A green agent for the AgentX-AgentBeats OpenEnv challenge. Evaluates purple agents on a healthcare insurance fraud detection task: each episode presents 100 sequential claims, the purple agent must decide to APPROVE, FLAG_REVIEW, INVESTIGATE, DENY, or REQUEST_INFO, and the environment returns a multi-component reward (40% decision correctness, 30% rationale quality, 20% evidence citation, 10% efficiency). A budget of 15 INVESTIGATE actions per episode enforces cost discipline. Fraud patterns include upcoding, phantom billing, duplicate claims, and provider collusion, generated synthetically via a seeded simulator. The primary leaderboard metric is mean total reward across 20 episodes. Based on a 14,000-decision evaluation study comparing 7 agent configurations; full methodology at https://huggingface.co/shylane/healthcare-fraud-openenv-blog