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 whitebeardit/.cursor --skill skill-qa-code-reviewgit clone --depth 1 https://github.com/whitebeardit/.cursorWrote 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/whitebeardit/.cursor/skill-qa-code-review)<a href="https://agentmods.dev/skills/whitebeardit/.cursor/skill-qa-code-review"><img src="https://agentmods.dev/badge/skills/whitebeardit/.cursor/skill-qa-code-review/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/whitebeardit/.cursor/skill-qa-code-review"><img src="https://agentmods.dev/badge/skills/whitebeardit/.cursor/skill-qa-code-review.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 | $0.00061 | $0.00914 |
| Opus 5.5 | $0.00024 | $0.00366 |
| Sonnet 5.5 | $0.00012 | $0.00183 |
| Haiku 4.5 | $0.00006 | $0.00091 |
Grade A, and why
qa-code-review 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.
How it starts
The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
QA Code Review
This skill defines how to review QA Playwright code (specs, test-data, fixtures) by considering the perspective of each QA subagent, then consolidating their concerns into one report focused on manutenção, qualidade e padronização.
When to Use
- User asks for a code review of specs, test-data, or flow.
- User asks "o que acha do código?" or "revise esse teste".
- User wants a consolidated improvement list from the point of view of the project's QA standards.
Process
- Identify scope: What is under review? (single spec, whole flow, test-data, fixtures.)
- Apply each relevant QA perspective by reading and applying the criteria from:
- Conventions (maintain): skill-qa-playwright-maintain-conventions — imports, test-data usage, structure, locators.
- Fixtures (add-fixture): skill-qa-playwright-add-fixture — whether fixtures would reduce duplication or improve structure.
- Flow (add-flow): skill-qa-playwright-add-new-flow — when reviewing a flow: folders, inputs, baseURL, naming.
- Optionally consider:
- Test-data: skill-qa-playwright-add-test-data — if the review involves inputs.json, builder.ts.
- Frontend-friendly: skill-frontend-qa-friendly — locators, accessibility, stability.
- Produce a single report with the structure below.
Output Structure
Produce the review in this order:
1. Manutenção (conventions)
- Checklist from maintain skill: imports from fixtures, test-data vs hardcode, directory structure, baseURL.
- Explicit: ✅ atende / ⚠️ atenção / ❌ não atende, with short reason.
2. Qualidade
- Locators: resilient (getByRole, getByLabel, getByText) vs brittle (XPath por posição, classes).
- Assertions: web-first, timeouts adequados, critérios de sucesso claros.
- Legibilidade: Arrange–Act–Assert, comentários úteis, nome do teste descritivo.
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 · 64 lines · 61 tokens per session scan A 94308a243a74
qa-code-review is a skill published in the GitHub repository whitebeardit/.cursor (12 stars, last pushed 7mo ago), licensed MIT. It adds 61 tokens to every session and 914 once invoked, about $0.0002 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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