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performance-profiling

Diagnose CPU bottlenecks, memory leaks, and latency using profiling artifacts.

7|Updated Mar 19, 2026
Search Tags:#performance#optimization#profiling#load-testing#nodejs#jvm#flame-graphs
One-click install
npx skills add https://github.com/camilooscargbaptista/cto-toolkit --skill performance-profiling-camilooscargbaptista
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: performance-profiling
Source: https://github.com/camilooscargbaptista/cto-toolkit/tree/main/performance-profiling
Command: npx skills add https://github.com/camilooscargbaptista/cto-toolkit --skill performance-profiling-camilooscargbaptista

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps diagnose and remediate performance problems such as high CPU, memory leaks, latency spikes, low throughput, and contention by guiding measurement, profiling, targeted fixes, and verification.

Core Features & Use Cases

  • Structured investigation workflow: Define metrics, measure baselines, profile, form hypotheses, fix, and verify improvements.
  • Multi-platform guidance: Actionable profiling and remediation techniques for Node.js, Java/JVM, Flutter, and web frontends.
  • Tools & tactics: Advice on flame graphs, JFR and heap dumps, event loop monitoring, k6/Locust load tests, caching patterns, and GC tuning.
  • Operational checks: Practical checklists for production readiness, autoscaling, connection pools, and percentile monitoring (p50/p90/p99).

Quick Start

Use the performance-profiling skill to analyze a slow endpoint by providing observed metrics, profiling artifacts, or a description of the symptoms and environment.

Frequently Asked Questions about performance-profiling

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

FAQPage Schema
How do I find and fix CPU bottlenecks and memory leaks in a Node.js application?▼

To fix CPU bottlenecks and memory leaks in Node.js, you analyze flame graphs and monitor the event loop to identify blocking operations. This profiling workflow guides targeted remediation and verifies improvements through baseline metrics.

What is the best way to profile high latency and throughput regressions in Java JVM applications?▼

Profiling high latency and throughput regressions in JVM applications involves analyzing JFR recordings and heap dumps. This process diagnoses contention and GC issues, forming hypotheses for targeted fixes to restore expected performance.

Can I use flame graphs and heap dumps to diagnose performance issues in Flutter and web frontend projects?▼

Yes, flame graphs and heap dumps can diagnose performance issues in Flutter and web frontend projects. The profiling workflow applies multi-platform guidance to pinpoint UI rendering bottlenecks and high latency symptoms.

Do I need load testing results to troubleshoot p99 latency spikes and low throughput?▼

Yes, load testing results from tools like k6 or Locust are required to troubleshoot p99 latency spikes and low throughput. Observability data and load test results establish baselines and verify remediation steps under production conditions.

How do I tune caching strategies and connection pools for production readiness after profiling?▼

Tuning caching strategies and connection pools for production readiness requires applying operational checklists after profiling. This ensures autoscaling configurations and percentile monitoring (p50/p90/p99) effectively prevent future throughput regressions.

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