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 fpindej/netrock --skill verifygit clone --depth 1 https://github.com/fpindej/netrockWrote 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/fpindej/netrock/verify)<a href="https://agentmods.dev/skills/fpindej/netrock/verify"><img src="https://agentmods.dev/badge/skills/fpindej/netrock/verify/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/fpindej/netrock/verify"><img src="https://agentmods.dev/badge/skills/fpindej/netrock/verify.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00016 | $0.00189 |
| Opus 5.5 | $0.00006 | $0.00076 |
| Sonnet 5.5 | $0.00003 | $0.00038 |
| Haiku 4.5 | $0.00002 | $0.00019 |
Grade A, and why
verify 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 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.
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.
What it actually says
/verify
Run the full post-change verification pipeline. Report the result of each step. If any step fails, stop and show the errors.
Backend (run when src/backend/ changed)
dotnet build src/backend/MyProject.slnx && dotnet test src/backend/MyProject.slnx -c Release
Frontend (run when src/frontend/ changed)
cd src/frontend && pnpm run test && pnpm run format && pnpm run lint && pnpm run check
If unsure which stack changed, run both. Fix all failures before reporting success.
For UI-visible changes, static checks are not enough: also verify in a real browser (/polish-ui step 5 describes the breakpoint/theme sweep).
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 First seen · 25 lines · 16 tokens per session scan A 3db503553c07
verify is a skill published in the GitHub repository fpindej/netrock (234 stars, last pushed 3d ago), licensed MIT. It adds 16 tokens to every session and 189 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
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Use when running mutation testing, killing mutants, verifying test quality, checking mutation score, or analyzing survivors after the test baseline is green.
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Use when writing tests from the outside-in, defining behavior before code, or any feature where tests should start from observable business behavior and let internal design emerge.
gherkin-gate
Use before writing any test or implementation task, when observable behavior needs to be captured in business language scenarios and approved by the user before code begins.