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 mcncarl · Agent Tool · ★ 1.7k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is jianying-headless safe to install? View the security audit →
Jianying Headless 面向剪映专业版 macOS 的本地自动化工具。通过结构化剪辑计划生成可编辑草稿， 在独立副本中修改多轨工程，并调用本机剪映引擎导出 MP4。 主要适配版本：11.5.0 · 兼容版本：11.4.2 首次使用请从 从零生成第一个剪映草稿 开始。 教程包含安装前提、环境检查、拖入自己的视频、首页登记、保存重开和常见报错处理。 11.5.0 仍需匹配具体安装身份与工具链，尚不保证任意电脑安装即用。 项目适用于 AI 视频工作流的工程交接、批量草稿生成和 Agent 辅助剪辑。 提供 Python 命令行入口及配套 Agent Skill。它不是剪映官方 SDK，运行时需要安装匹配版本的剪映。 核心功能 核心流程为：素材与剪辑计划 → 可编辑剪映草稿 → 原生引擎导出。 剪映中后续手工修改的内容不会自动同步回原计划或旧导出快照。 Hypit 协作案例 一个约 50.23 秒的 IG 滚动动画教程展示了从 Hypit 到剪映的工程交接。 转换使用原工程的独立画面、配音、图片和文字时间安排，而不是仅导入一条最终成片。 该案例已在剪映 11.5.0 完成构建、打开播放、保存、完全退出、冷重开和结构回读， 并通过原生导出的 1507 / 1507 帧检查与完整解码检查。 画面对照 两组图片均取自真实案例的 1、8、17、28、37、48 秒。展示的是可编辑工程交接， 不是视觉无损转换：特殊字体、逐词颜色动画、部分裁切与阴影未原样保留， 第 37 秒的补充画面也存在差异。完整主观视听验收尚未完成。 详见 Hypit 协作案例 和 媒体说明。 当前转换是单向、按项目实现；不提供任意 Hypit 工程的一键无损转换或双向同步。 运行环境 Apple Silicon Mac，macOS 26.0+
| Stars | 1,686 |
| Forks | 721 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 57.5233567832512/100 |
| Open Issues | 6 |
| Last Updated | 2026-09-20 |
| Created | 2026-09-15 |
| Platforms | python |
| Est. Tokens | ~14k |
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jianying-headless is Private source preview: native Jianying drafts, isolated editing/export, and standalone Agent Skill.. It is categorized as a Agent Tool with 1.7k GitHub stars.
jianying-headless is primarily written in Python.
You can find installation instructions and usage details in the jianying-headless GitHub repository at github.com/mcncarl/jianying-headless. The project has 1.7k stars and 721 forks, indicating an active community.
The top alternatives to jianying-headless on Agent Skills Hub include notebooklm-skill, agent-skills, excalidraw-diagram-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: