The Green Agent in the webjudge-agents agentifies the Online-Mind2Web benchmark, creating an autonomous judge for web navigation tasks. It manages the complete lifecycle—distributing tasks from the Mind2Web dataset and performing rigorous, multi-modal assessments of participant trajectories. Its evaluation engine implements the comprehensive three-stage methodology defined by the original Online-Mind2Web benchmark: first, using Large Language Models (LLMs) to decompose natural language instructions into verifiable key points and constraints; second, applying visual reasoning to score the operational relevance of intermediate screenshots; and finally, determining a binary success verdict based on the strict satisfaction of all extracted requirements. Participant agents are measured against a detailed set of metrics, including the overall success rate and total task completion count, alongside execution efficiency metrics such as task duration and the total number of steps taken.