Optimize JVM performance through profiling, GC tuning, and memory analysis.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionjava-performanceExecute the skills CLI command in your project's root directory to begin installation:
Fetches java-performance from pluginagentmarketplace/custom-plugin-java and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate java-performance. Access via /java-performance in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Optimize JVM performance through profiling, GC tuning, and memory analysis.
This skill covers JVM performance optimization including garbage collection tuning, memory analysis, CPU profiling, and benchmarking with JMH.
Use when you need to:
# High-throughput
-XX:+UseG1GC
-XX:MaxGCPauseMillis=200
-Xms4g -Xmx4g
-XX:+AlwaysPreTouch
# Low-latency
-XX:+UseZGC
-XX:+ZGenerational
-Xms8g -Xmx8g
# Memory-constrained
-XX:+UseSerialGC
-Xms512m -Xmx512m
-XX:+UseCompressedOops
# Container-optimized
-XX:+UseContainerSupport
-XX:MaxRAMPercentage=75.0
-XX:+ExitOnOutOfMemoryError
# Thread dump
jstack -l <pid> > threaddump.txt
# Heap dump
jmap -dump:format=b,file=heap.hprof <pid>
# GC analysis
jstat -gcutil <pid> 1000 10
# Flight recording
jcmd <pid> JFR.start duration=60s filename=app.jfr
# Async profiler
./profiler.sh -d 30 -f profile.html <pid>
@BenchmarkMode(Mode.Throughput)
@Warmup(iterations = 3, time = 1)
@Measurement(iterations = 5, time = 1)
@State(Scope.Benchmark)
public class MyBenchmark {
@Benchmark
public void testMethod(Blackhole bh) {
bh.consume(compute());
}
}
| GC | Latency | Throughput | Heap Size |
|---|---|---|---|
| G1 | Medium | High | 4-32GB |
| ZGC | Very Low | Medium | 8GB-16TB |
| Shenandoah | Very Low | Medium | 8GB+ |
| Parallel | High | Very High | Any |
| Problem | Cause | Solution |
|---|---|---|
| GC thrashing | Heap too small | Increase heap |
| High latency | GC pauses | Switch to ZGC |
| Memory leak | Object retention | Heap dump + MAT |
| CPU spikes | Hot loops | Profile + optimize |
Skill("java-performance")
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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We added java-performance from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Keeps context tight: java-performance is the kind of skill you can hand to a new teammate without a long onboarding doc.
java-performance fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
java-performance is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
I recommend java-performance for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: java-performance is the kind of skill you can hand to a new teammate without a long onboarding doc.
We added java-performance from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
java-performance is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
java-performance fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: java-performance is focused, and the summary matches what you get after install.
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