164 Java Profiling Verify

Community

jabrena

164-java-profiling-verify

Use when you need to verify Java performance optimizations by comparing profiling results before and after refactoring — including baseline validation, post-refactoring report generation, quantitative before/after metrics comparison, side-by-side flamegraph analysis, regression detection, or creating profiling-comparison-analysis and profiling-final-results documentation. This should trigger for requests such as Verify performance fix; Verify the performance; Verify the memory; Verify the threading; Compare before and after profiling results; Check for performance regressions after refactoring. Part of Plinth Toolkit

Overview

Publisher	jabrena
Repository	`plinth`
Skill name	`164-java-profiling-verify`
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 164 Java Profiling Verify 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/164-java-profiling-verify
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/164-java-profiling-verify .claude/skills/164-java-profiling-verify

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

Use it in TypingMind

Enable 164 Java Profiling Verify 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 164 Java Profiling Verify 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 164 Java Profiling Verify 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 4 / Verify results

Verify performance optimizations through rigorous before/after comparison: ensure baseline and post-refactoring profiling data use identical test conditions, generate post-refactoring reports, compare metrics (memory, CPU, GC, threading), perform side-by-side flamegraph analysis, document findings in profiling-comparison-analysis-YYYYMMDD.md and profiling-final-results-YYYYMMDD.md, and validate success criteria.

What is covered in this Skill?

Pre-refactoring baseline: run profiler with same load before changes
Post-refactoring: generate new reports with identical test conditions
Comparison: memory (leaks, allocations, GC), CPU (hotspots, contention), visual flamegraph comparison
Documentation: profiler/docs/profiling-comparison-analysis-YYYYMMDD.md, profiler/docs/profiling-final-results-YYYYMMDD.md
File naming: baseline/after suffixes, timestamp-based organization
Validation: verify reports exist, compare metrics, identify regressions

Scope: Identical test conditions are critical. Document test scenarios. Validate application runs with refactored code before generating new reports.

Constraints

Use identical test conditions between baseline and post-refactoring. Verify both report sets are complete. Document test scenarios.

CONSISTENCY: Use identical test conditions and load patterns for baseline and post-refactoring
VALIDATE: Ensure both baseline and post-refactoring reports exist and are non-empty before comparison
DOCUMENT: Record test scenarios and load patterns for reproduction
BEFORE APPLYING: Read the reference for comparison templates and validation steps
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

Verify performance fix
Verify the performance
Verify the memory
Verify the threading
Verify the GC
Verify the profiling
Compare before and after profiling results
Performance benchmark
Check for performance regressions after refactoring

Workflow

Read verification reference and confirm baseline data

Read references/164-java-profiling-verify.md and verify baseline artifacts exist and are non-empty.

Generate post-refactoring profiling data

Run profiling with identical load/test conditions to produce comparable post-refactoring artifacts.

Compare before/after metrics and visuals

Perform quantitative comparisons for memory/CPU/GC/threading and side-by-side flamegraph analysis.

Document final verification outcome

Create comparison and final results reports with regressions, gains, and reproducible scenario details.

Reference

For detailed guidance, examples, and constraints, see references/164-java-profiling-verify.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/164-java-profiling-verify.md13 KB

Frequently asked questions

What does the 164 Java Profiling Verify AI skill do?

Why use 164 Java Profiling Verify on TypingMind?

Because you install it once and use it with any model. 164 Java Profiling Verify 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 164 Java Profiling Verify in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jabrena/plinth/tree/main/skills/164-java-profiling-verify. 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 164 Java Profiling Verify?

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 164 Java Profiling Verify?

As many as you like. As long as a model supports skills, you can use 164 Java Profiling Verify with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the 164 Java Profiling Verify 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.

View all

Autoreview

openclaw

OrganizationPopular

Structured code review when explicitly requested, preferring OpenAI/Codex before Claude.

Claw Score

Audit or refresh OpenClaw maturity scorecard docs from root taxonomy, maturity scores, and QA evidence artifacts without using maintainer discrawl data or committed inventory reports.

Clawsweeper

Use for all ClawSweeper work: OpenClaw issue/PR sweep reports, repair jobs, cloud fix PRs, @clawsweeper maintainer mention commands, trusted ClawSweeper-reviewed autofix/automerge, GitHub Actions…

Control Ui E2e

Use when designing, testing, fixing, or extending the OpenClaw Control UI GUI, including UI stress-test galleries with feedback inputs, Vitest + Playwright end-to-end checks, mocked Gateway flows,…

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Java Profiling Workflow / Step 4 / Verify results

Constraints

When to use this skill

Workflow

Reference

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now