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arch-video-cut
Automatic Architecture Video Editing Workflow with Self-Learning Preferences
Legitimate architecture video editing workflow using ffmpeg for merging, subtitling, and audio mixing with a self-learning preference system. All shell execution is documented and necessary for video processing.
技能名称arch-video-cut
分析耗时28.5s
引擎pi
✓
可以安装
No action needed. Skill is safe to use.
资源类型声明权限推断权限状态证据
命令执行 WRITE WRITE ✓ 一致 scripts/full_workflow.py:46 subprocess.run(..., shell=True) — required for ffmpe…
文件系统 WRITE WRITE ✓ 一致 All writes scoped to data/ and config/ directories as documented
1 项发现
🔗
中危 外部 URL 外部 URL
http://www.ual-studio.com/
SKILL.md:242

目录结构

6 文件 · 29.5 KB · 1018 行
Markdown 3f · 510L Python 3f · 508L
├─ ▾ 📁 scripts
│ ├─ 🐍 full_workflow.py Python 263L · 10.3 KB
│ ├─ 🐍 manage_preferences.py Python 74L · 2.4 KB
│ └─ 🐍 preference_learner.py Python 171L · 5.5 KB
├─ 📝 README.md Markdown 54L · 877 B
├─ 📝 SELF_LEARNING_GUIDE.md Markdown 210L · 4.4 KB
└─ 📝 SKILL.md Markdown 246L · 6.0 KB

安全亮点

✓ All subprocess shell execution is directly documented via ffmpeg installation instructions in SKILL.md
✓ File I/O is strictly scoped to data/ and config/ directories, no sensitive paths accessed
✓ No external network connections made by runtime code (external URL is only in author branding in SKILL.md)
✓ No credential harvesting, environment variable iteration, or sensitive file access
✓ No obfuscation, base64 execution, or anti-analysis techniques
✓ No hidden functionality — SKILL.md accurately describes all capabilities
✓ No supply chain risks — uses only standard library and ffmpeg (documented as a prerequisite)
✓ Self-learning system only writes user preferences to config/user_preferences.json, no exfiltration