agentleFS
jhonatan-oliveiradevjhonatan-oliveiradev/agent-skills/skills/testing-playable-games/SKILL.md

testing-playable-games

Skill1 starsChanged 3 months agoMITView on GitHub

Use when verifying a browser or desktop game build for gameplay correctness, controls, combat feel, camera behavior, animation, performance, progression, and regression risk before calling a feature complete.

The file

Files
SKILL.md

Testing Playable Games

Test in layers

  1. Boot and recoverability: load, restart, pause, resume, route/scene transition.
  2. Controls: keyboard/gamepad/touch as supported; repeated and conflicting inputs.
  3. Movement and camera: boundaries, collision, slopes, follow lag, zoom, occlusion.
  4. Combat: hit registration, invulnerability, cooldowns, enemy state transitions, death, reset.
  5. Animation: transitions, looping, foot sliding, weapon continuity, effect timing.
  6. Progression: inventory, pickups, checkpoints, save/load, rewards.
  7. Performance: frame pacing, long-session stability, asset spikes, offscreen work.

Evidence

Reproduce failures with exact steps. For visual defects capture the state or frame where the problem is visible. Separate design feedback from implementation bugs.

Acceptance

A feature is not complete because its isolated code path works. It must survive normal gameplay sequences and transitions into and out of the state.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.