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 AIFrontierLab · Agent Tool · ★ 97
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is AgentArk safe to install? View the security audit →
🛸 AgentArk Distilling Multi-Agent Intelligence into a Single LLM Agent. Yinyi Luo1 · Yiqiao Jin2 · Weichen Yu1 · Mengqi Zhang3 · Srijan Kumar2
| Stars | 97 |
| Forks | 13 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 70.0942760109686/100 |
| Open Issues | 3 |
| Last Updated | 2026-05-09 |
| Created | 2026-02-02 |
| Platforms | python |
| Est. Tokens | ~522k |
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AgentArk is Official Implementation for the Paper [AgentArk: Distilling Multi-Agent Intelligence into a Single LLM Agent](https://arxiv.org/abs/2602.03955). It is categorized as a Agent Tool with 97 GitHub stars.
AgentArk is primarily written in Python. It covers topics such as agent, ai, cmu.
You can find installation instructions and usage details in the AgentArk GitHub repository at github.com/AIFrontierLab/AgentArk. The project has 97 stars and 13 forks, indicating an active community.
AgentArk is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to AgentArk on Agent Skills Hub include zypher-agent, oreilly-ai-agents, decipher-research-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: