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One Page Test Strategy

Community
naodeng
one-page-test-strategy

Use this skill when a team needs a concise visual test strategy tied to project goals and risks; triggers include 一页纸测试策略、测试策略图 and one-page test strategy.

Overview

Publishernaodeng
Repositoryawesome-qa-skills
Skill nameone-page-test-strategy
Stars
279
Forks
36
Bundled files
7
Links
Skill sourceRepositoryHomepage
  • 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.

  • 7 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 One Page Test Strategy 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/skills/en/testing-types/one-page-test-strategy
  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/skills/en/testing-types/one-page-test-strategy .claude/skills/one-page-test-strategy
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable One Page Test Strategy 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 One Page Test Strategy 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 One Page Test Strategy 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.

One-Page Test Strategy

中文版： See the corresponding Chinese skill.

When to Use

  • A team needs a visual test strategy that is easy to discuss, share, and update.
  • Business goals, quality risks, and test approaches need to fit on one page.
  • The strategy should show early testing, built-in quality, and relevant post-release feedback.

If the user needs a full execution plan, detailed staffing, or test cases, use the existing full test-strategy capability; do not force those details onto this page.

Workflow

  1. Read and follow prompts/one-page-test-strategy.md for input review, output structure, and quality criteria.
  2. Extract goals, current phase, key risks, system characteristics, team capability, and constraints; separate facts, assumptions, and gaps.
  3. Follow the prompt's required modules: guiding principle and goal, functionality/performance/security scope, test enablers and constraints (environment/data/tools/team), seven lifecycle stages, shift-left/right, test quadrants, lean test layers, and iteration/release feedback.
  4. If context is incomplete, provide a discussable draft with assumptions and open questions; do not invent gates, facts, or owners.

Core Constraints

  • Treat the strategy as a goal-driven team discussion artifact that evolves with project phases and risks, not as a full test plan or execution record.
  • Show shared team ownership of quality; name individual owners only when input supports them.
  • Always retain functionality, performance, and security scope columns with project-relevant risks or an Open status; do not require all three to be in scope.
  • Always include a compact module for test environments/infrastructure, test data and access limits, automation/manual approach and tools, and relevant team roles/capability; distinguish known facts, recommendations, and Open items.
  • Always cover requirements analysis, before development, development, development complete, testing, before release, and released; show early shift-left feedback and post-release shift-right feedback.
  • Always show Q1–Q4 quadrants and the unit/API-integration/exploratory layers; orient business-facing/technology-facing vertically and supports-the-team/evaluates-the-product horizontally. Fill them from project definitions and evidence, and mark gaps Open. Automation/manual and tools are activity attributes, not quadrant axes.
  • Quadrants and layers are selection frameworks, not fixed checklists, execution order, or ratios; choose investment based on goals, risks, architecture, and capability.
  • Always show the iteration 1 → iteration 2 → … → iteration n → release/production cadence and explain how feedback enters the next iteration; mark unknown cadence and production mechanisms Open.
  • Entry/exit gates, numeric thresholds, test ratios, and schedules must come from project evidence; do not claim production monitoring or user feedback exists without evidence.

Progressive Disclosure

  • Read prompts/one-page-test-strategy.md for every strategy generation.
  • Read examples/one-page-sample.md when the user wants a layout reference; its project facts illustrate the format only.
  • When the user requests an image, slide, or other medium, preserve the seven lifecycle stages, four quadrants, three test layers, shift-left/right, and iteration feedback modules while following that format.

Pre-delivery Checklist

  • The page includes shared team quality ownership, the goal, and risk/status across functionality, performance, and security.
  • The page includes environment/infrastructure, test data/access limits, tools/approach, and team capability/roles, distinguishing known facts from Open items.
  • All seven lifecycle stages appear and show shift-left/right feedback.
  • Q1–Q4 quadrants use the stated axis orientation; unit/API-integration/exploratory layers and the iteration/release feedback loop each have a visible module.
  • Selected test types, quadrants, and layers fit known context; unsupported items remain recommendations or Open.
  • Assumptions, unknown gates, and open decisions are visible.
  • No fixed test ratios, numeric gates, or day-by-day schedules are invented; the page has not expanded into test cases or execution claims.

Common Mistakes

  • Do not apply the same generic template unchanged to every project.
  • Do not list every test type or layer to fill the page.
  • Do not draw test quadrants as a fixed execution sequence or assume every architecture uses a testing pyramid.
  • Do not use unconfirmed numeric thresholds to imply release agreement.

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 One Page Test Strategy AI skill do?

Use this skill when a team needs a concise visual test strategy tied to project goals and risks; triggers include 一页纸测试策略、测试策略图 and one-page test strategy.

Why use One Page Test Strategy on TypingMind?

Because you install it once and use it with any model. One Page Test Strategy 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 One Page Test Strategy 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/one-page-test-strategy. 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 One Page Test Strategy?

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 One Page Test Strategy?

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

Is the One Page Test Strategy 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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