diff --git a/scripts/test_level2_level3.py b/scripts/test_level2_level3.py
new file mode 100644
index 0000000..6becb6d
--- /dev/null
+++ b/scripts/test_level2_level3.py
@@ -0,0 +1,193 @@
+#!/opt/homebrew/bin/python3.11
+"""
+Test Level 2/3 Dynamic Feature Extraction
+
+Purpose:
+1. Demonstrate Level 2/3 on-demand extraction
+2. Test with pose.json + video frames
+3. Show feature output structure
+
+Usage:
+    python scripts/test_level2_level3.py --file-uuid <uuid> --frame <frame_num>
+"""
+
+import sys
+import os
+import json
+import argparse
+import cv2
+
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+sys.path.insert(0, os.path.join(os.path.dirname(os.path.abspath(__file__)), "utils"))
+
+from feature_extractor import HierarchicalFeatureExtractor
+from proportion_calculator import calculate_proportions, estimate_region_from_keypoints
+
+OUTPUT_DIR = os.environ.get("MOMENTRY_OUTPUT_DIR", "/Users/accusys/momentry/output_dev")
+
+
+def get_regions_from_keypoints(keypoints, eye_width):
+    """Calculate Level 2 regions from keypoints"""
+    regions = {}
+    
+    # Face region (eyes to chin)
+    face_region = estimate_region_from_keypoints(
+        keypoints,
+        top_keypoint='left_eye',
+        bottom_keypoint='nose',
+        left_keypoint='left_ear',
+        right_keypoint='right_ear',
+        eye_width_factor=2.0
+    )
+    if face_region.get('width', 0) > 0:
+        regions['face'] = face_region
+    
+    # Torso region (neck to hip)
+    torso_region = estimate_region_from_keypoints(
+        keypoints,
+        top_keypoint='neck',
+        bottom_keypoint='left_hip',
+        left_keypoint='left_shoulder',
+        right_keypoint='right_shoulder',
+        eye_width_factor=0
+    )
+    if torso_region.get('width', 0) > 0:
+        regions['torso'] = torso_region
+    
+    # Leg region (hip to ankle)
+    leg_region = estimate_region_from_keypoints(
+        keypoints,
+        top_keypoint='left_hip',
+        bottom_keypoint='left_ankle',
+        left_keypoint=None,
+        right_keypoint=None,
+        eye_width_factor=0
+    )
+    if leg_region.get('width', 0) > 0:
+        regions['leg'] = leg_region
+    
+    # Arms
+    left_arm_region = estimate_region_from_keypoints(
+        keypoints,
+        top_keypoint='left_shoulder',
+        bottom_keypoint='left_wrist',
+        left_keypoint=None,
+        right_keypoint=None,
+        eye_width_factor=0
+    )
+    if left_arm_region.get('width', 0) > 0:
+        regions['left_arm'] = left_arm_region
+    
+    right_arm_region = estimate_region_from_keypoints(
+        keypoints,
+        top_keypoint='right_shoulder',
+        bottom_keypoint='right_wrist',
+        left_keypoint=None,
+        right_keypoint=None,
+        eye_width_factor=0
+    )
+    if right_arm_region.get('width', 0) > 0:
+        regions['right_arm'] = right_arm_region
+    
+    return regions
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Test Level 2/3 Feature Extraction")
+    parser.add_argument("--file-uuid", "-u", required=True, help="File UUID")
+    parser.add_argument("--frame", "-f", type=int, default=0, help="Frame number")
+    parser.add_argument("--video", "-v", help="Video path (optional)")
+    parser.add_argument("--pose-json", "-p", help="Pose JSON path (optional)")
+    args = parser.parse_args()
+    
+    file_uuid = args.file_uuid
+    frame_num = args.frame
+    
+    video_path = args.video or f"{OUTPUT_DIR}/{file_uuid}.mp4"
+    pose_json_path = args.pose_json or f"{OUTPUT_DIR}/{file_uuid}.pose.json"
+    
+    if not os.path.exists(video_path):
+        print(f"Video not found: {video_path}")
+        sys.exit(1)
+    
+    if not os.path.exists(pose_json_path):
+        print(f"Pose JSON not found: {pose_json_path}")
+        sys.exit(1)
+    
+    with open(pose_json_path) as f:
+        pose_data = json.load(f)
+    
+    cap = cv2.VideoCapture(video_path)
+    cap.set(cv2.CAP_PROP_POS_FRAMES, frame_num)
+    ret, frame = cap.read()
+    cap.release()
+    
+    if not ret:
+        print(f"Cannot read frame {frame_num}")
+        sys.exit(1)
+    
+    # Find frame in pose data
+    pose_frame = None
+    for pf in pose_data.get('frames', []):
+        if pf.get('frame') == frame_num:
+            pose_frame = pf
+            break
+    
+    if not pose_frame:
+        print(f"Frame {frame_num} not in pose.json")
+        sys.exit(1)
+    
+    person = pose_frame['persons'][0]
+    keypoints = person.get('keypoints', [])
+    bbox = person.get('bbox', {})
+    
+    # Calculate proportions (Level 1 reference)
+    proportions = calculate_proportions(keypoints, bbox)
+    eye_width = proportions.get('reference_units', {}).get('eye_width', 0)
+    
+    # Get Level 2 regions
+    regions = get_regions_from_keypoints(keypoints, eye_width)
+    
+    # Extract features
+    extractor = HierarchicalFeatureExtractor()
+    
+    print(f"=== Frame {frame_num} ===")
+    print(f"Bbox: {bbox}")
+    print(f"Proportions: height_estimate={proportions.get('height_estimate', {}).get('estimated_height_cm', 0)}cm")
+    print(f"Shot type: {proportions.get('shot_type', {}).get('shot_type', 'unknown')}")
+    
+    # Level 2 extraction
+    print("\n=== Level 2 (Medium Regions) ===")
+    level2 = extractor.extract_level2(frame, regions)
+    for region, features in level2.items():
+        if region != 'level' and features:
+            color = features.get('color', {})
+            print(f"{region}: dominant_colors={color.get('dominant_colors', [[]])[:1]}, h_mean={color.get('h_mean', 0):.1f}")
+    
+    # Level 3 extraction
+    print("\n=== Level 3 (Fine Details) ===")
+    level3 = extractor.extract_level3(frame, keypoints, eye_width)
+    for region, features in level3.items():
+        if region != 'level' and features:
+            color = features.get('color', {})
+            print(f"{region}: h_mean={color.get('h_mean', 0):.1f}")
+    
+    # Save output
+    output = {
+        'frame': frame_num,
+        'bbox': bbox,
+        'proportions': proportions,
+        'regions': regions,
+        'level2': level2,
+        'level3': level3,
+    }
+    
+    output_path = f"{OUTPUT_DIR}/{file_uuid}_level23_frame{frame_num}.json"
+    with open(output_path, 'w') as f:
+        json.dump(output, f, indent=2, default=str)
+    
+    print(f"\nSaved to: {output_path}")
+
+
+if __name__ == "__main__":
+    main()
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