swarm-dashboard
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.
Best use case
swarm-dashboard is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using swarm-dashboard should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/swarm-dashboard/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How swarm-dashboard Compares
| Feature / Agent | swarm-dashboard | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Swarm Dashboard Skill
> Real-time monitoring for AI agent swarms with a beautiful, auto-refreshing web UI.
## Quick Start
```python
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
```bash
# 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 |Related Skills
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