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 Kokxi/qa-test-skills --skill qa-scenario-treegit clone --depth 1 https://github.com/Kokxi/qa-test-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/kokxi/qa-test-skills/qa-scenario-tree)<a href="https://agentmods.dev/skills/kokxi/qa-test-skills/qa-scenario-tree"><img src="https://agentmods.dev/badge/skills/kokxi/qa-test-skills/qa-scenario-tree/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/kokxi/qa-test-skills/qa-scenario-tree"><img src="https://agentmods.dev/badge/skills/kokxi/qa-test-skills/qa-scenario-tree.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 | $0.00130 | $0.03017 |
| Opus 5 | $0.00065 | $0.01509 |
| Sonnet 5 | $0.00026 | $0.00603 |
| Haiku 4.5 | $0.00013 | $0.00302 |
Grade A, and why
qa-scenario-tree 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 5d 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 — 296 lines — stays where its author put it; the contents beside it link to each section on GitHub.
⚠️ 安全警告：本技能的示例可能涉及订单号、支付金额、截图、身份证、手机号等敏感数据。 实际使用时请勿粘贴真实生产数据、客户信息或财务凭证；测试前应脱敏/掩码处理。 本技能仅在 workspace/ 输出评估文件，不持久化、不外传、不跨会话复用。
场景树构建
核心原则
用树结构组织测试场景，确保覆盖完整、层次清晰。
场景数量要求（参考值）
关键指标：根据项目复杂度调整
| 复杂度 | 倍数 | 示例（显性5条） |
|---|---|---|
| 简单项目 | ×3 | 场景15个 |
| 中等项目 | ×5 | 场景25个 |
| 复杂项目 | ×7 | 场景35个 |
复杂度判断标准：
- 简单：单模块、低风险、无并发
- 中等：多模块、中风险、少量并发
- 复杂：跨模块、高风险、高并发
场景树结构
根节点：功能模块
├─ 主路径（Happy Path） → 数量：需求数量 × 1
│ ├─ 场景1：正常流程1
│ ├─ 场景2：正常流程2
│ └─ ...
├─ 分支路径（Alternative Path） → 数量：需求数量 × 2
│ ├─ 场景A：分支条件1
│ ├─ 场景B：分支条件2
│ └─ ...
├─ 异常路径（Exception Path） → 数量：需求数量 × 1.5
│ ├─ 场景X：异常情况1
│ ├─ 场景Y：异常情况2
│ └─ ...
└─ 数据流（Data Flow） → 数量：需求数量 × 0.5
├─ 场景α：数据创建
├─ 场景β：数据流转
└─ ...
场景类型覆盖清单
主路径场景
- 核心业务流程是否覆盖？
- 正常用户操作路径是否覆盖？
- 主要功能点是否覆盖？
分支路径场景
- 不同用户角色是否覆盖？
- 不同业务规则是否覆盖？
- 不同配置选项是否覆盖？
- 不同数据状态是否覆盖？
- 不同环境条件是否覆盖？
异常路径场景
- 输入异常是否覆盖？（空值/超长/格式错误）
- 状态异常是否覆盖？（非法状态转换）
- 网络异常是否覆盖？（断网/超时/延迟）
- 依赖异常是否覆盖？（第三方服务故障）
- 并发异常是否覆盖？（数据冲突/资源竞争）
- 资源异常是否覆盖？（内存不足/磁盘满）
数据流场景
- 数据创建是否覆盖？
- 数据读取是否覆盖？
- 数据更新是否覆盖？
- 数据删除是否覆盖？
- 数据同步是否覆盖？
- 数据一致性是否覆盖？
## 构建方法
### 第1步：识别主路径
**问**：用户从开始到结束，最正常的操作路径是什么？
主路径识别：
- 用户起点：用户从哪里开始？
- 核心步骤：必须执行的步骤有哪些？
- 用户终点：用户在哪里结束？
- 成功标志：怎么算完成？
示例（电商下单）： 用户浏览商品 → 加入购物车 → 选择地址 → 选择支付 → 确认支付 → 支付成功 → 生成订单
### 第2步：识别分支路径
**问**：在主路径的每一步，有什么条件分支？
分支识别方法：
- 条件判断：if-else条件是什么？
- 用户选择：用户有哪些选择？
- 状态分支：不同状态走不同路径？
- 配置分支：不同配置走不同路径？
示例（电商下单）：
- 选择地址：有地址/无地址/新增地址
- 选择支付：微信支付/支付宝/银行卡
- 使用优惠券：有/无/过期
### 第3步：识别异常路径
**问**：在每个步骤，可能出什么问题？怎么恢复？
异常识别方法：
- 输入异常：用户输入错误
- 系统异常：系统故障
- 网络异常：网络问题
- 依赖异常：第三方服务问题
- 并发异常：并发操作问题
示例（电商下单）：
- 加入购物车：库存不足
- 选择地址：地址不存在
- 支付：支付失败
- 支付：网络中断
### 第4步：识别数据流
**问**：数据在模块间怎么流转？在哪创建/更新/删除？
数据流识别：
- 数据创建：在哪里创建数据？
- 数据读取：在哪里读取数据？
- 数据更新：在哪里更新数据？
- 数据删除：在哪里删除数据？
- 数据一致性：数据在各模块间是否一致？
示例（电商下单）：
- 订单数据：创建订单 → 更新库存 → 生成支付单
- 用户数据：读取地址 → 使用优惠券 → 更新积分
## 场景描述模板
每个场景应包含：
```markdown
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.
- 5d ago Changed ebcade1187b9
- 11d ago First seen · 296 lines · 130 tokens per session scan A 16decd0eaf35
qa-scenario-tree is a skill published in the GitHub repository Kokxi/qa-test-skills (25 stars, last pushed 8d ago), licensed MIT. It adds 130 tokens to every session and 3,017 once invoked, about $0.0006 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 2026-08-30.
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