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 bovinphang/frontend-craft --skill fec-e2e-testinggit clone --depth 1 https://github.com/bovinphang/frontend-craftWrote 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/bovinphang/frontend-craft/fec-e2e-testing)<a href="https://agentmods.dev/skills/bovinphang/frontend-craft/fec-e2e-testing"><img src="https://agentmods.dev/badge/skills/bovinphang/frontend-craft/fec-e2e-testing/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/bovinphang/frontend-craft/fec-e2e-testing"><img src="https://agentmods.dev/badge/skills/bovinphang/frontend-craft/fec-e2e-testing.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 | $0.00752 |
| Opus 5.5 | $0.00041 | $0.00301 |
| Sonnet 5.5 | $0.00021 | $0.00150 |
| Haiku 4.5 | $0.00010 | $0.00075 |
Grade A, and why
fec-e2e-testing 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
E2E 测试规范
用途
用真实浏览器验证关键用户旅程，发现单元测试无法覆盖的集成风险。
流程
- 明确关键旅程：登录、购买、创建、搜索、权限、支付等跨页面流程优先；若只是选择测试层级，先做测试分层规划。
- 新项目优先 Playwright；已有 Cypress 项目沿用 Cypress，不为迁移而迁移。
- 用 Page Object 或 fixtures 封装登录、页面定位器和共享数据，spec 中避免裸选择器。
- 断言用户可见结果，依赖 Locator 自动等待、网络响应或可见状态，不使用固定 sleep。
- CI 必须上传 HTML report、截图、trace 或视频；flaky 用例要隔离、复现、标注来源并关联 issue。
- 调试失败时先读 trace、console、network 和截图，再改测试；不要把真实产品缺陷误判成 flaky。
- 对关键浏览器能力、支付、权限、上传和实时通信流程，记录测试环境、种子数据和清理策略。
- 测试数据必须可重复：优先使用 API seed、数据库 fixture、测试账号或 mock 服务；随机数据需带唯一前缀并在 teardown 清理。
详细参考
- 需要目录结构、Page Object、spec 组织、配置、flaky 调试和产物示例时，加载 references/playwright-patterns.md。
- 需要 CI 示例和 Markdown 报告模板时，加载 references/e2e-ci-reporting.md。
- 需要 Web3/钱包流程或高风险金融流程时，加载 references/e2e-special-scenarios.md。
- 需要跨页面截图或视觉回归配置时，加载 references/e2e-visual-regression.md。
约束
- 禁止依赖
sleep/ 固定setTimeout作为主要同步手段。 - 不在生产环境跑真实 E2E。
- 避免在 E2E 中断言组件内部像素级样式；跨页面截图/视觉回归仅覆盖用户旅程中的关键页面状态。
- 失败必须能靠截图、trace 或视频定位。
- 组件内部契约测试分流到组件测试 workflow。
- 不把不稳定等待、随机数据或依赖测试顺序带入 CI。
- 不把重试次数当作 flaky 治理；重试只能保留证据，根因仍需定位。
预期输出
关键用户旅程有稳定 E2E 覆盖，失败产物可定位问题，CI 中报告和 trace 可下载；flaky 用例有复现命令、隔离策略和后续 issue。
What ships with it
4 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 First seen · 43 lines · 103 tokens per session scan A 577baf07e7da
fec-e2e-testing is a skill published in the GitHub repository bovinphang/frontend-craft (22 stars, last pushed 29d ago), licensed MIT. It adds 103 tokens to every session and 752 once invoked, about $0.0004 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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