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 kaya70875 · Agent Tool · ★ 82
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ytfetcher safe to install? View the security audit →
YTFetcher ⚡ Build structured YouTube datasets for NLP, ML, sentiment analysis & RAG in minutes. A python tool for fetching thousands of videos fast from a Youtube channel along with structured transcripts and additional metadata. Export data easily as CSV, TXT, or JSON. 📚 Table of Contents Installation Quick CLI Usage Basic Usage (Python API) Features Fetching Specific Channel Tabs (Videos / Shorts / Streams) Using Different Fetchers Retreive Different Languages Filtering Converting ChannelData to Rows SQLite Cache Failed Transcripts & Retry Behavior [Fetching Only Manually Created Transcripts](#fetching-only
| Stars | 82 |
| Forks | 11 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 63.8902991939173/100 |
| Open Issues | 3 |
| Last Updated | 2026-07-04 |
| Created | 2025-07-12 |
| Platforms | browser, python |
| Est. Tokens | ~18k |
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ytfetcher is ⚡ Build structured YouTube datasets at scale — effortlessly fetch transcripts and rich metadata for NLP, ML, and AI workflows.. It is categorized as a Agent Tool with 82 GitHub stars.
ytfetcher is primarily written in Python. It covers topics such as ai-tools, bulk, data-extraction.
You can find installation instructions and usage details in the ytfetcher GitHub repository at github.com/kaya70875/ytfetcher. The project has 82 stars and 11 forks, indicating an active community.
The top alternatives to ytfetcher on Agent Skills Hub include decodo-openclaw-skill, context-compressor, create-llm. 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.
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