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This paper introduces HumanCLAW, an evaluation framework that decouples action decision-making from low-level execution to assess whether vision-language models can act through a physical body. Testing nine state-of-the-art VLMs on 1,218 episodes across 41 scenes, the best model achieves only a 16.8% success rate, revealing that current VLMs lack embodied self-awareness.