Run Playwright-based automated tests for web games with deterministic time-stepping.
npx skills add https://github.com/openai/skills --skill develop-web-game
Please help me install this Agent Skill. Skill: develop-web-game Source: https://github.com/openai/skills/tree/main/skills/.curated/develop-web-game Command: npx skills add https://github.com/openai/skills --skill develop-web-game
This Skill streamlines the development of web games by providing a robust loop for implementing small changes, running automated tests with Playwright, and inspecting visual and textual output.
render_game_to_text) to verify correctness.Use the develop-web-game skill to run the Playwright client against http://localhost:5173 with the provided action payloads.
High-intent search queries and answers about installing and using this skill.
Automate web game testing with Playwright by executing game logic and validating state through deterministic time-stepping, input simulation, and capturing screenshots. This approach enables reliable iterative development by programmatically verifying visual and textual output.
Your web game needs to expose `window.render_game_to_text` for capturing text-based game state and `window.advanceTime` for deterministic time-stepping. These functions allow the Playwright client to execute actions and validate state changes reliably during iterative development.
Yes, you can capture screenshots and console error logs during web game testing. The Playwright-based client captures visual output alongside text-based game state, allowing you to inspect both visual changes and console errors after simulating inputs.
Deterministic time-stepping in web game testing advances the game state by controlled intervals using `window.advanceTime`. This ensures that game logic executes predictably during automated Playwright tests, making state validation reproducible across multiple iterative development cycles.
Playwright supports iterative development workflows for browser-based games by running automated tests against local environments. You can implement mechanics in small steps, simulate inputs via action payloads, and verify correctness through captured screenshots and JSON output.
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