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 microclaw · Codex Skill · ★ 746
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is microclaw safe to install? View the security audit →
MicroClaw English | 中文 One agent runtime for Telegram, Discord, Slack, Feishu, IRC, Web, and more. Multi-step tool use, persistent memory, scheduled tasks, skills, MCP, and a local web control plane. Quick Start | Install | Why MicroClaw | Architecture | Docs Quick Routes: Tools · Config Defaults · Provider Matrix · Runbook · Web Hooks · <a href="docs/clawhub
| Stars | 746 |
| Forks | 138 |
| Language | Rust |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 74.8700194770272/100 |
| Open Issues | 3 |
| Last Updated | 2026-10-06 |
| Created | 2026-02-07 |
| Platforms | rust |
| Est. Tokens | ~34k |
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microclaw is 🦀An agentic AI assistant that lives in your chats, inspired by nanoclaw and incorporating some of its design ideas. Built with Rust 🦀. It is categorized as a Codex Skill with 746 GitHub stars.
microclaw is primarily written in Rust. It covers topics such as bot, nanoclaw, openclaw.
You can find installation instructions and usage details in the microclaw GitHub repository at github.com/microclaw/microclaw. The project has 746 stars and 138 forks, indicating an active community.
microclaw is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to microclaw on Agent Skills Hub include OpenClaw-Medical-Skills, clawsec, ClawPanel. 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: