Monitor OpenHeron runtime health, token usage, and error logs via command-line diagnostics.
npx skills add https://github.com/openheron/openheron --skill self-observe
Please help me install this Agent Skill. Skill: self-observe Source: https://github.com/openheron/openheron/tree/main/openheron/skills/self-observe Command: npx skills add https://github.com/openheron/openheron --skill self-observe
This Skill helps users understand the operational status and resource consumption of the OpenHeron AI assistant, enabling proactive issue detection and performance monitoring.
Run the self_status_report.sh script to generate a consolidated report of OpenHeron's runtime status and token usage.
High-intent search queries and answers about installing and using this skill.
To run a health check on OpenHeron services, execute the self_status_report.sh script. It verifies critical services like the gateway and heartbeat, providing a consolidated overview of runtime status to diagnose performance issues.
You can track LLM token usage and costs across different providers by running the self_status_report.sh script. It provides insights into token consumption, enabling you to monitor and manage LLM costs effectively.
The best way to analyze error logs and identify system failures in OpenHeron is by using the self-observe skill. It quickly surfaces recent errors and exceptions from log files, helping you identify failures during slow responses or unexpected behavior.
Yes, you can monitor OpenHeron runtime status through command-line diagnostics. The skill satisfies requirements for operational visibility by providing scripts that generate consolidated reports of system health and token usage.
No, you do not need to install any dependencies to use OpenHeron diagnostics and log analysis. The skill operates independently with its built-in scripts, requiring no additional environment setup to start monitoring system health.
You should use command-line diagnostics for OpenHeron when you need proactive issue detection, operational visibility, and quick consolidation of runtime health, token usage, and recent errors to address slow responses or unexpected behavior.
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