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 MartinDelophy · Agent Tool · ★ 844
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ai-video-editor safe to install? View the security audit →
Timeline Studio — Browser AI Video Editor English Русский Timeline Studio is a local-first AI video editor that runs in the browser. It combines a CapCut-style multi-track timeline with browser-side AI voiceovers, automatic captions, vision tools, talking-avatar generation, and deterministic offline export. Open the editor · Watch on YouTube · Hugging Face Space Video demo https://github.com/user-attachments/assets/e8327caa-429e-40ff-a7fe-a59e6cf7a464 AI capabilities Multilingual voiceover: Chinese
| Stars | 844 |
| Forks | 106 |
| Language | JavaScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 66.8744503325676/100 |
| Open Issues | 7 |
| Last Updated | 2026-09-20 |
| Created | 2026-07-09 |
| Platforms | browser, node |
| Est. Tokens | ~15k |
These tools work well together with ai-video-editor for enhanced workflows:
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ai-video-editor is Open-source, local-first video editor where creators and AI agents edit the same real timeline.. It is categorized as a Agent Tool with 844 GitHub stars.
ai-video-editor is primarily written in JavaScript. It covers topics such as agent-skills, ai-music, ai-video-editor.
You can find installation instructions and usage details in the ai-video-editor GitHub repository at github.com/MartinDelophy/ai-video-editor. The project has 844 stars and 106 forks, indicating an active community.
ai-video-editor is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ai-video-editor on Agent Skills Hub include OpenChatCut, MasterSelects, openclip. 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: