openclaw-command-center: AI assistant command and control dashboard — Spawn more Overlords

by jontsai · Codex Skill · ★ 246

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install openclaw-command-center

git clone https://github.com/jontsai/openclaw-command-center

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 76/100

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.

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.

agent-orchestrationaiai-agentsanthropicautomationclaudedashboardllamallmmonitoring

Quick Facts

Stars246
Forks57
LanguageJavaScript
CategoryCodex Skill
LicenseMIT
Quality Score76/100
Open Issues3
Last Updated2026-10-06
Created2026-01-29
Platformsclaude-code, node
Est. Tokens~16k

About openclaw-command-center

🦞 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.

Compatible Skills

These tools work well together with openclaw-command-center for enhanced workflows:

  • clawbridge — semantic(0.22)+complementary+same_lang+similar_pop+shared_platform (53%)
  • hello-claw — semantic(0.18)+complementary+same_lang+similar_pop+shared_platform (51%)
  • claw-dashboard — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (51%)
  • claudekit — semantic(0.15)+complementary+same_lang+similar_pop+shared_platform (50%)
  • claude-code-karma — semantic(0.17)+complementary+rare_topics+similar_pop+shared_platform (50%)

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How this security grade is produced

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:

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