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-regression-testinggit 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-regression-testing)<a href="https://agentmods.dev/skills/kokxi/qa-test-skills/qa-regression-testing"><img src="https://agentmods.dev/badge/skills/kokxi/qa-test-skills/qa-regression-testing.svg" alt="Measured on agentmods" 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 | $0.00128 | $0.03111 |
| Opus 5 | $0.00064 | $0.01555 |
| Sonnet 5 | $0.00026 | $0.00622 |
| Haiku 4.5 | $0.00013 | $0.00311 |
Grade A, and why
qa-regression-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 3d 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 — 290 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发布阻塞策略和回归用例分级。 实际使用时请勿直接阻塞发布,先与项目经理和开发确认风险等级和发布窗口。 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。
回归测试策略
无代码评审时的替代方案:如果
qa-code-review-for-test的输出不可用(代码评审不在本次工作流路径中),可直接根据用户提供的变更描述、版本 diff 或功能变更列表来确定变更影响范围和回归重点。上游依赖为可选,不阻塞工作流执行。
核心原则
回归不是全量重测,而是「判断哪些不用测」比「决定哪些要测」更重要。
回归金字塔
第1层:冒烟回归(P0 — 提交级)
定位:每次提交/部署必须通过的快速验证
执行频率:每次提交/构建
执行方式:自动化(CI/CD触发)
执行时间:< 15分钟
覆盖率:核心流程 100%
典型用例:
├─ 关键登录态验证
├─ 主页/核心页面可访问
├─ 核心API健康检查
├─ 数据库连接正常
用例特征:
├─ 数量少(< 50条)
├─ 执行快(秒级)
├─ 结果明确(通过/不通过)
└─ 失败即阻塞发布
第2层:核心回归(P0 + P1 — 日级)
定位:每日/每个迭代版本的关键功能验证
执行频率:每日/每次提测
执行方式:自动化为主 + 人工抽测
执行时间:< 2小时
覆盖率:核心功能 100% + 关联功能 80%
典型用例:
├─ 所有P0用例
├─ 关联功能的核心场景
├─ 历史缺陷的复测用例
├─ 变更影响区域的主路径
用例特征:
├─ 中等数量(100-500条)
├─ 覆盖核心链路
├─ 可自动化率 > 80%
└─ 失败需人工确认
第3层:全量回归(P0-P3 — 发版级)
定位:大版本发布前的全面验证
执行频率:每个大版本
执行方式:自动 + 人工结合
执行时间:1-5天
覆盖率:全功能覆盖 90%+
典型用例:
├─ 全量P0-P2用例
├─ 所有功能点的边界场景
├─ 兼容性覆盖组合
├─ 全链路性能验证
用例特征:
├─ 数量大(500+条)
├─ 覆盖全面
├─ 部分需人工执行(探索式)
└─ 结果用于发版决策
回归用例筛选策略
策略1:基于变更的筛选(Change-Based)
适用场景:小迭代 / Bugfix版本
核心逻辑:代码变更 = 需要回归的区域
执行步骤:
1. 获取代码变更列表(Diff / Commit)
2. 确定变更影响的模块和接口
3. 从用例库中提取覆盖这些模块的用例
4. 增加模块间调用链上的关联用例
5. 增加历史缺陷中同类变更的相关用例
适用条件:
├─ 有代码评审结果(qa-code-review-for-test)
├─ 用例与代码有映射关系
└─ 变更边界清晰
优点:精准、用例量少
缺点:依赖代码映射、可能遗漏间接影响
策略2:基于风险的筛选(Risk-Based)
适用场景:大版本 / 重构 / 新功能上线
核心逻辑:高风险区域 = 必须回归
执行步骤:
1. 引用风险评估结果(qa-risk-intuition)
2. 高风险区域 → 全量回归(P0-P2全覆盖)
3. 中风险区域 → 核心回归(P0-P1)
4. 低风险区域 → 冒烟回归(P0)
5. 历史缺陷高发模块 → 增加额外覆盖
适用条件:
├─ 有风险评估报告
├─ 用例库有优先级标注
└─ 回归时间有限
优点:时间弹性大、可裁剪
缺点:依赖风险判断的准确性
策略3:基于时间的筛选(Time-Boxed)
适用场景:回归时间严重不足 / 紧急发布
核心逻辑:时间限制 = 用例上限,按价值排序
执行步骤:
1. 计算可用回归时间
2. 按优先级倒序裁减:
├─ 先保冒烟(P0,必须过)
├─ 再保核心(P0+P1,尽量过)
└─ 最后全量(P0-P2,能过多少算多少)
3. 标记未覆盖的风险区域
4. 输出回归风险报告
优点:总能给出可执行的方案
缺点:覆盖率随裁剪下降,需显式暴露风险
策略比较速查
| 策略 | 适用场景 | 用例量 | 依赖 | 风险暴露 |
|---|---|---|---|---|
| 变更驱动 | 小迭代/Bugfix | 少 | 代码映射 | 低 |
| 风险驱动 | 大版本/重构 | 中 | 风险评估 | 中 |
| 时间驱动 | 紧急发布 | 灵活 | 时间预估 | 高(显式暴露) |
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.
- 3d ago Changed 3246f4fa8002
- 8d ago First seen · 290 lines · 128 tokens per session scan A 9248e4a2d0ff
qa-regression-testing is a skill published in the GitHub repository Kokxi/qa-test-skills (24 stars, last pushed 6d ago), licensed MIT. It adds 128 tokens to every session and 3,111 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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