agentic-ai-roadmap — security grade SAFE, quality 58/100

Security audit verdict: SAFE · quality 58/100

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 romanyn36 · Agent Tool · ★ 131

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

🔒 Is agentic-ai-roadmap safe to install? View the security audit →

About agentic-ai-roadmap

🚀 The Complete AI Engineer Roadmap 2026 Agentic & Generative AI: From Zero to Deployment A structured roadmap from absolute beginner fundamentals in Python and mathematics, through machine learning and deep learning, to building and deploying advanced agentic AI systems. 📋 About This Roadmap before we dive in,iam Rom

agenticagentic-ai-roadmapaiai-roadmapdeep-learninglangchainlanggraphlearllmmachine-learning

Quick Facts

Stars131
Forks1
CategoryAgent Tool
LicenseMIT
Quality Score57.5058464828033/100
Last Updated2026-08-21
Created2026-02-06
Est. Tokens~28k

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Frequently Asked Questions

What is agentic-ai-roadmap?

agentic-ai-roadmap is A comprehensive AI learning roadmap covering Python fundamentals, mathematics, machine learning, deep learning, LLMs, and agentic systems — focused on hands-on projects, practical tools, and real-worl. It is categorized as a Agent Tool with 131 GitHub stars.

How do I install or use agentic-ai-roadmap?

You can find installation instructions and usage details in the agentic-ai-roadmap GitHub repository at github.com/romanyn36/agentic-ai-roadmap. The project has 131 stars and 1 forks, indicating an active community.

What license does agentic-ai-roadmap use?

agentic-ai-roadmap is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to agentic-ai-roadmap?

The top alternatives to agentic-ai-roadmap on Agent Skills Hub include create-llm, openchatbi, ARIS-in-AI-Offer. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

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:

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