by wx4766 · Agent Tool · ★ 185
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/wx4766/html-to-video.git
git clone https://github.com/wx4766/html-to-video.git ~/.workbuddy/skills/html-to-videoTaken from the project's README on GitHub.
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 | 185 |
| Forks | 14 |
| Language | JavaScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 65/100 |
| Last Updated | 2026-11-07 |
| Created | 2026-10-11 |
| Platforms | cli, node |
| Est. Tokens | ~16k |
html-to-video · 用代码逐帧做视频 把 HTML / Canvas 动画逐帧渲染成 MP4（可配乐、可出 GIF）。 不是 AI 文生视频，而是： 字幕、运镜、转场全在代码里，改一行代码重渲即可。 为什么用它 适合：讲解动画、动态图解、产品演示、数据可视化动画、游戏宣传片。 不适合：实拍感 / 氛围镜头（那个应该走 VideoGen）。 和 Remotion / Motion Canvas 什么关系 同类工具里最常被拿来比的三个，说清楚各自适合什么，省得你上手才发现选错： 一句话选择：要在 React 应用里内嵌视频编辑器、或大规模云端渲染 → Remotion 更合适； 要手工一帧帧精修分镜 → Motion Canvas 更合适； 只想把一屏现成的 HTML 变成 mp4，不想为此建个工程 → 用这个。 尤其是「AI
Looking for a html-to-video alternative? If you're comparing html-to-video with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
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把一个主题做成有配音、字幕、封面的讲解分析类视频 —— 全本地、用 HTML 写画面，稳定音画同步。 面向 AI 编程智能体的确定性 HTML → MP4 渲染流水线。
DeepSeek Harness 本地视频制作与设计插件：多轨剪辑、模板与设计体系、原生预览画布和真实文件导出
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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: