Developers relying on Claude Code for automated workflows have long struggled with silent failures, where a session appears active but is effectively dead. A new open-source project titled "AI-observibility" (sic) on GitHub aims to solve this by providing a local dashboard that monitors these sessions in real time.
Detecting The Stall
The tool, created by Mohammed Nihal, is designed specifically to identify when a Claude Code session gets stuck or hangs. Unlike high-level API monitoring that only tracks token usage or API availability, this dashboard drills down into the operational state of the coding agent itself. This distinction is critical for developers who need to know not just if the model is responding, but if the agent is actually making progress on the task at hand.
Why Local Matters
By keeping the observability stack local, the project sidesteps the privacy and latency concerns associated with third-party monitoring services. This approach allows for immediate feedback loops, which are essential when debugging complex agentic workflows. The project was highlighted on Hacker News, signaling that the developer community is feeling the pain of opaque AI tooling and is hungry for better visibility into how their coding assistants behave under load.
Key Takeaways
- The tool provides a dedicated dashboard for monitoring Claude Code session health.
- It specifically targets the detection of stuck or hanging sessions, a common pain point.
- The solution is local, prioritizing privacy and speed over cloud-based aggregation.
- The project was recently featured on Hacker News, indicating growing interest in AI observability.
The Bottom Line
As we push more autonomy into coding agents, we need the same robust monitoring tools we have for traditional servers. "AI-observibility" is a necessary step toward treating AI agents as production infrastructure rather than magic boxes.