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Ai Agents Dashboard
ASecurityLive real-time dashboard for monitoring AI agent swarms with smart completion detection, clickable agent detail views, idle time tracking, and activity streaming. Auto-launches a beautiful web UI with capybara-inspired colors.
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- Added October 17, 2026
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[](https://www.skillsdirectory.com/skills/diegosouzapw-ai-agents-dashboard)---
name: ai-agents-dashboard
description: Live real-time dashboard for monitoring AI agent swarms with smart completion detection, clickable agent detail views, idle time tracking, and activity streaming. Auto-launches a beautiful web UI with capybara-inspired colors.
version: 6.0.0
author: HappyCapy
triggers:
- launch dashboard
- agent dashboard
- monitor agents
- live dashboard
- show agent progress
- track swarm
- ai dashboard
---
# AI Agents Dashboard Skill
> Real-time monitoring for AI agent swarms with a beautiful, auto-refreshing web UI.
## Features
- **Real-time Updates**: Auto-refreshes every 2 seconds
- **Smart Completion Detection**: Auto-detects when agents finish
- **Last Activity Tracking**: Shows "Xs/Xm/Xh ago" for each agent
- **Idle State Detection**: Agents idle >60s shown as "IDLE"
- **Beautiful UI**: Capybara-inspired color palette with light/dark themes
- **Clickable Agent Details**: Click any agent for live activity feed
- **Zero Dependencies**: Pure Python stdlib + vanilla HTML/CSS/JS
- **Single File**: Self-contained with embedded HTML
## Quick Start
### 1. Create Swarm Configuration
Create `swarm-config.json` in your project directory:
```json
{
"swarm_name": "My Project Swarm",
"start_time": "2026-02-05T14:00:00Z",
"agents": {
"agent-1": {
"role": "Core Architect",
"wave": 1,
"task_id": "abc123",
"mission": "Set up project structure"
},
"agent-2": {
"role": "Backend Developer",
"wave": 2,
"task_id": "def456",
"mission": "Build API endpoints"
}
}
}
```
### 2. Launch Dashboard
```bash
# Copy server to your workspace
cp ~/.claude/skills/ai-agents-dashboard/ai-agents-dashboard-server.py /workspace/my-project/
# Set environment variables
export SWARM_DIR="/workspace/my-project"
export SWARM_NAME="My Project Swarm"
export DASHBOARD_PORT=8080
# Start server
python3 /workspace/my-project/ai-agents-dashboard-server.py &
# Export port for web access
/app/export-port.sh 8080
```
### 3. View Dashboard
Open the exported URL in your browser. Dashboard auto-refreshes every 2 seconds.
## Configuration
### Environment Variables
| Variable | Default | Description |
|----------|---------|-------------|
| `SWARM_DIR` | Current directory | Directory containing swarm-config.json |
| `TASK_DIR` | `/tmp/claude-1000` | Directory containing task output files |
| `DASHBOARD_PORT` | `8080` | HTTP server port |
| `SWARM_NAME` | From config | Display name for the swarm |
## API Endpoints
### GET /
Returns the dashboard HTML page.
### GET /api/status
Returns JSON with full swarm status.
### GET /api/agent/{agent-id}
Returns detailed information about a specific agent.
### GET /health
Returns `{"status": "ok", "version": "v6"}` for health checks.
## Status States
| Status | Color | Condition |
|--------|-------|-----------|
| `pending` | Gray | No output file exists |
| `running` | Orange (pulse) | Active output, <60s since last event |
| `idle` | Teal | 60-120s since last event |
| `completed` | Green | >120s idle OR completion marker found |
| `failed` | Red | status.json has `"status": "failed"` |
## Files in This Skill
```
~/.claude/skills/ai-agents-dashboard/
├── SKILL.md # This file
├── ai-agents-dashboard-server.py # Main server (self-contained)
└── launch-dashboard.py # Launcher utility script
```
## Using the Launcher Utility
```python
from launch_dashboard import launch_dashboard, update_agent_task_id
# Launch dashboard
url = launch_dashboard(
swarm_name="my-project",
swarm_dir="/workspace/my-project",
agents={
"agent-1-core": {"role": "Core", "wave": 1, "mission": "Setup"},
"agent-2-api": {"role": "API", "wave": 2, "mission": "Build API"},
}
)
# Update agent task IDs after launching
update_agent_task_id(
swarm_dir="/workspace/my-project",
agent_id="agent-1-core",
task_id="abc123def456"
)
```
## Troubleshooting
### Port already in use?
```bash
lsof -i :8080
export DASHBOARD_PORT=8081
```
### Live Activity Feed Not Showing?
Call `update_agent_task_id()` after launching each agent to create symlinks.
## Credits
Built for monitoring AI agent swarms in real-time.
Attribution
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