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build-jvm-analysis

Profile JVM applications with async-profiler and JFR to identify bottlenecks and memory leaks.

7|3|Updated Dec 1, 2025
Search Tags:#profiling#jvm#dead-code#gc-tuning#memory-debugging#production-data#heap-dump
One-click install
npx skills add https://github.com/yzavyas/claude-1337 --skill build-jvm-analysis
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: build-jvm-analysis
Source: https://github.com/yzavyas/claude-1337/tree/main/plugins/jvm-analysis-1337/skills/build-jvm-analysis
Command: npx skills add https://github.com/yzavyas/claude-1337 --skill build-jvm-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

JVM runtime analysis guidance and tooling patterns to profile performance, tune garbage collection, and debug memory leaks using production data.

Core Features & Use Cases

  • Production-grade profiling: guidance on using async-profiler, JFR, and memory analysis to identify bottlenecks.
  • GC tuning and memory debugging: strategies to tune GC and locate memory leaks in JVM-based services.
  • Use Case: For a latency-sensitive Java service under load, apply these steps to locate hot paths and reduce GC pauses.

Quick Start

Run a guided JVM profiling workflow on a running Java service to identify hot paths and GC pauses.

Frequently Asked Questions about build-jvm-analysis

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

FAQPage Schema
How do I profile JVM performance bottlenecks in a production Java service?▼

To profile JVM performance bottlenecks, use production data with tools like async-profiler and JFR to identify hot paths and reduce latency. This provides guided workflows to analyze runtime profiling data for your Java services under load.

What is the best way to debug JVM memory leaks using heap dumps?▼

Debugging JVM memory leaks requires analyzing heap dumps from your running application to locate unreferenced objects. This provides memory analysis patterns and workflows to pinpoint leaks in JVM-based services using production traffic data.

How do I tune garbage collection to reduce GC pauses in a latency-sensitive Java application?▼

Tune garbage collection to reduce GC pauses by applying GC tuning guidelines to your JVM configuration. This offers strategies to adjust GC settings for latency-sensitive Java services experiencing high pause times under load.

Can I use async-profiler and JFR for production data profiling on a running service?▼

Yes, you can use async-profiler and JFR for production data profiling on a running service. This provides patterns to safely profile runtime performance and capture production traffic without requiring application downtime.

How do I detect dead code in a JVM application?▼

Detect dead code in a JVM application by applying runtime profiling workflows to identify unused execution paths. This uses production traffic data to locate and remove dead code that impacts overall memory and performance.

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