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

# Launch dashboard
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"},
    }
)

# After launching each agent with Task tool, update task ID
update_agent_task_id(
    swarm_dir="/workspace/my-project",
    agent_id="agent-1",
    task_id="abc123"  # From Task tool response
)

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

# Start server
swarm-dashboard serve --port 8080 --swarm-dir /workspace

# Launch in background
swarm-dashboard launch --name "My Swarm" --dir /workspace

# Check status
swarm-dashboard status --dir /workspace

# Stop
swarm-dashboard stop --dir /workspace

Configuration

Environment variables:

SWARM_DIR - Directory with agent folders
TASK_DIR - Directory with task outputs
DASHBOARD_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

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 # Launch dashboard 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"}, } ) # After launching each agent with Task tool, update task ID update_agent_task_id( swarm_dir="/workspace/my-project", agent_id="agent-1", task_id="abc123" # From Task tool response )

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

# Start server swarm-dashboard serve --port 8080 --swarm-dir /workspace # Launch in background swarm-dashboard launch --name "My Swarm" --dir /workspace # Check status swarm-dashboard status --dir /workspace # Stop swarm-dashboard stop --dir /workspace

Configuration

Environment variables:

SWARM_DIR - Directory with agent folders

TASK_DIR - Directory with task outputs

DASHBOARD_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