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 →
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RemoteLab 中文 | English A cross-surface AI workbench that helps ordinary people hand repetitive digital work to AI. RemoteLab is not only for the small group of people who already know how to use AI well. The goal is to bring AI automation to a much wider set of users, especially people with lots of repetitive digital work but no engineering automation background. It does not care much whether the control surface is a phone, tablet, or desktop. The point is to let a user hand over a messy recurring task, screenshot, or sample file, have the AI clarify the problem first, and then let strong executors like , , and compatible local tools do the real work on a real machine. Current baseline: — an owner-first session runtime, durable on-disk history, executor adapters, App-based workflow packaging, and a no-build web UI that works across phone and desktop. Reach the same system from desktop, phone, and integration surfaces like Feishu or email-driven flows. Quick install If the demo makes sense, do not keep reading.
| Stars | 109 |
| Forks | 32 |
| Language | JavaScript |
| Category | AI Tool |
| License | MIT |
| Quality Score | 59.7553198600912/100 |
| Open Issues | 3 |
| Last Updated | 2026-08-06 |
| Created | 2026-02-27 |
| Platforms | browser, node |
| Est. Tokens | ~515k |
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remotelab is Self-hosted remote access to Agent Tools from any browser — phone, tablet, or computer. It is categorized as a AI Tool with 109 GitHub stars.
remotelab is primarily written in JavaScript.
You can find installation instructions and usage details in the remotelab GitHub repository at github.com/Ninglo/remotelab. The project has 109 stars and 32 forks, indicating an active community.
remotelab is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to remotelab on Agent Skills Hub include SciToolAgent, redesigned-pancake, claude-code-voice-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: