What problem does it solve? Annotating objects in CARLA simulator camera frames for detection datasets requires manual camera-intrinsics math and pose synchronization, which is error-prone when done ad hoc. This Skill reads actor and level 3D bounding boxes, draws them in the world, and projects them into a camera frame as 2D boxes with a JSON sidecar. ## Core Features & Use Cases - List 3D box geometry: Report dimensions (LxWxH from extent) of every matching actor via list --filter vehicle.*. - Draw 3D boxes in the world: Overlay tracking debug boxes that follow moving actors for a configurable duration on a rendered server. - Project to 2D annotations: Capture one camera frame, project each actor's 8 world vertices through the camera intrinsics, and write an annotated PNG plus a JSON of xyxy boxes. - Use Case: Spawn an RGB camera on the ego vehicle, then run project --camera <id> --filter vehicle.* to produce boxes.png and boxes.json ready for detection-dataset tooling. ## Quick Start Ask the agent to put bounding boxes on the vehicles visible in the ego camera and save the annotated image with a JSON of 2D boxes.