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 browser-use · Agent Tool · ★ 2.0k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is macOS-use safe to install? View the security audit →
Tell your MacBook what to do, and it's done—across ANY app. Created by Ofir Ozeri ♥️ migrated in collaboration with Magnus and Gregor macOS-use enables AI agents to interact with your Macbook see it in action! Quick start ⚠️ Important: Review the Warning section before proceeding. With pip: From github Clone first Don't forget API key Supported providers: [OAI](https://pl
| Stars | 1,996 |
| Forks | 192 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 65.023311450624/100 |
| Open Issues | 16 |
| Last Updated | 2025-03-05 |
| Created | 2025-01-23 |
| Platforms | python |
| Est. Tokens | ~15k |
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macOS-use is Make Mac apps accessible for AI agents. It is categorized as a Agent Tool with 2.0k GitHub stars.
macOS-use is primarily written in Python.
You can find installation instructions and usage details in the macOS-use GitHub repository at github.com/browser-use/macOS-use. The project has 2.0k stars and 192 forks, indicating an active community.
macOS-use is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to macOS-use on Agent Skills Hub include notebooklm-skill, agent-skills, excalidraw-diagram-skill. 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: