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 rokbenko · Agent Tool · ★ 320
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ai-playground safe to install? View the security audit →
Code from YouTube channel Code AI with Rok Found something awesome here? Star this repo and help me hit 325 ⭐! Why am I using AI voiceover? Want to support me? 📚 Table of contents 📚 Click to expand LLM providers OpenAI Google Frameworks LlamaIndex Agents LangGraph CrewAI [Fetch.ai](https://github.com/rokbenko/ai-play
| Stars | 320 |
| Forks | 85 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 55.2312154706805/100 |
| Open Issues | 3 |
| Last Updated | 2026-04-23 |
| Created | 2023-11-07 |
| Platforms | gemini, python |
| Est. Tokens | ~10182k |
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ai-playground is Code from tutorials presented on the "Code AI with Rok" YouTube channel. It is categorized as a Agent Tool with 320 GitHub stars.
ai-playground is primarily written in Python. It covers topics such as anthropic, crewai, exa.
You can find installation instructions and usage details in the ai-playground GitHub repository at github.com/rokbenko/ai-playground. The project has 320 stars and 85 forks, indicating an active community.
ai-playground is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ai-playground on Agent Skills Hub include corpusos, open-research-ANA, go-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: