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 mahseema · Agent Tool · ★ 86
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is aibooks safe to install? View the security audit →
AIBooks A curated list of books on Artificial Intelligence (AI), Machine Learning (ML), Deep Learning, and Transformers. This list is intended for students, educators, researchers, and professionals who are interested in exploring the theoretical foundations, practical applications, and future directions of these technologies. Inspired by GoBooks Contents Artificial Intelligence & Machine Learning Deep Learning Transformers and Advanced Topics Practical Guides and Applications Artificial Intelligence & Machine Learning Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig A comprehensive text that provides an in-depth overview of the entire field of artificial intelligence, including various AI techniques and theories. Pattern Recognition and Machine Learning by Christopher M. Bishop This book offers an introduction to the field of pattern recognition and machine learning, aimed at advanced undergraduates and graduate students. [Machine Learning: A Probabilistic Perspective](https://www.amazon.com/Machine-Learning-Probabilistic-Perspective-Computation/dp
| Stars | 86 |
| Forks | 9 |
| Category | Agent Tool |
| Quality Score | 48.6234537626373/100 |
| Last Updated | 2025-08-03 |
| Created | 2023-08-31 |
| Est. Tokens | ~5k |
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aibooks is Curated List of AI, ML and Deep Learning books. It is categorized as a Agent Tool with 86 GitHub stars.
You can find installation instructions and usage details in the aibooks GitHub repository at github.com/mahseema/aibooks. The project has 86 stars and 9 forks, indicating an active community.
The top alternatives to aibooks on Agent Skills Hub include kindly-web-search-mcp-server, clanker, toolsdk-mcp-registry. 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: