claw-insights and openclaw-trace
Open-source agent observability via session replay and metrics complements end-to-end tracing specifically for OpenClaw multi-agent systems, suggesting a relationship where the former provides general monitoring capabilities that could be enhanced by the latter's specialized tracing for a particular framework.
About claw-insights
LucaL6/claw-insights
Open-source agent observability — session replay, metrics, and shareable snapshots for AI agent workflows
Operates as a zero-intrusion read-only sidecar that tails logs and CLI output without SDK integration, storing data locally in SQLite and exposing observability through GraphQL APIs and Server-Sent Events. Built with an adapter architecture for extensibility beyond OpenClaw, it includes structured AI agent skills for autonomous setup and snapshot capture via REST API or CLI. Tech stack spans Express, GraphQL Yoga, SQLite, Satori rendering, and a React 19 frontend with real-time ECharts dashboards for token analytics and error tracking.
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