mcpField
1
162-java-profiling-analyze

162-java-profiling-analyze

github.com/jabrenaDevelopment456355 installsUpdated 1d ago
Repository

About 162-java-profiling-analyze

A Java profiling analysis skill for developers who need to assess performance data. It validates workload relevance, cross-checks profiling artifacts, prioritizes bottlenecks, and records evidence and caveats in reports.

Key features

  1. 01Inventory profiling artifacts
  2. 02Validate workload realism
  3. 03Analyze memory, CPU, and threads
  4. 04Cross-reference profiling files
  5. 05Prioritize by Impact/Effort
  6. 06Document evidence and limitations

Use cases

  1. 01Investigating Java CPU hotspots
  2. 02Checking memory leaks and GC pressure
  3. 03Diagnosing thread contention or deadlocks

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/jabrena/plinth --skill 162-java-profiling-analyze

After installing, type/162-java-profiling-analyzein Claude Code to confirm it loaded.

Bundled filesreferences/162-java-profiling-analyze.md

Details

From the project README

Java Profiling Workflow / Step 2 / Analyze profiling data

Analyze profiling results systematically: inventory results (flamegraphs, JFR, GC logs, thread dumps), identify problems (memory leaks, CPU hotspots, threading issues), document findings using standardized templates (profiling-problem-analysis-YYYYMMDD.md, profiling-solutions-YYYYMMDD.md), prioritize using Impact/Effort scores, and correlate multiple profiling files for validation.

What is covered in this Skill?

  • Inventory: scan profiler/results/ for allocation-flamegraph, heatmap-cpu, memory-leak, *.jfr, *.log, *.txt
  • Problem identification: memory (leaks, excessive allocations, GC pressure), performance (CPU hotspots, blocking), threading (deadlocks, contention, pool saturation)
  • Documentation: docs/profiling-problem-analysis-YYYYMMDD.md, docs/profiling-solutions-YYYYMMDD.md
  • Prioritization: Impact (1–5) / Effort (1–5), focus on high priority first
  • Tools: async-profiler, JFR, JProfiler/YourKit, GCViewer, flamegraphs, heatmaps

Scope: Validate profiling results represent realistic load scenarios. Cross-reference multiple files. Include quantitative metrics.

Constraints

Validate profiling results represent realistic load before analysis. Document assumptions and limitations. Cross-reference multiple files.

  • VALIDATE: Ensure profiling results represent realistic load scenarios before analysis
  • DOCUMENT: Record assumptions and limitations in analysis reports
  • CROSS-REFERENCE: Use multiple profiling files to validate findings
  • BEFORE APPLYING: Read the reference for problem analysis and solutions templates
  • EDGE CASE: If request scope is ambiguous, stop and ask a clarifying question before applying changes
  • EDGE CASE: If required inputs, files, or tooling are missing, report what is missing and ask whether to proceed with setup guidance

When to use this skill

  • Analyze JFR profile
  • Analyze the profile
  • Analyze the performance
  • Analyze the memory
  • Analyze the threading
  • Analyze the GC
  • Analyze the profiling
  • Prioritize Java profiling bottlenecks by impact
  • Performance analysis

Workflow

  1. Read analysis reference and inventory inputs

Read references/162-java-profiling-analyze.md and inventory profiling artifacts in profiler/results/.

  1. Validate data quality and assumptions

Confirm datasets represent realistic load conditions and record assumptions/limitations before drawing conclusions.

  1. Identify and prioritize bottlenecks

Analyze memory/CPU/threading findings, cross-reference multiple files, and prioritize issues by Impact/Effort.

  1. Document findings and solution options

Create docs/profiling-problem-analysis-YYYYMMDD.md and docs/profiling-solutions-YYYYMMDD.md with quantitative evidence.

Reference

For detailed guidance, examples, and constraints, see references/162-java-profiling-analyze.md.

Comments

Markdown supported