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-test-strategy-designgit 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-test-strategy-design)<a href="https://agentmods.dev/skills/kokxi/qa-test-skills/qa-test-strategy-design"><img src="https://agentmods.dev/badge/skills/kokxi/qa-test-skills/qa-test-strategy-design/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-test-strategy-design"><img src="https://agentmods.dev/badge/skills/kokxi/qa-test-skills/qa-test-strategy-design.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 | $0.00118 | $0.02242 |
| Opus 5 | $0.00059 | $0.01121 |
| Sonnet 5 | $0.00024 | $0.00448 |
| Haiku 4.5 | $0.00012 | $0.00224 |
Grade A, and why
qa-test-strategy-design 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 7d 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 — 240 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评估和 CI/CD 流水线的策略引用。 这些是策略参考不是直接操作；请勿未经授权即执行发布或变更流水线配置。 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。
测试策略制定
核心原则
根据项目特征（工期/复杂度/团队/风险）制定分层测试策略。
深度要求（参考值）
关键指标：根据项目复杂度调整策略深度
| 复杂度 | 策略要素要求 | 输出要求 | 说明 |
|---|---|---|---|
| 简单项目 | 至少覆盖4个要素 | 1-2页策略摘要 | 内部工具/低风险 |
| 中等项目 | 全部6个要素 | 3-5页策略文档 | 业务系统/中等风险 |
| 复杂项目 | 全部6个要素+风险评估 | 5-10页完整策略 | 核心系统/高风险 |
测试策略六要素
要素1：项目背景评估
评估维度：
├─ 项目阶段：新项目/迭代优化/维护阶段
├─ 团队规模：人员数量和经验水平
├─ 技术栈：技术复杂度和团队熟悉度
├─ 工期：开发周期和测试周期
└─ 历史质量：历史Bug密度和漏测率
评估结果：
- 项目阶段：[新项目/迭代/维护]
- 团队：[X人，经验水平]
- 技术栈：[复杂度]
- 工期：[X周]
- 历史质量：[Bug密度/漏测率]
要素2：风险分析
风险识别：
├─ 业务风险：核心功能/资金/安全
├─ 技术风险：新架构/复杂逻辑/第三方
├─ 进度风险：工期紧/人员不足
└─ 质量风险：历史问题多/复杂度高
风险等级：
- 高风险：必须深测
- 中风险：常规测试
- 低风险：冒烟测试
要素3：分层策略
测试金字塔：
┌─────────┐
│ E2E测试 │ 10%
├─────────┤
│ 接口测试 │ 30%
├─────────┤
│ 单元测试 │ 60%
└─────────┘
分层比例：
├─ 单元测试：60-70%（核心逻辑）
├─ 接口测试：20-30%（业务流程）
├─ E2E测试：10%（核心路径）
└─ 探索测试：补充（复杂场景）
要素4：手段选择
自动化 vs 手动：
├─ 自动化：回归测试/冒烟测试/数据驱动
├─ 手动：探索测试/用户体验/兼容性
└─ 工具辅助：性能测试/安全测试/接口测试
选择依据：
- 重复执行：自动化
- 复杂判断：手动
- 数据驱动：自动化
- 探索性：手动
要素5：资源分配
资源分配：
├─ 人力分配：测试人员角色和任务
├─ 时间分配：各阶段测试时间
├─ 环境分配：测试环境准备
└─ 工具分配：测试工具准备
时间分配：
- 需求分析：10%
- 用例设计：20%
- 测试执行：50%
- 回归测试：15%
- 报告总结：5%
要素6：准入准出标准
准入标准：
├─ 需求评审通过
├─ 开发自测通过
├─ 冒烟测试通过
├─ 测试环境就绪
└─ 测试数据准备
准出标准：
├─ 用例执行率 ≥ 95%
├─ 用例通过率 ≥ 90%
├─ 高严重度Bug修复率 = 100%
├─ 中严重度Bug修复率 ≥ 90%
└─ 无阻塞性Bug
策略输出模板
# 测试策略
## 1. 项目背景
- 项目阶段：[阶段]
- 团队：[规模和经验]
- 技术栈：[复杂度]
- 工期：[周期]
## 2. 风险分析
- 高风险区域：[列表]
- 中风险区域：[列表]
- 低风险区域：[列表]
## 3. 测试策略
- 单元测试：[比例和范围]
- 接口测试：[比例和范围]
- E2E测试：[比例和范围]
- 探索测试：[比例和范围]
## 4. 手段选择
- 自动化范围：[哪些需要自动化]
- 手动范围：[哪些需要手动]
- 工具选择：[使用什么工具]
## 5. 资源分配
- 人力：[分配方案]
- 时间：[时间节点]
- 环境：[环境准备]
- 工具：[工具准备]
## 6. 准入准出
- 准入标准：[标准列表]
- 准出标准：[标准列表]
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.
- 7d ago Changed 22c218178bf2
- 12d ago First seen · 240 lines · 118 tokens per session scan A 481f2d03542b
qa-test-strategy-design is a skill published in the GitHub repository Kokxi/qa-test-skills (27 stars, last pushed 10d ago), licensed MIT. It adds 118 tokens to every session and 2,242 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.
Other skills, from other repositories
sparc-methodology
SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration.
swarm-advanced
Advanced swarm orchestration patterns for research, development, testing, and complex distributed workflows.
code-review
Reviews Spec Kit code changes for positive and negative test coverage, regression evidence for bug fixes, and consistent repository terminology. Use when reviewing a diff or pull request. Do not use for implementing changes or posting GitHub review actions.
agent-harness-fault-injection
Use when an agent workflow needs deterministic recovery evidence for sandbox, MCP/tool, worker, checkpoint, memory, or orchestration failures.
octocode-benchmark
Use when planning, running, grading, or reporting the by-hand Octocode research benchmark — pairwise matchups (Octocode anchor vs one baseline: gh+RTK, gh+Headroom, or plain gh) over markdown questions, with a fresh isolated runner agent per (question, arm, pass), one blind judge per question grading two answers X/Y…
octocode-graph-eval
Use when you need a measurable keep/discard loop — goal→KPI, baseline vs target, held-out checks, eval suites, or don't-stop-till-done against a runnable sensor. Not for ordinary ship checks where 'tests passed' is enough.