A Java microbenchmarking skill built around JMH, the Java Microbenchmark Harness. It guides the setup of benchmarks so compiler optimizations, warmup, and JVM behavior do not distort timing results.

It is for measuring Java throughput, execution time, startup paths, and timing distributions with Maven or Gradle projects.

It reduces the risk of believing misleading performance numbers caused by dead-code removal, constant folding, insufficient warmup, or contaminated runs.

jmh — Skill for Claude Code and Codex by umit/skills

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add umit/skills --skill jmh

Clone the repo

git clone --depth 1 https://github.com/umit/skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/umit/skills/jmh/github.svg)](https://agentmods.dev/skills/umit/skills/jmh)

Your own site

<a href="https://agentmods.dev/skills/umit/skills/jmh"><img src="https://agentmods.dev/badge/skills/umit/skills/jmh/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/umit/skills/jmh"><img src="https://agentmods.dev/badge/skills/umit/skills/jmh.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 273 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,429 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00273	$0.01429
Opus 5.5	$0.00109	$0.00572
Sonnet 5.5	$0.00055	$0.00286
Haiku 4.5	$0.00027	$0.00143

Measured 1mo ago against content hash 6b1f64d9e1ce, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

jmh scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/jmh/SKILL.md · 64 lines

How it starts

The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.

JMH — trustworthy Java microbenchmarks

Workflow

Pre-flight before running — read references/pitfalls.md and apply its 15-point checklist to the benchmark source. Catch DCE, constant folding, missing Blackhole, @Fork(0), @Warmup < 5, final constants in the op, missing @State, raw loops without @OperationsPerInvocation. Most "fast" results come from broken benchmarks; catching this before running saves hours.
Identify the build system — Maven (pom.xml with jmh-core) or Gradle (me.champeau.jmh plugin). Setup differs; running differs. See references/maven.md or references/gradle.md.
Pick the right Mode — Throughput for ops/sec, AverageTime for ns/op, SingleShotTime for cold-path / startup, SampleTime for distribution (p50/p99). Wrong mode → wrong question answered. See references/modes.md.
Write the benchmark — annotate class with @State(Scope.Benchmark), @BenchmarkMode, @OutputTimeUnit, @Fork(value=3, jvmArgs={"-Xmx2g","-Xms2g"}), @Warmup(iterations=5), @Measurement(iterations=10). Every @Benchmark method either returns a value or takes a Blackhole parameter. Use @Param for matrices instead of separate methods.
Re-check the source against the checklist after edits.
Run with profilers attached — never run benchmarks without -prof gc (allocation rate context) and ideally -prof async:output=flamegraph (flame graph per benchmark). See references/profilers.md.
Output JSON (-rf json -rff results.json) — never trust the console table alone; JSON is what diffing and visualization tools consume.
Analyze — drag results.json to https://jmh.morethan.io for charts, or use Bencher/Codspeed in CI for continuous diff. See references/analysis.md.
Report with confidence intervals — JMH prints Score ± Error (99.9%). Two means are not different if their confidence intervals overlap. Don't claim "10% faster" inside the noise band.

Quick reference

Read the full file on GitHub · 64 lines

Files

What ships with it

7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

1mo ago First seen · 64 lines · 273 tokens per session scan A 6b1f64d9e1ce

Subscribe to this mod's changes

jmh is a skill published in the GitHub repository umit/skills (6 stars, last pushed 5mo ago), licensed MIT. It adds 273 tokens to every session and 1,429 once invoked, about $0.0011 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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