This paper presents CRISP (Critique-and-Replan for Interactive Social Presence), an autonomous framework enabling robots to critique and replan their own social behaviors using a Vision-Language Model as a human-like social critic. The framework integrates joint and constraint extraction from robot description files, step-by-step behavior planning, low-level joint control code generation from visual information, VLM-based evaluation of social appropriateness, and iterative refinement through reward-based search. This approach enables robots to generate human-like, socially appropriate motions across various platforms with improved autonomy and naturalness.