Code review samples for Python/Panda3D-style game logic, written in an AI training and evaluation format.

The repository contains intentionally small examples that focus on practical review skills: identifying runtime bugs, frame-rate issues, input handling mistakes, asset-path assumptions, collision/proximity edge cases, and maintainability problems.

Python code review for interactive 3D/game-development snippets

Panda3D concepts such as task loops, scene updates, loader usage, and camera/input flow

Clear bug reports with expected behavior, observed behavior, root cause, and suggested fixes

AI-training style feedback that is concise, grounded, and actionable

Small pure-Python helper tests for the review reasoning

The tests do not require a Panda3D window. They validate the pure-Python helper logic used in the review examples.

Each review uses a consistent structure:

Summary

Severity

Observed issue

Why it matters

Suggested fix

Edge cases to test

This mirrors the kind of clear written evaluation expected in AI code-review and model-training tasks.