Automate HTML5 game QA with scene graph inspection and input simulation.
npx skills add https://github.com/donghyun-bagelcode/2026-ai-jam --skill game-eye-qa
Please help me install this Agent Skill. Skill: game-eye-qa Source: https://github.com/donghyun-bagelcode/2026-ai-jam/tree/main/.gemini/skills/game-eye-qa Command: npx skills add https://github.com/donghyun-bagelcode/2026-ai-jam --skill game-eye-qa
HTML5 game development often lacks robust, automated QA tooling, leading to elusive bugs and slow iteration cycles.
Install game-eye and run it against your dev server to begin automated QA with a session-based workflow.
High-intent search queries and answers about installing and using this skill.
HTML5 game QA automation is achieved by running game-eye against a dev server, enabling structured scene graph inspection, input simulation, and assertion-based verification within a session-based workflow.
Yes, this automated testing approach works directly with PixiJS v7/v8 and GDevelop, allowing you to perform in-depth scene graph inspection and assertion-based verification for these specific frameworks.
To run automated test loops, you need game-eye installed and a running dev server, which together enable session-based QA and assertion-based verification for your HTML5 game.
Scene graph inspection works by directly analyzing the game's structure without relying on screenshots or VLM, allowing you to verify game states and debug issues programmatically.
Yes, you can simulate keyboard and mouse input during HTML5 game testing, allowing you to trigger specific game states and perform assertion-based verification on the resulting scene graph.
The primary limitation is that game-eye requires a running dev server to function and currently supports only PixiJS v7/v8 and GDevelop, limiting its use for other HTML5 frameworks.
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