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 longzhi · Codex Skill · ★ 57
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is clawhive safe to install? View the security audit →
clawhive English | 中文 An open-source, Rust-native alternative to OpenClaw — deploy your own AI agents across Telegram, Discord, Feishu/Lark, WhatsApp, WeChat, and more with a single binary. One binary, 14 MB, zero runtime dependencies. No Node.js, no npm, no Docker — just download, configure, and run. Installation Auto-detects OS/architecture, downloads latest release, installs binary and skills to . After installation, run to activate in your current shell: Or download manually from GitHub Releases. Setup Configure providers, agents, and channels using either method: Option A: Web Setup Wizard — Start the server and open the browser-based wizard:
| Stars | 57 |
| Forks | 14 |
| Language | Rust |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 66.6045378651611/100 |
| Open Issues | 17 |
| Last Updated | 2026-05-13 |
| Created | 2026-02-12 |
| Platforms | rust |
| Est. Tokens | ~2681k |
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clawhive is Lightweight, Rust-native AI Agent platform. Security sandbox from day one.. It is categorized as a Codex Skill with 57 GitHub stars.
clawhive is primarily written in Rust. It covers topics such as a2a, agent, agent-framework.
You can find installation instructions and usage details in the clawhive GitHub repository at github.com/longzhi/clawhive. The project has 57 stars and 14 forks, indicating an active community.
clawhive is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to clawhive on Agent Skills Hub include zeph, awesome-a2a, ai-agent-tools-catalog. 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: