What is docker-jfr-benchmark-loop?

A repeatable Docker-based performance test for one RDF4J Java benchmark, with Java Flight Recorder collecting CPU-time data. Docker runs the test in an isolated container, while JFR records runtime activity.

Use it to run one JMH benchmark repeatedly, investigate performance bottlenecks, and profile benchmark runs with JFR.

It makes baseline-versus-change comparisons more consistent and helps show which methods use the most CPU.

How eclipse-rdf4j/rdf4j configures Codex

Reuse

Borrowing it

Nothing to install: this file belongs to eclipse-rdf4j/rdf4j. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/eclipse-rdf4j/rdf4j/main/.agent/skills/docker-jfr-benchmark-loop/SKILL.md

Clone the repo

git clone --depth 1 https://github.com/eclipse-rdf4j/rdf4j

Made for: 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/eclipse-rdf4j/rdf4j/docker-jfr-benchmark-loop/github.svg)](https://agentmods.dev/skills/eclipse-rdf4j/rdf4j/docker-jfr-benchmark-loop)

Your own site

<a href="https://agentmods.dev/skills/eclipse-rdf4j/rdf4j/docker-jfr-benchmark-loop"><img src="https://agentmods.dev/badge/skills/eclipse-rdf4j/rdf4j/docker-jfr-benchmark-loop/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/eclipse-rdf4j/rdf4j/docker-jfr-benchmark-loop"><img src="https://agentmods.dev/badge/skills/eclipse-rdf4j/rdf4j/docker-jfr-benchmark-loop.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 101 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 949 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. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

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	$0.00101	$0.00949
Opus 5	$0.00051	$0.00475
Sonnet 5	$0.00020	$0.00190
Haiku 4.5	$0.00010	$0.00095

Measured 7d ago against content hash c754aa35b705, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

docker-jfr-benchmark-loop 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 7d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/run-docker-jfr-loop.sh), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

.agent/skills/docker-jfr-benchmark-loop/SKILL.md · 91 lines

How it starts

The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Docker JFR Benchmark Loop

Use this skill for one-benchmark perf work in this repo. Default runner: scripts/run-docker-jfr-loop.sh, not ad hoc Maven or raw JMH commands.

Quick start

Dry-run a known selector:

.codex/skills/docker-jfr-benchmark-loop/scripts/run-docker-jfr-loop.sh \
  org.eclipse.rdf4j.model.benchmark.ValueCreationBenchmark.createBNode \
  --dry-run

Explicit selector plus params:

.codex/skills/docker-jfr-benchmark-loop/scripts/run-docker-jfr-loop.sh \
  --module core/model \
  --class org.eclipse.rdf4j.model.benchmark.ValueCreationBenchmark \
  --method createBNode \
  --param samples=1000

Repo-grounded defaults

The wrapper calls repo helper scripts/run-single-benchmark-docker.sh.
The Docker helper already forces Linux Java 26 plus --enable-jfr --enable-jfr-cpu-times.
The inner helper already enforces:
- settings=profile
- dumponexit=true
- duration=120s
- warmup=0
- measurement=10 iterations of 10s
- forks=1
- jdk.CPUTimeSample#enabled=true
- report-on-exit=cpu-time-hot-methods
This skill wrapper adds the missing fidelity flags:
- -XX:FlightRecorderOptions=stackdepth=1024,samplethreads=true
- -XX:+UnlockDiagnosticVMOptions
- -XX:+DebugNonSafepoints

Core loop

Pick one benchmark selector. Keep selector, params, Docker image, and profiling flags constant for the whole comparison.
Capture a baseline run with scripts/run-docker-jfr-loop.sh.
Read the .jfr using references/jfr-reading.md.
Choose one candidate fix with material CPU share. Prefer the fix most likely to move total runtime, not just local self time.
Re-run the exact same selector and params.
Compare benchmark delta plus hotspot shift.
Repeat until:
- the hotspot shifts,
- CPU share falls below a meaningful threshold,
- or GC / locks / memory / I/O / JIT behavior dominates instead.

Operating rules

Route benchmark variation through --param.
Route JVM tuning through --jvm-arg.
Do not use raw --jmh-arg during JFR runs; the helper rejects extra JMH args when JFR is enabled.
Do not switch to a second StartFlightRecording; stay aligned with repo helper behavior.
Do not treat a small benchmark gain as proof the hotspot fix failed. First check whether another bottleneck surfaced and now caps the total speedup.
If the run is not CPU-bound, say so and pivot to lock, GC, memory, I/O, or JIT evidence instead of forcing a CPU-only story.

Read the full file on GitHub · 91 lines

Files

What ships with it

4 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.

7d ago First seen · 91 lines · 101 tokens per session scan A c754aa35b705

Subscribe to this mod's changes

docker-jfr-benchmark-loop is a skill published in the GitHub repository eclipse-rdf4j/rdf4j (412 stars, last pushed yesterday), licensed BSD-3-Clause. It adds 101 tokens to every session and 949 once invoked, about $0.0005 per session on Opus 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 2026-09-03.

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rdf4j: Skill for Codex