JarvisEvo is a research project implementing a photo editing agent that uses a synergistic editor-evaluator architecture. The system employs a multimodal large language model (MLLM) as the core intelligence, trained with RLHF to self-improve through iterative editing and evaluation cycles. The project includes model weights on HuggingFace and a benchmark dataset (ArtEdit-Bench) for evaluating photo editing agents.