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 Nicolepcx · Agent Tool · ★ 2.2k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ai-agents-the-definitive-guide safe to install? View the security audit →
⭐ If you find this repository helpful, please consider giving it a ⭐ here on GitHub (click the star button in the top right corner) It's a quick way to show support for this openly available code. ⭐ AI Agents - The definitive Guide This is the corresponding code for the book AI Agents - The Definitive Guide the book can be found here and on Amazon. The book has an accompanying website with quizzes and additional material, as well as a Discord channel. TOC Chapter 1 From LLMs to Agents: The Foundational Blueprint Chapter 2 Architectures and Patterns: Planning, Reactivity, and Multi-Agent-Systems Chapter 3 Advanced Planning, Reasoning, and Scalable Execution in Agents Chapter 4 Models Behind the Agents: Capabilities and Optimization Chapter 5 From Prototypes to Production: Contr
| Stars | 2,205 |
| Forks | 443 |
| Language | Jupyter Notebook |
| Category | Agent Tool |
| Quality Score | 59.0359623970463/100 |
| Last Updated | 2026-08-01 |
| Created | 2025-08-22 |
| Est. Tokens | ~18k |
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ai-agents-the-definitive-guide is Repo for AI Agents The Definitive Guide. It is categorized as a Agent Tool with 2.2k GitHub stars.
ai-agents-the-definitive-guide is primarily written in Jupyter Notebook. It covers topics such as agents, ai-agents, benchmarks.
You can find installation instructions and usage details in the ai-agents-the-definitive-guide GitHub repository at github.com/Nicolepcx/ai-agents-the-definitive-guide. The project has 2.2k stars and 443 forks, indicating an active community.
The top alternatives to ai-agents-the-definitive-guide on Agent Skills Hub include sre, DeepMCPAgent, mcp-agent. 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: