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 kanfu-panda/pdlc-skills --skill pdlc-e2egit clone --depth 1 https://github.com/kanfu-panda/pdlc-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/kanfu-panda/pdlc-skills/pdlc-e2e)<a href="https://agentmods.dev/skills/kanfu-panda/pdlc-skills/pdlc-e2e"><img src="https://agentmods.dev/badge/skills/kanfu-panda/pdlc-skills/pdlc-e2e/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/kanfu-panda/pdlc-skills/pdlc-e2e"><img src="https://agentmods.dev/badge/skills/kanfu-panda/pdlc-skills/pdlc-e2e.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 | $0.00021 | $0.00533 |
| Opus 5 | $0.00010 | $0.00267 |
| Sonnet 5 | $0.00004 | $0.00107 |
| Haiku 4.5 | $0.00002 | $0.00053 |
Grade A, and why
pdlc-e2e 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 10d 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
端到端测试
编写端到端（E2E）测试用例，验证完整的用户操作流程。
工作流程
- 阅读需求文档: 阅读
docs/01_requirements/user-stories/下的用户故事和验收标准 - 阅读 UI 设计: 阅读
docs/02_design/ui-ux/下的 UI 设计文档 - 梳理测试场景: 按用户旅程梳理核心操作路径
- 编写测试计划: 在
docs/04_testing/e2e-tests/下补充 E2E 测试用例 - 编写测试代码: 使用项目对应的 E2E 框架编写自动化测试
- 运行验证: 确保测试可通过
测试场景设计
- 核心路径（P0）: 必须通过，如登录→主流程→结果验证
- 分支路径（P1）: 常见的备选操作路径
- 异常路径（P2）: 网络错误、超时、权限不足等异常场景
- 边界场景（P3）: 空数据、超长输入、并发操作
测试框架（根据前端技术栈）
- React/Vue/Next.js: Playwright 或 Cypress
- 微信小程序: miniprogram-automator
- API 层: 直接用 HTTP 请求库
要求
- 测试用例命名格式:
应该_当<条件>时_<预期行为> - 测试数据独立，不依赖其他测试的执行结果
- 每个测试结束后清理数据
测试目标: $ARGUMENTS
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.
- 10d ago First seen · 50 lines · 21 tokens per session scan A ee145955b0c8
pdlc-e2e is a skill published in the GitHub repository kanfu-panda/pdlc-skills (13 stars, last pushed yesterday), licensed MIT. It adds 21 tokens to every session and 533 once invoked, about $0.0001 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.
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