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 Agents365-ai · Claude Skill · ★ 50
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is yt2bb safe to install? View the security audit →
yt2bb - YouTube to Bilibili Video Repurposing 中文文档 A Claude Code skill that repurposes YouTube videos for Bilibili with bilingual (EN/ZH) hardcoded subtitles. Compatible with Claude Code, OpenClaw, Hermes Agent, Pi (pi-mono), and indexed by SkillsMP. Workflow Usage Installation Claude Code OpenClaw Hermes Agent Pi (pi-mono) Prerequisites Python 3 ffmpeg yt-dlp openai-whisper YouTube account logged in via Chrome browser (yt-dlp extracts cookies aut
| Stars | 50 |
| Forks | 4 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 68.4371621614765/100 |
| Last Updated | 2026-08-30 |
| Created | 2026-02-17 |
| Platforms | claude-code, python |
| Est. Tokens | ~14k |
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yt2bb is YouTube to Bilibili video repurposing with bilingual subtitles. It is categorized as a Claude Skill with 50 GitHub stars.
yt2bb is primarily written in Python. It covers topics such as agent-skills, bilibili, claude-code.
You can find installation instructions and usage details in the yt2bb GitHub repository at github.com/Agents365-ai/yt2bb. The project has 50 stars and 4 forks, indicating an active community.
yt2bb is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to yt2bb on Agent Skills Hub include claude-skills, skills, claudepro-directory. 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: