162 Java Profiling Analyze

Community

jabrena

162-java-profiling-analyze

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

Overview

Publisher	jabrena
Repository	`plinth`
Skill name	`162-java-profiling-analyze`
Stars	455
Forks	95
Bundled files	1
License	Apache-2.0
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by jabrena on GitHub. Read the source before you install it.

Installation

Install the 162 Java Profiling Analyze AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/jabrena/plinth/tree/main/skills/162-java-profiling-analyze
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/jabrena/plinth.git /tmp/plinth
mkdir -p .claude/skills
cp -r /tmp/plinth/skills/162-java-profiling-analyze .claude/skills/162-java-profiling-analyze

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable 162 Java Profiling Analyze in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads 162 Java Profiling Analyze on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so 162 Java Profiling Analyze is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

Read analysis reference and inventory inputs

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

Validate data quality and assumptions

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

Identify and prioritize bottlenecks

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

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.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

references/162-java-profiling-analyze.md9 KB

Frequently asked questions

What does the 162 Java Profiling Analyze AI skill do?

Why use 162 Java Profiling Analyze on TypingMind?

Because you install it once and use it with any model. 162 Java Profiling Analyze is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install 162 Java Profiling Analyze in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jabrena/plinth/tree/main/skills/162-java-profiling-analyze. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use 162 Java Profiling Analyze?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with 162 Java Profiling Analyze?

As many as you like. As long as a model supports skills, you can use 162 Java Profiling Analyze with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the 162 Java Profiling Analyze AI skill free?

Yes. It is published on GitHub by jabrena under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Java Profiling Workflow / Step 2 / Analyze profiling data

Constraints

When to use this skill

Workflow

Reference

Bundled files

Frequently asked questions

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