self-observe

Monitor OpenHeron runtime health, token usage, and error logs via command-line diagnostics.

10|3|Updated Feb 21, 2026
One-click install
npx skills add https://github.com/openheron/openheron --skill self-observe
Or copy as Structured Prompt for Agent
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

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill helps users understand the operational status and resource consumption of the OpenHeron AI assistant, enabling proactive issue detection and performance monitoring.

Core Features & Use Cases

  • Runtime Health Checks: Verifies the status of critical OpenHeron services like the gateway and heartbeat.
  • Token Usage Monitoring: Provides insights into LLM token consumption across different providers.
  • Error Log Analysis: Quickly surfaces recent errors and exceptions from log files.
  • Use Case: When experiencing slow responses or unexpected behavior, use this skill to get a consolidated overview of system health, token costs, and recent errors to diagnose the problem.

Quick Start

Run the self_status_report.sh script to generate a consolidated report of OpenHeron's runtime status and token usage.

Frequently Asked Questions about self-observe

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run a health check on OpenHeron services and diagnose performance issues?

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.

How can I track LLM token usage and costs across different providers?

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.

What is the best way to analyze error logs and identify system failures in OpenHeron?

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.

Can I monitor OpenHeron runtime status through command-line diagnostics?

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.

Do I need to install any dependencies to use OpenHeron diagnostics and log analysis?

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.

When should I use command-line diagnostics instead of other monitoring approaches for OpenHeron?

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.