VectorClaw
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TDQS
Scored across 24 tools
Several tools have effectively the same purpose: vector_look and vector_capture_image both capture a camera frame, vector_status and vector_charger_status both report battery/charging state, and vector_face_detection overlaps heavily with vector_list_visible_faces. An agent could easily select the wrong tool despite the descriptions.
Most tools follow a vector_ + verb_noun pattern (drive, find_faces, capture_image), and the shared prefix makes the set feel unified. A few noun-style names like vector_pose, vector_status, vector_cube, and vector_face deviate slightly, but they are still predictable and readable.
24 tools is at the heavy end for a single server, and redundant pairs inflate the count. However, the robot-control domain legitimately needs many operations for driving, sensors, vision, and display, so the scope is borderline rather than excessive.
The set covers core Vector workflows: movement, docking, camera, speech, animation, face/object detection, head/lift control, sensor status, and setup. Lacking explicit audio capture or a dedicated stop-speaking command are minor gaps that don't create dead ends.