0k GitHub stars.
chengfeng-videocut-skills is primarily written in JavaScript.
You can find installation instructions and usage details in the chengfeng-videocut-skills GitHub repository at github.com/Agentchengfeng/chengfeng-videocut-skills. The project has 3.0k stars and 388 forks, indicating an active community.
chengfeng-videocut-skills is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to chengfeng-videocut-skills on Agent Skills Hub include AI-Research-SKILLs, claude-skills, awesome-claude-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: