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ENJA

openclaw-agent-dashboard

karem505/openclaw-agent-dashboard

A glassmorphic, single-file agent management and server monitoring dashboard designed for OpenClaw. It provides real-time task tracking, API monitoring, document editing, and server metrics in a responsive UI.

49 12MITUpdated 2026-06-09
View on GitHubOpen source file

Overview

This project provides a sleek, single-file HTML dashboard and accompanying server monitor built for OpenClaw. It features a modern dark glassmorphic interface with zero build steps, relying on vanilla JavaScript, CSS3, and native Canvas charts. It supports task kanban boards, live agent logs, markdown-powered document editing, API integration monitoring, mobile-friendly navigation, PWA support, and secure browser-native authentication.

Capabilities

  • ▸Task management with Kanban boards and list views
  • ▸Markdown document viewer and editor with live previews
  • ▸API integration monitoring cards with status indicators
  • ▸Real-time agent log streaming and session tracking
  • ▸Server performance metrics monitoring (CPU, memory, disk, network, uptime)
  • ▸Mobile-responsive layout with bottom navigation and PWA support
  • ▸Browser-native authentication with cookie sessions

Best for

Monitoring active AI agent sessions, token usage, and system logs in real time, Managing tasks using a drag-and-drop Kanban board interface with priority and status filters, Tracking server CPU, memory, disk, and network metrics through visual gauge cards and sparklines, Accessing and managing agent workspaces and system-installed skills from mobile devices via PWA support

Evoa Score breakdown= Σ (score × weight)
73
Task usefulness20%100 → +20.0

実タスクにどれだけ役立つか（機能の豊富さ・用途の明確さ）。 — AIによるcapabilities/use-cases解析

Code quality15%85 → +12.8

実装・指示の品質。 — AIによるSKILL.md/README解析

Maintenance15%85 → +12.8

リポジトリがどれだけ活発に保守されているか。 — GitHub 最終push日時の新しさ

Documentation12%42 → +5.0

ドキュメントの充実度・分かりやすさ。 — README/独自要約の情報量

Security15%80 → +12.0

危険・不審な挙動が無いか。 — AIによるセキュリティレビュー

Originality10%70 → +7.0

ありふれたラッパーではない独自性。 — AIによる独自性判定

Popularity8%47 → +3.8

コミュニティの採用度。 — GitHub Stars/Forks（対数スケール）

Compatibility5%0 → +0.0

対応AIエージェントの広さ。 — AIによる対応エージェント判定

Weighted total73.3 / 100

ライセンス不明/制限あり（Red）のSkillは総合スコアに0.85倍の補正を適用します。 ランキングはこのScoreのみで決まり、広告で変わりません。 算出方法の詳細 →

Security considerations

Authentication is managed via tokens or query parameters, and cookie sessions. Exposing the server via public tunnels like Tailscale Funnel requires configuring secure secret tokens.

Categories

AutomationDevOpsProductivityAI Engineering

Summary and analysis are original content generated by AI Skills Rank. The skill's source text is not reproduced here — view it on the linked repository.