openclaw-dashboard: Secure, real-time monitoring dashboard for OpenClaw AI agents

by tugcantopaloglu · Codex Skill · ★ 699

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

How to install openclaw-dashboard

git clone https://github.com/tugcantopaloglu/openclaw-dashboard.git

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: CAUTION · quality 69/100

Flagged: reads agent memory, sudo usage. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

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.

ai-agentsclaudedashboarddevopsllmmfamonitoringnodejsopenclawraspberry-pi

Quick Facts

Stars699
Forks118
LanguageHTML
CategoryCodex Skill
LicenseMIT
Quality Score69/100
Last Updated2026-11-05
Created2026-02-10
Platformsbrowser, claude-code
Est. Tokens~21k

About openclaw-dashboard

OpenClaw Agent Dashboard A beautiful, secure, real-time monitoring dashboard for OpenClaw agents. Track sessions, monitor API usage, view costs, manage memory files, and keep tabs on system health — all in one place.

Compatible Skills

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

  • MedgeClaw — semantic(0.22)+complementary+same_lang+similar_pop+shared_platform (53%)
  • ruby_llm-agents — semantic(0.30)+complementary+rare_topics+similar_pop (50%)
  • Lucid — semantic(0.26)+complementary+rare_topics+similar_pop+shared_platform (49%)
  • claude-code-usage-bar — semantic(0.23)+complementary+rare_topics+similar_pop+shared_platform (47%)
  • claude-swarm — semantic(0.33)+complementary+similar_pop+shared_platform (46%)

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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:

View on GitHub → Browse Codex Skill tools