by Jeomon · Agent Tool · ★ 302
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/CursorTouch/Web-Use.gitTaken from the project's README on GitHub. Check the security audit before running it.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 302 |
| Forks | 57 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 69/100 |
| Open Issues | 3 |
| Last Updated | 2026-08-06 |
| Created | 2024-10-03 |
| Platforms | browser, python |
| Est. Tokens | ~16k |
🌐 Web-Use Web-Use is an intelligent autonomous browsing agent, built to seamlessly navigate websites, interact with dynamic content, perform smart searches, download files, and adapt to ever-changing pages — all with minimal effort from you.
Looking for a Web-Use alternative? If you're comparing Web-Use with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Web-Use is a CDP powered Browser Agent
🚀 Custom modes for Roo Code VS Code extension - Enhanced AI coding assistance configurations
A curated collection of top-tier penetration testing tools and productivity utilities across multiple domains.
A desktop MCP client designed as a tool unitary utility integration, accelerating AI adoption through the Mode
🚀 MassGen is an open-source multi-agent scaling system that runs in your terminal, autonomously orchestrating
Just a Better Chatbot. Powered by Agent & MCP & Workflows.
Explore other popular agent tool tools:
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: