Qa Game logo

Qa Game

Organization
PlayableIntelligence
qa-game

Add Playwright QA tests to a game — visual regression, gameplay verification, and performance. Use when the user says "add tests", "test my game", "add QA", "check for bugs", or "add visual regression tests". Do NOT use for manual playtesting or gameplay design.

Overview

PublisherPlayableIntelligence
Repositorygame-creator
Skill nameqa-game
Stars
331
Forks
41
Bundled files
Instructions only
LicenseMIT
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Qa Game 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.
  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/PlayableIntelligence/game-creator.git /tmp/game-creator
mkdir -p .claude/skills
cp -r /tmp/game-creator/skills/qa-game .claude/skills/qa-game
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Qa Game 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 Qa Game 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 Qa Game 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.

QA Game

Add automated QA testing with Playwright to an existing game project. Tests verify your game boots, scenes work, scoring functions, and visuals haven't broken — like a safety net for your game.

Instructions

Analyze the game at $ARGUMENTS (or the current directory if no path given).

First, load the game-qa skill to get the full testing patterns and fixtures.

Step 1: Audit testability

  • Read package.json to identify the engine and dev server port
  • Read vite.config.js for the server port
  • Read src/main.js to check if window.__GAME__, window.__GAME_STATE__, window.__EVENT_BUS__ are exposed
  • Read src/core/GameState.js to understand what state is available
  • Read src/core/EventBus.js to understand what events exist
  • Read src/core/Constants.js to understand game parameters (rates, speeds, durations, max values)
  • Read all scene files to understand the game flow
  • Read design-brief.md if it exists — it documents expected mechanics, magnitudes, and win/lose reachability

Step 2: Setup Playwright

  1. Install dependencies: npm install -D @playwright/test @axe-core/playwright && npx playwright install chromium
  2. Create playwright.config.js with the correct dev server port and webServer config
  3. Expose window.__GAME__, window.__GAME_STATE__, window.__EVENT_BUS__, window.__EVENTS__ in src/main.js if not already present
  4. Create the test directory structure:
    tests/
    ├── e2e/
    │   ├── game.spec.js
    │   ├── visual.spec.js
    │   └── perf.spec.js
    ├── fixtures/
    │   └── game-test.js
    └── helpers/
        └── seed-random.js
  5. Add npm scripts: test, test:ui, test:headed, test:update-snapshots

Step 3: Generate tests

Write tests based on what the game actually does:

  • game.spec.js: Boot test, scene transitions, input handling, scoring, game over, restart
  • visual.spec.js: Screenshot regression for stable scenes (gameplay initial state, game over). Skip active gameplay screenshots — moving objects make them unstable.
  • perf.spec.js: Load time budget, FPS during gameplay, canvas dimensions

Follow the game-qa skill patterns. Use gamePage fixture. Use page.evaluate() to read game state. Use page.keyboard.press() for input.

Step 4: Design-intent tests

Add a test.describe('Design Intent') block to game.spec.js. These tests catch mechanics that technically exist but are too weak to matter.

  1. Lose condition: Detect deterministically whether the game has a lose state. Read GameState.js — if it has a won, result, or similar boolean/enum field, the game distinguishes win from loss. Also check render_game_to_text() in main.js — if it returns distinct outcome modes (e.g., 'win' vs 'game_over'), the game has a lose state.

    If a lose state exists: start the game, provide NO input, let it run to completion (use page.waitForFunction with the round duration from Constants.js). Assert the outcome is the losing one (e.g., won === false, mode === 'game_over').

    This assertion is non-negotiable. Do NOT write a test that passes when the player wins by doing nothing. If the current game behavior is "player wins with no input," that is a bug — write the test to catch it.

  2. Opponent/AI pressure: If an AI-driven mechanic exists (auto-climbing bar, enemy spawning, difficulty ramp), test that it produces substantial state changes. Run the game for half its duration without player input. Assert the opponent's state reaches at least 25% of its maximum. If design-brief.md exists, use its expected magnitudes for thresholds. Otherwise, derive from Constants.js: calculate rate * duration and assert it reaches meaningful levels.

  3. Win condition: Test that active player input leads to a win. Provide rapid input throughout the round and assert the outcome is a win.

Step 5: Entity interaction audit

Audit collision and interaction logic for asymmetries that would confuse a first-time player.

If design-brief.md has an "Entity Interactions" section, use it as the checklist. Otherwise, audit GameScene.js directly:

  1. Find all collision handlers, overlap checks, or distance-based interactions
  2. Map which entities interact with which others
  3. Flag any visible moving entity that interacts with one side (player OR opponent) but not the other — add a // QA FLAG: asymmetric interaction comment in the test file noting the entity name and the asymmetry

This is a flag, not a hard fail. Some asymmetries are intentional (e.g., hazards that only affect the player). The flag ensures the asymmetry is a conscious design choice, not an oversight.

Step 6: Run and verify

  1. Run npx playwright test to execute all tests
  2. If visual tests fail on first run, that's expected — generate baselines with npx playwright test --update-snapshots
  3. Run again to verify all tests pass
  4. Summarize results

Step 7: Report

Tell the user in plain English:

  • How many tests were created and what they check
  • How to run them: npm test (headless), npm run test:headed (see the browser), npm run test:ui (interactive dashboard)
  • "These tests are your safety net. Run them after making changes to make sure nothing broke."

Example Usage

/qa-game examples/flappy-bird

Result: Installs Playwright → creates 15 tests (boot, scene transitions, input, scoring, restart, game-over, visual regression, FPS, load time) → generates tests/ directory with fixtures and helpers → all tests pass. Run npm test anytime after changes.

Next Step

Tell the user:

Your game now has automated tests! Finally, run /game-creator:review-game for a full architecture review — it checks your code structure, performance patterns, and gives you a score with specific improvement suggestions.

Pipeline progress: /viral-game/design-game/add-audio/qa-game/review-game

(This is the /viral-game one-shot pipeline — not the /make-game multi-session, milestone-driven workflow.)

Frequently asked questions

What does the Qa Game AI skill do?

Add Playwright QA tests to a game — visual regression, gameplay verification, and performance. Use when the user says "add tests", "test my game", "add QA", "check for bugs", or "add visual regression tests". Do NOT use for manual playtesting or gameplay design.

Why use Qa Game on TypingMind?

Because you install it once and use it with any model. Qa Game 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 Qa Game in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/PlayableIntelligence/game-creator/tree/main/skills/qa-game. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Qa Game?

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 Qa Game?

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

Is the Qa Game AI skill free?

Yes. It is published on GitHub by PlayableIntelligence 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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