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. Part of cursor-rules-java project
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67%
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Impact
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Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/162-java-profiling-analyze/SKILL.mdAnalyze 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?
Scope: Validate profiling results represent realistic load scenarios. Cross-reference multiple files. Include quantitative metrics.
Validate profiling results represent realistic load before analysis. Document assumptions and limitations. Cross-reference multiple files.
Read references/162-java-profiling-analyze.md and inventory profiling artifacts in profiler/results/.
Confirm datasets represent realistic load conditions and record assumptions/limitations before drawing conclusions.
Analyze memory/CPU/threading findings, cross-reference multiple files, and prioritize issues by Impact/Effort.
Create docs/profiling-problem-analysis-YYYYMMDD.md and docs/profiling-solutions-YYYYMMDD.md with quantitative evidence.
For detailed guidance, examples, and constraints, see references/162-java-profiling-analyze.md.
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