How does the skill identify agent versions?

It parses the 'pyproject.toml' file for each agent to extract the source version and compares it with the image tag in the Kubernetes deployment.

What Kubernetes namespace does this skill target?

The skill is pre-configured to monitor agents within the 'ai-agents' namespace.

Can I view logs for a specific agent using this skill?

Yes, it provides a detailed info command that retrieves the last 20 lines of logs and the recent deployment history for any specified agent.

How are 'core' libraries handled?

The skill includes a specific check for the 'core-agents' library, allowing you to monitor the version of shared dependencies used by all agents.

Does this skill work with any Kubernetes cluster?

It uses the KUBECONFIG located at /home/al/.kube/config by default, which can be customized to point to your specific cluster configuration.

AI Agent Monitor for Kubernetes

Name: AI Agent Monitor for Kubernetes
Author: X-McKay

byX-McKay

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分析与监控

Monitors and manages the deployment status, versions, and health of AI agents within Kubernetes clusters.

关于

This skill provides a centralized interface for tracking AI agents deployed in a Kubernetes environment. It automates the retrieval of source versions from project metadata, matches them against live container images, and reports real-time pod statuses and logs. Designed for developers managing multi-agent systems, it simplifies the observability workflow by providing a single source of truth for agent deployment parity, health metrics, and runtime troubleshooting directly within the Claude interface.

主要功能

Version auditing for shared core agent libraries
Automated discovery of AI agents within the project structure
Comparison between source versioning and deployed image tags
Real-time Kubernetes pod status and health monitoring
Instant access to recent container logs and deployment history
1 GitHub stars

使用场景

Troubleshooting agent crashes or 'unknown' pod statuses through integrated log retrieval
Ensuring version consistency across a fleet of specialized AI agents and their shared dependencies
Verifying that the latest agent code changes have been successfully deployed to production

关于

主要功能

Version auditing for shared core agent libraries
Automated discovery of AI agents within the project structure
Comparison between source versioning and deployed image tags
Real-time Kubernetes pod status and health monitoring
Instant access to recent container logs and deployment history
1 GitHub stars

使用场景

Troubleshooting agent crashes or 'unknown' pod statuses through integrated log retrieval
Ensuring version consistency across a fleet of specialized AI agents and their shared dependencies
Verifying that the latest agent code changes have been successfully deployed to production