Automation Testing

Community

naodeng

automation-testing

Use this skill when you need to design automation testing approaches using patterns like POM, data-driven testing, or BDD; triggers include automation testing and test automation strategy.

Overview

Publisher	naodeng
Repository	`awesome-qa-skills`
Skill name	`automation-testing`
Stars	279
Forks	36
Bundled files	37
Links	Skill source Repository Homepage

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.
37 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 Automation Testing AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/naodeng/awesome-qa-skills/tree/main/skills/en/testing-types/automation-testing
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/naodeng/awesome-qa-skills/tree/main/skills/en/testing-types/automation-testing

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/skills/en/testing-types/automation-testing .claude/skills/automation-testing

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Automation Testing 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 Automation Testing 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 Automation Testing 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.

Automation Testing (English)

Chinese version： See the corresponding Chinese skill.

When to Use

Need help with automation testing in a real project context.
Need an output that can be used directly for execution, review, or follow-up.

Workflow

Read and follow the main prompt listed under Progressive disclosure (coverage, structure, quality bar).
Add only project context that changes the result: scope, environment, constraints, risks, dependencies, expected deliverable.
If input is incomplete, return a usable first draft and explicitly mark assumptions and gaps.
Default to Markdown; switch formats only when the user asks.

Domain Execution Essentials

Select using candidate flow | protection obligation | repeat-frequency evidence | oracle/observability | isolation/cleanup | stability | maintenance constraint | adopt/defer rationale. Keep ROI cost scenarios separate; returns cannot remedy missing oracles or authority.
Reuse the existing framework. First require observable postconditions, independent data, and a CI entry that propagates failure. Defer unmet candidates with unblock conditions.
Specify unique identities/business keys, setup, actions, business postconditions, failure signal, and teardown. Failed assertions must fail runner/CI, not merely log.
Separate candidate selection, generated assets, real runs, and business acceptance. Rapidly changing prototypes or non-isolatable real payments may need Human/controlled verification, with evidence-based tradeoffs.

Core Constraints

Prioritize by risk / business impact — do not treat everything equally.
Separate confirmed facts from current assumptions.
Do not invent endpoints, fields, environments, or root causes the user did not provide.
Keep output executable: concrete scenarios, clear priority, clear next steps.

Progressive Disclosure

When calibrating domain outcomes, valid controls, or evidence gaps, read references/domain-decision-example.md for sanitized input, per-item oracles, and reproducible calculations.
Before producing output, read and follow prompts/automation-testing.md (minimum coverage, output structure, quality bar).
When Excel/CSV/JSON/Word is requested: read output-formats.md and honor the format.
When a ready-made template fits: use matching files under output-templates/.
For deep framework/troubleshoot/schema notes: read only the relevant file(s) under references/, do not load the whole directory.
For format conversion or helper checks: prefer existing scripts/ over reinventing.
For evaluating/regressing this skill: use evals/ with skill-up.

Pre-delivery Checklist

Followed the main prompt's output structure
Minimum coverage focus: scope and objective, automation candidates, manual-only areas, priority by risk and ROI, framework alignment, data and environment needs, flaky-test risks, CI or execution strategy, ... (details in main prompt)
Covered the minimum checklist, or explained omissions
High-risk items have explicit priority
Did not invent details the user did not provide
Assumptions and gaps are marked

Common Pitfalls

Do not pretend completeness when scope/context is missing.
Do not treat every item as equally important.
Do not skip assumptions and information gaps.
Do not dump generic theory unrelated to the current toolchain.

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 Automation Testing AI skill do?

Use this skill when you need to design automation testing approaches using patterns like POM, data-driven testing, or BDD; triggers include automation testing and test automation strategy.

Why use Automation Testing on TypingMind?

Because you install it once and use it with any model. Automation Testing 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 Automation Testing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/naodeng/awesome-qa-skills/tree/main/skills/en/testing-types/automation-testing. 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 Automation Testing?

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 Automation Testing?

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

Is the Automation Testing 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Automation Testing (English)

When to Use

Workflow

Domain Execution Essentials

Core Constraints

Progressive Disclosure

Pre-delivery Checklist

Common Pitfalls

Bundled files

Frequently asked questions

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