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 jontsai · Codex Skill · ★ 244
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is openclaw-command-center safe to install? View the security audit →
🦞 OpenClaw Command Center English | 简体中文 Mission control for your AI agents Features • Quick Start • Security • Configuration Why Command Center? Your AI agents are running 24/7. You need to know what they're doing. Command Center gives you real-time visibility into your OpenClaw deployment — sessions, costs, system health, scheduled tasks — all in one secure dashboard. ⚡ Fast Single API call — unified state endpoint, not 16+ separate requests 2-second updates — real-time SSE push, not polling 5-second cache — backend stays responsive under load Instant startup — no build step, no compilation 🪶 Lightweight Zero dependencies for users — just Node.js 200KB total — dashboard + server No
| Stars | 244 |
| Forks | 58 |
| Language | JavaScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 76.1388793822519/100 |
| Open Issues | 6 |
| Last Updated | 2026-09-01 |
| Created | 2026-01-29 |
| Platforms | claude-code, node |
| Est. Tokens | ~16k |
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openclaw-command-center is 🤖 AI assistant command and control dashboard — Spawn more Overlords!. It is categorized as a Codex Skill with 244 GitHub stars.
openclaw-command-center is primarily written in JavaScript. It covers topics such as agent-orchestration, ai, ai-agents.
You can find installation instructions and usage details in the openclaw-command-center GitHub repository at github.com/jontsai/openclaw-command-center. The project has 244 stars and 58 forks, indicating an active community.
openclaw-command-center is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to openclaw-command-center on Agent Skills Hub include cai, claude-emporium, better-chatbot. 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: