Can the Resource Usage Tracker detect memory leaks?

Yes, it monitors memory patterns (heap, stack, and RSS) over time to identify usage growth indicative of leaks and suggests steps for resolution.

Does it provide real-time performance insights?

Yes, it leverages the resource-usage-tracker plugin to gather real-time data, allowing you to detect anomalies and bottlenecks as they occur.

How does this skill help reduce cloud costs?

The skill identifies underutilized resources and provides 'right-sizing' recommendations, ensuring you only pay for the infrastructure your application actually requires.

What metrics are specifically tracked by this skill?

It tracks CPU usage, memory consumption, disk and network I/O, file descriptors, database connections, and active thread or process counts.

Resource Usage Tracker

Name: Resource Usage Tracker
Author: intent-solutions-io

byintent-solutions-io

Analytics & Monitoring

Monitors and optimizes application resource consumption including CPU, memory, and network I/O to improve performance and reduce costs.

About

This skill empowers Claude to provide deep visibility into your application stack's resource utilization, identifying performance bottlenecks and cost-saving opportunities in real-time. It monitors critical metrics such as CPU cycles, memory allocation (heap, stack, RSS), disk and network I/O, and database connections. By analyzing this data, the skill offers actionable recommendations for right-sizing infrastructure, debugging memory leaks, and optimizing thread or connection pool configurations to ensure your application runs efficiently and cost-effectively throughout the development lifecycle.

Key Features

Tracking the impact of code changes on resource consumption patterns
Automated detection and diagnosis of memory leaks and bottlenecks
0 GitHub stars
Infrastructure right-sizing and cloud cost optimization recommendations
Real-time monitoring of CPU, memory, and disk/network I/O metrics
Analysis of database connection pool and thread/process utilization

Use Cases

Optimizing cloud infrastructure costs by right-sizing underutilized instances
Identifying and resolving application-level memory leaks during local development
Tuning database connection pools to handle high-concurrency workloads efficiently

About

Key Features

Tracking the impact of code changes on resource consumption patterns
Automated detection and diagnosis of memory leaks and bottlenecks
0 GitHub stars
Infrastructure right-sizing and cloud cost optimization recommendations
Real-time monitoring of CPU, memory, and disk/network I/O metrics
Analysis of database connection pool and thread/process utilization

Use Cases

Optimizing cloud infrastructure costs by right-sizing underutilized instances
Identifying and resolving application-level memory leaks during local development
Tuning database connection pools to handle high-concurrency workloads efficiently