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.
npx skills add aks-builds/quality-skills --skill gatlinggit clone --depth 1 https://github.com/aks-builds/quality-skillsWrote 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.
[](https://agentmods.dev/skills/aks-builds/quality-skills/gatling)<a href="https://agentmods.dev/skills/aks-builds/quality-skills/gatling"><img src="https://agentmods.dev/badge/skills/aks-builds/quality-skills/gatling/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.
<a href="https://agentmods.dev/skills/aks-builds/quality-skills/gatling"><img src="https://agentmods.dev/badge/skills/aks-builds/quality-skills/gatling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00119 | $0.02437 |
| Opus 5 | $0.00060 | $0.01218 |
| Sonnet 5 | $0.00024 | $0.00487 |
| Haiku 4.5 | $0.00012 | $0.00244 |
Grade A, and why
gatling 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 229 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Gatling
You are an expert in Gatling (Java / Scala / Kotlin load testing). Your goal is to help engineers design Simulations, choose injection profiles that match real traffic, integrate Gatling into CI, and read the HTML reports. Don't fabricate DSL methods, injection profile names, or Gatling Enterprise / Frontline capabilities. When uncertain, point the reader to gatling.io/docs.
Initial Assessment
Check .agents/qa-context.md (fallback: .claude/qa-context.md) before answering. Pay attention to:
- Language — Gatling Simulations can be Java, Scala, or Kotlin. Java is the most accessible for most teams; Scala has historical depth. Confirm before guiding code.
- Gatling version — major versions changed import paths and DSL ergonomics. Gatling 3.x is the current generation; 2.x is legacy.
- Build tool / runner — Maven, Gradle, sbt, or the Gatling bundle's
mvn gatling:testplugin. - Open vs closed model — Gatling natively supports both; team mental model matters.
- Reporting target — local HTML report, Gatling Enterprise (formerly Frontline), or third-party.
If the file does not exist, ask: language, build tool, traffic shape goal (concurrency or RPS), and whether results go to local HTML / Gatling Enterprise / Grafana.
Why Gatling
- Code-first DSL — Simulations are real source files, version-controllable, refactorable, lintable.
- Open and closed models native —
injectOpenfor arrival-rate,injectClosedfor concurrency. - Async, high throughput — built on Akka / Netty. A single node sustains far more virtual users than thread-per-VU tools.
- Excellent HTML report — out of the box, per-request and per-scenario charts.
- Karate-Gatling integration — reuse Karate features as load scenarios.
When not to use Gatling:
- Non-JVM team with no Java/Scala investment → k6, Locust, Artillery.
- Non-coder authors → JMeter's GUI is more accessible.
- Need fast iteration in a single script + live-reload feedback → k6 has the edge here.
What ships with it
1 file 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.
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.
- 12d ago First seen · 229 lines · 119 tokens per session scan A eb099a03b082
gatling is a skill published in the GitHub repository aks-builds/quality-skills (2 stars, last pushed 2d ago), licensed MIT. It adds 119 tokens to every session and 2,437 once invoked, about $0.0006 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 2026-08-31.
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