performance-monitor

Collect, analyze, and visualize real-time metrics from distributed systems.

1|Updated Apr 23, 2026

Search Tags:#monitoring #metrics #real-time #observability #distributed-systems #anomaly-detection

Ready to run

npx skills add https://github.com/mtsatryan/openclaw-ai-agents --skill performance-monitor-mtsatryan

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: performance-monitor
Source: https://github.com/mtsatryan/openclaw-ai-agents/tree/main/performance-monitor
Command: npx skills add https://github.com/mtsatryan/openclaw-ai-agents --skill performance-monitor-mtsatryan

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Real-time visibility into system health across distributed agent architectures, enabling teams to detect bottlenecks, prevent outages, and optimize performance.

Core Features & Use Cases

Real-time metric collection, aggregation, and visualization for CPU, memory, network, and service latency
Anomaly detection and alerting to trigger proactive incident response
End-to-end observability across multi-agent systems with dashboards, traces, and reports Use Case: Maintain SLA for a fleet of agents by continuously monitoring key performance indicators and automatically surfacing bottlenecks.

Quick Start

Enable instrumentation and deploy default dashboards to begin collecting core performance metrics immediately.

Frequently Asked Questions about performance-monitor

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

FAQPage Schema

How do I monitor real-time metrics across distributed systems?▼

You monitor real-time metrics across distributed systems by enabling instrumentation to collect, aggregate, and visualize CPU, memory, network throughput, and service latency data. This provides end-to-end observability to detect anomalies and optimize performance.

What is anomaly detection in multi-agent environments?▼

Anomaly detection in multi-agent environments is the process of continuously analyzing real-time system metrics to identify unusual patterns. It triggers proactive alerts for incident response, helping teams prevent outages and surface performance bottlenecks.

How do I set up dashboards for distributed system observability?▼

You set up dashboards for distributed system observability by deploying default dashboard configurations after enabling metric instrumentation. This immediately begins collecting core performance indicators like CPU usage, memory, network throughput, and latency.

Can I track service dependencies and network latency in real-time?▼

Yes, you can track service dependencies and network latency in real-time. The system collects and analyzes time-series metric data across multi-agent architectures, providing visual traces and reports to maintain service level agreements.

What is the best way to maintain SLA for a fleet of agents?▼

The best way to maintain SLA for a fleet of agents is by continuously monitoring key performance indicators across the distributed architecture. Real-time metric collection and automated anomaly detection surface bottlenecks to drive continuous performance improvements.

Do I need external dependencies for time-series storage and alerting?▼

No external dependencies are required for time-series storage and alerting. The system satisfies requirements for instrumented metric collection, alerting, and dashboard visualization natively, allowing you to begin tracking performance immediately.