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 MARKTECHPOST-AI-MEDIA-INC · Agent Tool · ★ 2.9k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is AI-Agents-Projects-Tutorials safe to install? View the security audit →
🤝 Show your support - give a ⭐️ if you liked the content Star History Agentic AI and Agents Tutorials/Implementations and Notebooks ▶ Microsoft Fara Tutorial: Run a Browser-Use Agent in Google Colab with a Mock OpenAI-Compatible Endpoint Codes Tutorial ▶ An Implementation of the Microsoft Agent Governance Toolkit for Safe AI Agent Tool Use with Policies, Approvals, Audit Logs, and Risk Controls Codes Tutorial ▶ Build Skill-Augmented AI Agents with SkillNet for Search, Evaluation, Graph Analysis, and Task Planning [Codes](https://github.com/Marktechpost/AI-Agents-Projects-Tutorials
| Stars | 2,908 |
| Forks | 617 |
| Language | Jupyter Notebook |
| Category | Agent Tool |
| Quality Score | 50.5973466295011/100 |
| Open Issues | 9 |
| Last Updated | 2026-09-20 |
| Created | 2025-05-15 |
| Est. Tokens | ~28k |
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AI-Agents-Projects-Tutorials is Multi-agent systems, memory, planning, reasoning loops. It is categorized as a Agent Tool with 2.9k GitHub stars.
AI-Agents-Projects-Tutorials is primarily written in Jupyter Notebook. It covers topics such as agent-skills, agentic-ai, agentic-ai-development.
You can find installation instructions and usage details in the AI-Agents-Projects-Tutorials GitHub repository at github.com/MARKTECHPOST-AI-MEDIA-INC/AI-Agents-Projects-Tutorials. The project has 2.9k stars and 617 forks, indicating an active community.
The top alternatives to AI-Agents-Projects-Tutorials on Agent Skills Hub include AI-Agents-Projects-Tutorials, PocketFlow, nexent. 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: