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Testability Analysis

Community
naodeng
testability-analysis

Use this skill when you need to assess whether a requirement or design can be efficiently and reliably tested; triggers include 可测试性分析 and testability analysis.

Overview

Publishernaodeng
Repositoryawesome-qa-skills
Skill nametestability-analysis
Stars
279
Forks
36
Bundled files
13
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 13 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by naodeng on GitHub. Read the source before you install it.

Installation

Install the Testability Analysis AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/naodeng/awesome-qa-skills/tree/main/evidence/skill-quality/2026-10-03-codex-pilot/reproduction/packages/testability-analysis-zh
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/naodeng/awesome-qa-skills.git /tmp/awesome-qa-skills
mkdir -p .claude/skills
cp -r /tmp/awesome-qa-skills/evidence/skill-quality/2026-10-03-codex-pilot/reproduction/packages/testability-analysis-zh .claude/skills/testability-analysis
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Testability Analysis in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Testability Analysis on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Testability Analysis is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

可测试性分析(中文版)

何时使用

  • 需要评估需求与系统在可控制、可观察、可隔离和可复现方面的测试准备度。
  • 需要对现有方案、结果或证据做风险评审,并形成可执行改进项。
  • 输入不完整,但仍需先给出带假设和信息缺口的可用初版。

输出格式选项

  • 默认输出 Markdown,适合评审、执行和持续补充。
  • 用户要求表格、CSV、JSON 或工单格式时,保留同样的风险、证据、优先级和边界字段。
  • 若输出会进入自动化流程,先确认字段 schema、枚举值和必填项。

如何使用

  1. 先阅读并遵循 prompts/testability-analysis.md 的输入、执行规则、最低覆盖清单和输出顺序。
  2. 补充真正影响判断的范围、环境、版本、限制、证据和成功标准。
  3. 先做输入审计,再区分已确认事实、合理假设和待确认问题。
  4. 当任务要求 architecture-testability-review 或 architecture 模式时,先从架构制品、依赖拓扑、异步边界、测试接缝、替身策略、故障注入入口和环境复现分析,再保留通用可测试性维度。
  5. 按风险和证据强度排序,产出可直接执行、评审或验证的结果。
  6. 信息不足时不要停在提问:先交付受限初版,并说明哪些结论暂不能成立。

参考文件

  • 每次执行必须读取 prompts/testability-analysis.md;它是本 Skill 的完整执行规范。
  • 需要评测或回归本 Skill 时,读取 evals/eval.yaml 与匹配的 evals/cases/ 用例。
  • 只有目录实际存在且任务需要时,才读取 references/、examples/、scripts/ 或 output-formats.md,不要假设不存在的资产。
  • 需要回归 architecture-testability-review 时使用 architecture-* Eval 和本地触发数据;仍复用本 Skill 的物理目录,不创建别名目录。

核心约束

  • 不要把测试框架选择当测试性本身
  • 每项改进说明价值和成本
  • 避免为测试暴露不安全后门
  • architecture 模式必须用架构级来源支撑接缝、替身、隔离和故障注入判断;不把框架名称当作可测试性证据。
  • 不编造输入中不存在的系统行为、字段、数据、指标或根因。
  • 关键结论必须关联证据;证据不足时标记为假设并给出验证方法。
  • 优先级必须说明业务影响、发生可能性或可探测性依据。

交付前自检

  • 已覆盖:可观察性、可控制性、隔离、确定性、数据准备、故障注入、环境一致、自动化接口。
  • 已区分事实、假设、缺口和建议。
  • 高风险项有明确优先级、证据、负责人或下一步。
  • 输出包含可验证的判断标准,而非泛泛而谈。
  • 未执行未经授权的生产写操作或破坏性动作。

常见误区

  • 只列检查点,不说明输入条件、预期结果或证据。
  • 把所有事项都标为高优先级,失去取舍价值。
  • 用工具名或通用理论替代领域判断。
  • 输入不完整时直接拒绝,或反过来假装结论已经确定。

最佳实践

  • 从最可能造成业务损失、安全问题或发布阻塞的路径开始。
  • 用最小可验证实验缩小不确定性,并记录复现条件。
  • 让输出能够被另一位工程师直接执行和复核。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Testability Analysis AI skill do?

Use this skill when you need to assess whether a requirement or design can be efficiently and reliably tested; triggers include 可测试性分析 and testability analysis.

Why use Testability Analysis on TypingMind?

Because you install it once and use it with any model. Testability Analysis is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Testability Analysis in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/naodeng/awesome-qa-skills/tree/main/evidence/skill-quality/2026-10-03-codex-pilot/reproduction/packages/testability-analysis-zh. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Testability Analysis?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Testability Analysis?

As many as you like. As long as a model supports skills, you can use Testability Analysis with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Testability Analysis AI skill free?

It is published on GitHub by naodeng. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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