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162 java profiling analyze

Skill jabrena/plinth/skills/162-java-profiling-analyze

Plinth is an AI-native engineering toolkit for modern Java enterprise SDLC, built around reusable Commands, Agents, Skills, and MCP Servers.

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npx -y skills add jabrena/plinth --skill 162-java-profiling-analyze

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Use when you need to analyze Java profiling data collected during the detection phase — including interpreting flamegraphs, memory allocation patterns, CPU hotspots, threading issues, systematic problem categorization, evidence documentation with profiling-problem-analysis and profiling-solutions markdown files, or prioritizing fixes using Impact/Effort scoring. This should trigger for requests such as Analyze JFR profile; Analyze the profile; Analyze the performance; Analyze the memory; Analyze the threading; Analyze GC logs from profiling; Prioritize Java profiling bottlenecks by impact. Part of Plinth Toolkit

The file declares its own license as Apache-2.0. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

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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.

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