Skill: action-and-motion-understanding

[Case 2]

• Initial Environment: A high-angle view of a tennis rally where the far-end player has just moved aggressively toward the net.
• Real Question: What is the specific technique used by the player to hit the ball and what was the direction of the shot?
• Real Trajectory: Analyze the player's body orientation and swing path as they approach the net. Detect the cross-court arm extension and the open-faced racquet angle. Map the resulting ball trajectory from the impact point across the longitudinal axis of the court. Conclude the action is a volley and its direction is cross-court.
• Real Answer: The player hit a forehand volley to the cross-court.
• Why this demonstrates the capability: This illustrates 'Kinetic Action Recognition and Directional Inference'. The agent must link the physical biomechanics of the player (shoulder rotation, wrist angle) to the resulting equipment state (ball path), proving an understanding of specialized technical execution.

[Case 3]

• Initial Environment: A synchronized multi-clip view of two athletes performing gymnastics floor routines. The first performs a double-tuck, the second a triple-twist.
• Real Question: Which of these videos has the highest difficulty in terms of technical skills?
• Real Trajectory: Divide each routine into countable rotational sub-units (Action Units). Trace the 360-degree rotation count for both the vertical and horizontal axes. Identify that the second athlete completes three full revolutions in the air compared to the first athlete's two, establishing a measurable increase in centrifugal momentum and technical complexity.
• Real Answer: Video 2 is more difficult due to the higher rotational count.
• Why this demonstrates the capability: This presents 'Technical Difficulty Ranking' through AU decomposition. The agent utilizes objective kinetic metrics derived from the video stream to synthesize a comparative judgment of athletic proficiency.

Pipeline Execution Instructions

To synthesize data for this capability, you must strictly follow a 3-phase pipeline. Do not hallucinate steps. Read the corresponding reference file for each phase sequentially:

1. Phase 1: Environment Exploration Read the exploration guidelines to discover raw knowledge seeds: references/EXPLORATION.md

2. Phase 2: Trajectory Selection Once Phase 1 is complete, read the selection criteria to evaluate the trajectory: references/SELECTION.md

3. Phase 3: Data Synthesis Once a trajectory passes Phase 2, read the synthesis instructions to generate the final data: references/SYNTHESIS.md