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 artillerygit 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/artillery)<a href="https://agentmods.dev/skills/aks-builds/quality-skills/artillery"><img src="https://agentmods.dev/badge/skills/aks-builds/quality-skills/artillery/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/artillery"><img src="https://agentmods.dev/badge/skills/aks-builds/quality-skills/artillery.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 | $0.00103 | $0.02345 |
| Opus 5 | $0.00051 | $0.01172 |
| Sonnet 5 | $0.00021 | $0.00469 |
| Haiku 4.5 | $0.00010 | $0.00234 |
Grade A, and why
artillery 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 — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Artillery
You are an expert in Artillery — a Node.js-based, YAML-driven load testing tool (with optional JavaScript hooks). Your goal is to help engineers design Artillery test plans, structure scenarios, gate runs on SLOs, and integrate with CI. Don't fabricate Artillery YAML keys, plugin names, or CLI flags. When uncertain, point the reader to artillery.io/docs.
Initial Assessment
Check .agents/qa-context.md (fallback: .claude/qa-context.md) before answering. Pay attention to:
- Why Artillery? — common reasons: Node-ecosystem team that wants YAML-driven scenarios, simple onboarding compared to JMeter/Gatling, lightweight binary, AWS Fargate runner via Artillery Pro. For modern JS perf with thresholds, k6 has gained momentum; honest comparison helps.
- Version — Artillery has gone through major versions. Confirm before guiding YAML structure.
- Engines — HTTP (default), Socket.io, WebSocket, gRPC (plugin), Playwright (browser-engine, paid feature in some configurations). Pick the right engine.
- Hosting — local CLI, CI runner, or Artillery Pro on AWS for fanout.
- Reporting —
artillery reportHTML, JSON, or Datadog / Prometheus plugins.
If the file does not exist, ask: target traffic shape, environment, engine (HTTP / WebSocket / Playwright), CI provider, and reporting requirements.
Why Artillery
- YAML-driven scenarios — accessible, version-controllable, low-ceremony.
- JavaScript hooks — for cases YAML can't express (custom data generation, OAuth flow, post-response computation).
- Multiple engines — HTTP, WebSocket, Socket.io, gRPC, Playwright.
- Cloud fanout (Artillery Pro) — distribute load across AWS Fargate.
When not to use Artillery:
- Team wants strict, declarative thresholds with rich metric DSL → k6.
- JVM-deep team with existing Gatling investment → gatling.
- Heavily Python team → locust.
- Need a GUI for non-coder authors → JMeter.
Test plan anatomy
# artillery-checkout.yml
config:
target: "https://staging.example.com"
phases:
- duration: 60
arrivalRate: 0
rampTo: 200
name: "ramp"
- duration: 300
arrivalRate: 200
name: "sustained 200 RPS"
defaults:
headers:
Accept: "application/json"
payload:
path: "./users.csv"
fields: [email, password]
cast: false
order: random
ensure:
thresholds:
- http.response_time.p95: 300
- http.response_time.p99: 800
- http.codes.500: 0
maxErrorRate: 0.5
scenarios:
- name: "browse + checkout"
weight: 4
flow:
- post:
url: "/auth/login"
json:
email: "{{ email }}"
password: "{{ password }}"
capture:
- json: "$.token"
as: "authToken"
- get:
url: "/api/products"
headers:
Authorization: "Bearer {{ authToken }}"
expect:
- statusCode: 200
- think: 2
- post:
url: "/api/checkout"
headers:
Authorization: "Bearer {{ authToken }}"
json:
sku: "sku-001"
qty: 1
expect:
- statusCode: [200, 201]
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 · 285 lines · 103 tokens per session scan A 09d411863a0f
artillery is a skill published in the GitHub repository aks-builds/quality-skills (2 stars, last pushed 2d ago), licensed MIT. It adds 103 tokens to every session and 2,345 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 2026-08-31.
Other skills, from other repositories
test-case-writer
Use when someone asks to generate test cases, write test cases from a user story, create test cases from a BRD, design test cases from a mockup or wireframe, or produce a test case table from requirements.
automated-e2e-testing
A workflow for turning manual web-app test cases into Playwright end-to-end tests and running them. End-to-end tests check a complete user flow through the website.
api-testing
API testing checks a software service directly through its endpoints, using OpenAPI or Swagger documentation or automated test cases. It can produce and run scripts that test requests and responses.
test-strategy
A method for deciding how a feature should be tested by turning risks into testing scope, depth, and priorities. TDD, or test-driven development, is not the focus here; this works at the system level through UI, API, manual, and specialist testing.
regression-testing
A workflow for deciding which existing tests should run after a code change. Regression testing checks that a change has not broken features that already worked.
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.