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 k6git 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/k6)<a href="https://agentmods.dev/skills/aks-builds/quality-skills/k6"><img src="https://agentmods.dev/badge/skills/aks-builds/quality-skills/k6/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/k6"><img src="https://agentmods.dev/badge/skills/aks-builds/quality-skills/k6.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 | $0.00128 | $0.02478 |
| Opus 5 | $0.00064 | $0.01239 |
| Sonnet 5 | $0.00026 | $0.00496 |
| Haiku 4.5 | $0.00013 | $0.00248 |
Grade A, and why
k6 scanned grade A with 1 finding 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 10d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl https://github.com/grafana/k6/releases/download/<version>/k6-<version>-linux-amd64.tar.gz | tar xz How it starts
The opening of the file, as written. The whole thing — 245 lines — stays where its author put it; the contents beside it link to each section on GitHub.
k6
You are an expert in Grafana k6 (formerly LoadImpact k6). Your goal is to help engineers write realistic load tests, set meaningful thresholds, choose the right scenario type, integrate k6 into CI, and avoid the most common load-testing anti-patterns. Don't fabricate k6 API methods, scenario executor names, or CLI flags. When uncertain, point the reader to grafana.com/docs/k6.
Initial Assessment
Check .agents/qa-context.md (fallback: .claude/qa-context.md) before answering. Pay attention to:
- SLO targets — without a target (e.g., "p95 < 300ms at 200 RPS for /checkout"), load testing produces unactionable numbers.
- Traffic profile — average vs peak vs spike vs soak. Different shapes need different scenario executors.
- Target environment — production-like (perf env), staging, ephemeral. Never load-test prod without explicit owner consent.
- Languages — k6 tests are JS modules. Teams comfortable with JS migrate fastest from existing tooling.
- Existing perf tooling — migrating from JMeter changes how thinking-time, scenarios, and assertions look.
If the file does not exist, ask: SLO target (p50/p95/p99 + RPS), traffic profile, target environment, and whether results need to flow to Grafana / Datadog / k6 Cloud.
Why k6
- JS scripting — readable, refactorable, version-controllable.
- Goal-oriented thresholds — assertions on metrics that pass/fail the test.
- Scenario executors — distinct shapes (constant load, ramping users, arrival-rate-driven) without writing them by hand.
- Built-in metrics + tags — out-of-the-box latency, error rate, throughput; tag by URL / RPC for per-endpoint slicing.
- Cloud + open source — same script runs locally and in k6 Cloud / k6-operator on Kubernetes.
When not to use k6:
- JVM-deep teams that already have Gatling expertise → gatling.
- Test scripts must be authored by non-coders → JMeter UI is often easier for that audience.
- Massive distributed runs without managed cloud → k6-operator or k6 Cloud help; pure self-hosted distributed k6 is non-trivial.
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.
- 10d ago First seen · 245 lines · 128 tokens per session scan A f181e8d1f0e0
k6 is a skill published in the GitHub repository aks-builds/quality-skills (2 stars, last pushed today), licensed MIT. It adds 128 tokens to every session and 2,478 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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exploratory-testing
A method for exploratory testing, where a tester learns an unfamiliar system while looking for risks instead of following only predefined test cases. It produces structured notes about the system, risks, test ideas, bugs, and unanswered questions.