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 renezander030 · Agent Tool · ★ 861
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is capcut-cli safe to install? View the security audit →
capcut-cli English | 中文 Create and edit real CapCut / JianYing projects from the terminal — or any LLM agent. Open the result in CapCut with every track still editable. capcut-cli works directly on the local draft store: JSON in, JSON out, with no upload, API, MCP server, or HTTP daemon. Also from the maintainer: 500 Years Frozen in Time: The Inca Children Mystery, a 14:49 documentary from Bronze Age Banter. → → ▶ Captioned output example (60 seconds) https://github.com/user-attachments/assets/4e6ee99c-0745-
| Stars | 861 |
| Forks | 90 |
| Language | JavaScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 68.7970165760452/100 |
| Open Issues | 3 |
| Last Updated | 2026-10-11 |
| Created | 2026-04-13 |
| Platforms | claude-code, cli, node |
| Est. Tokens | ~16k |
These tools work well together with capcut-cli for enhanced workflows:
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capcut-cli is Independent, unofficial CLI to edit CapCut and JianYing (剪映) projects — subtitles, timing, speed, volume, templates, cut long-form to shorts. No API needed, reads draft_content.json and draft_info.jso. It is categorized as a Agent Tool with 861 GitHub stars.
capcut-cli is primarily written in JavaScript. It covers topics such as agent-skills, ai-agent, automation.
You can find installation instructions and usage details in the capcut-cli GitHub repository at github.com/renezander030/capcut-cli. The project has 861 stars and 90 forks, indicating an active community.
capcut-cli is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to capcut-cli on Agent Skills Hub include video-recap-skills, cutcli-cookbook, OpenChatCut. 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: