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 byerlikaya/claude-starter-kit --skill sonarqube-checkgit clone --depth 1 https://github.com/byerlikaya/claude-starter-kitWrote 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/byerlikaya/claude-starter-kit/sonarqube-check)<a href="https://agentmods.dev/skills/byerlikaya/claude-starter-kit/sonarqube-check"><img src="https://agentmods.dev/badge/skills/byerlikaya/claude-starter-kit/sonarqube-check/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/byerlikaya/claude-starter-kit/sonarqube-check"><img src="https://agentmods.dev/badge/skills/byerlikaya/claude-starter-kit/sonarqube-check.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Prompt Injection · line 10 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- medium MCP Rug Pull · line 39 Docker image references without a specific tag (:latest is implicit) or digest (@sha256:...) can be silently replaced by a malicious image.Fix: Pin the image: image:tag or image@sha256:abc123
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 | $0.00064 | $0.01862 |
| Opus 5.5 | $0.00026 | $0.00745 |
| Sonnet 5.5 | $0.00013 | $0.00372 |
| Haiku 4.5 | $0.00006 | $0.00186 |
Grade A, and why
sonarqube-check scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -sfu "$T:" "$S/api/qualitygates/project_status?projectKey=$K" # pass / fail, and which condition failed How it starts
The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SonarQube quality gate — produce the real report, locally
Trigger phrases: "sonarqube", "quality gate", "code smell", "sonar scan", "sonar rapor", "A rating"
Only a SonarQube analysis can say "rating A, 0 findings". A clean build says the compiler was happy — a
different claim, about a different rule set. Passing one off as the other is how a team is told the code is clean
and then opens a report full of findings.
You do not need a company server or someone else's token to get the real thing: SonarQube Community Build is free, needs no licence key, and runs in one Docker container on this machine. That is the default path here — the gate is produced locally, offline, and it is a genuine SonarQube verdict, not a proxy for one.
Language-agnostic on purpose: SonarQube covers 20+ languages plus IaC (Terraform, Kubernetes, Dockerfile). Detect what the project actually uses; never assume a stack.
Step 1 — get a real analysis (pick the first that applies)
a) The project already has a SonarQube → use it, and skip to step 2.
b) It does not → stand one up locally. Docker one-liner, the Docker-free server zip, the first login and the
token: references/stand-up-server.md. No licence, no external account, nothing leaves the machine.
Restarting is not installing. Bringing an already-approved service back up on this machine — the same image, the same volumes — is resuming what the user already said yes to, and this skill's own advice to keep a named volume assumes exactly that. A NEW image, a new volume, or a tool this machine does not have is an install, and needs the answer below.
Nothing here is installed without the user saying so. Docker, Java, a scanner, a linter — each is a proposal with its cost stated, and the user picks. If they decline all of them, that is a valid answer: go to (c) and report "unverified" rather than installing anything to make a number appear.
What ships with it
2 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.
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 Changed · -45 lines df2d5effac0c
- 1mo ago Changed · +5 lines 3d491e8d020f
- 1mo ago First seen · 151 lines · 64 tokens per session scan A 07af97659d88
sonarqube-check is a skill published in the GitHub repository byerlikaya/claude-starter-kit (24 stars, last pushed 1mo ago), licensed MIT. It adds 64 tokens to every session and 1,862 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-30.
Other skills, from other repositories
oracle
Oracle second-model review: bundle prompts/files, debug, refactor, design.
pr-review
Review open PRs two ways - default is a per-PR deep review with severity-tagged findings, inline comments, and a verdict; --survey runs a risk-tiered triage digest of what's safe to merge first.
feedback-builder
Point Aeon at a service's /feedback endpoint - pull what agents reported (bugs, missing features), triage and cluster it, then build the best accepted request as a PR for a human to approve.
pr-triage
First-touch triage for external pull requests - verdict, label, and a welcoming comment within minutes of open.
[REPLACE: SKILL_NAME]
First-touch review of newly opened PRs on [REPLACE: WATCHEDREPO] — verdict + welcoming comment + label.
no-mistakes
Validate committed feature-branch changes through the no-mistakes pipeline: intent, rebase, review, test, docs, lint, push, PR, and CI. Use when the user asks to run no-mistakes, ship safely, validate before pushing, or gate a change before it reaches upstream.