Quality Engineering Test Plan Authoring

Community

HoangNguyen0403

quality-engineering-test-plan-authoring

Turn acceptance criteria into an executable test plan (scenarios, seed, selector gaps) before generating E2E code. Use when ACs exist but no runnable test plan does yet.

Overview

Publisher	HoangNguyen0403
Repository	`agent-skills-standard`
Skill name	`quality-engineering-test-plan-authoring`
Stars	573
Forks	166
Bundled files	6
License	MIT
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.
6 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by HoangNguyen0403 on GitHub. Read the source before you install it.

Installation

Install the Quality Engineering Test Plan Authoring 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/HoangNguyen0403/agent-skills-standard/tree/develop/.agents/skills/quality-engineering/quality-engineering-test-plan-authoring
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/HoangNguyen0403/agent-skills-standard/tree/develop/.agents/skills/quality-engineering/quality-engineering-test-plan-authoring

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/HoangNguyen0403/agent-skills-standard.git /tmp/agent-skills-standard
mkdir -p .claude/skills
cp -r /tmp/agent-skills-standard/.agents/skills/quality-engineering/quality-engineering-test-plan-authoring .claude/skills/quality-engineering-test-plan-authoring

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

Use it in TypingMind

Enable Quality Engineering Test Plan Authoring 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 Quality Engineering Test Plan Authoring 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 Quality Engineering Test Plan Authoring 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.

Quality Engineering: Test Plan Authoring

Priority: P1 (HIGH)

Input

AC-* IDs and SRS lanes (unit/integration/E2E-web/E2E-mobile/API) from the approved PRD/SRS. Never derive scenarios from reading the code — code shows what exists, not what the acceptance criteria require.

Output

docs/srs/test-plan-[slug].md (and specs/[slug].md once Playwright Test Agents are initialised on the target repo). Each scenario block: Steps, Expected, @AC-n tag, priority, exactly one lane (web|ios|android|api). One scenario covers one AC condition — do not fold multiple conditions into one scenario.

Seed

tests/seed.spec.ts (or platform equivalent) carries only shared prerequisites: auth and navigation to the starting screen. No assertions.

Mandatory Sections

Selector Gaps (elements the plan needs that have no stable id yet — feeds specialist-testid-inserter) and Data & Reset (fixtures needed, how state resets between scenarios). Gaps must follow the <screen>-<element>-<role> naming convention defined in quality-engineering-selector-stability.

Scenario Classes

Each AC condition expands to P (positive), N (negative: a stated condition violated), and E (edge: boundary of a stated condition). Classes must differ by precondition or input, never by phrasing. Every Expected cites its AC or business rule, or is tagged ASSUMED and surfaced under an Assumed Results header. On a HALT trigger (ultra-short AC, no expected behavior, bundled ACs, contradiction, undefined state) stop and ask; return HALT: <trigger> in autonomous mode.

Relationship to Zephyr

Manual Zephyr TCs stay the system of record for business sign-off (quality-engineering-zephyr-test-generation); this skill's scenarios carry a bidirectional TC-key reference where one exists, and are additive, not a replacement.

Anti-Patterns

A scenario without an Expected outcome.
A plan derived from source code instead of AC-*.
Duplicating unit-level coverage in an E2E scenario.
A scenario spanning more than one lane.
A plan with no seed reference.
A negative scenario that only rephrases the positive.
An expected outcome not traceable to an AC and not tagged ASSUMED.

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 Quality Engineering Test Plan Authoring AI skill do?

Turn acceptance criteria into an executable test plan (scenarios, seed, selector gaps) before generating E2E code. Use when ACs exist but no runnable test plan does yet.

Why use Quality Engineering Test Plan Authoring on TypingMind?

Because you install it once and use it with any model. Quality Engineering Test Plan Authoring 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 Quality Engineering Test Plan Authoring in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/HoangNguyen0403/agent-skills-standard/tree/develop/.agents/skills/quality-engineering/quality-engineering-test-plan-authoring. 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 Quality Engineering Test Plan Authoring?

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 Quality Engineering Test Plan Authoring?

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

Is the Quality Engineering Test Plan Authoring AI skill free?

Yes. It is published on GitHub by HoangNguyen0403 under the MIT license. 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

Quality Engineering: Test Plan Authoring

Priority: P1 (HIGH)

Input

Output

Seed

Mandatory Sections

Scenario Classes

Relationship to Zephyr

Anti-Patterns

References

Bundled files

Frequently asked questions

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