openclaw-dashboard and openclaw-trace
The first tool provides a dashboard to visualize data, while the second offers end-to-end tracing, making them complementary for observability within OpenClaw multi-agent systems.
About openclaw-dashboard
mudrii/openclaw-dashboard
A beautiful, zero-dependency command center for OpenClaw AI agents
This tool provides a centralized hub to monitor your OpenClaw AI agents, especially when running many of them for critical operations. It takes data from your OpenClaw setup, logs, and system resources to present an at-a-glance overview of agent health, costs, scheduled tasks, and performance. Operations managers, AI product owners, or anyone overseeing AI automation would use this to ensure their agents are running efficiently and within budget.
About openclaw-trace
Tell-Me-Mo/openclaw-trace
End-to-end tracing and observability for OpenClaw multi-agent systems
This tool provides a clear view into how your OpenClaw AI agents are performing, consuming resources, and incurring costs. It takes the output logs from your agents and visualizes their execution traces, token usage, and expenses. Anyone managing or optimizing multi-agent AI systems will find this useful for understanding agent behavior and resource consumption.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work