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 CelaDaniel · Agent Tool · ★ 724
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is free-ai-resources-x safe to install? View the security audit →
Free AI Learning Resources X Your open source gateway to mastering AI completely free, forever. 411+ hand picked resources · 30 specialized categories · 100% free · Community driven Start Learning · Browse All Categories · Contribute Why This Repo
| Stars | 724 |
| Forks | 106 |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 57.68082057091/100 |
| Open Issues | 7 |
| Last Updated | 2026-05-21 |
| Created | 2025-10-17 |
| Est. Tokens | ~10k |
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free-ai-resources-x is 🌟 A curated collection of free, high quality AI tools 🤖, APIs 🔗, datasets 📊, and learning resources 📚 covering machine learning 🧠, deep learning 🧩, generative AI 🎨, NLP 💬, and data science 📈. It is categorized as a Agent Tool with 724 GitHub stars.
You can find installation instructions and usage details in the free-ai-resources-x GitHub repository at github.com/CelaDaniel/free-ai-resources-x. The project has 724 stars and 106 forks, indicating an active community.
free-ai-resources-x is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to free-ai-resources-x on Agent Skills Hub include awesome-AI-toolkit, AITreasureBox, awesome-llms-fine-tuning. 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: