| name | swarm-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. V6 features embedded HTML, line-by-line JSON parsing, and capybara-inspired colors. |
| version | 6.1.0 |
| author | HappyCapy |
| triggers | ["launch dashboard","swarm dashboard","monitor agents","agent dashboard","live dashboard","show agent progress","track swarm"] |
Swarm Dashboard Skill
Real-time monitoring for AI agent swarms with a beautiful, auto-refreshing web UI.
Quick Start
from swarm_dashboard import launch_dashboard, update_agent_task_id
url = launch_dashboard(
swarm_name="My Project",
swarm_dir="/workspace/my-project",
agents={
"agent-1": {"role": "Core Architect", "wave": 1, "mission": "Setup"},
"agent-2": {"role": "Backend Dev", "wave": 2, "mission": "Build API"},
}
)
update_agent_task_id(
swarm_dir="/workspace/my-project",
agent_id="agent-1",
task_id="abc123"
)
Features
- Real-time Updates - Auto-refreshes every 2 seconds
- Smart Completion Detection - Auto-detects finished agents
- Capybara-Inspired UI - Natural color palette with light/dark themes
- Clickable Details - Live activity feed, tools used, files created
- Zero Dependencies - Pure Python stdlib
CLI Usage
swarm-dashboard serve --port 8080 --swarm-dir /workspace
swarm-dashboard launch --name "My Swarm" --dir /workspace
swarm-dashboard status --dir /workspace
swarm-dashboard stop --dir /workspace
Configuration
Environment variables:
SWARM_DIR - Directory with agent foldersTASK_DIR - Directory with task outputsDASHBOARD_PORT - Server port (default 8080)SWARM_NAME - Display name
API Endpoints
| Endpoint | Description |
|---|
GET / | Dashboard HTML |
GET /api/status | Swarm status JSON |
GET /api/agent/{id} | Agent details |
GET /health | Health check |
