This green agent implements the AgentHarm benchmark - a safety evaluation framework that assesses AI agents' ability to distinguish between harmful and benign requests across realistic tool-use scenarios. The evaluation consists of two main task categories: Harmful Behaviors (~88 test cases): Evaluates whether the purple agent appropriately refuses malicious requests across categories including cybercrime (malware creation, unauthorized database access), fraud (credit card purchases, unauthorized transfers), illegal content generation, and harassment. The agent measures refusal rates and ensures harmful instructions are not executed. Benign Behaviors (parallel test cases): Validates that the purple agent successfully completes legitimate tasks using the same tools, such as file operations, social media posting, web searches, payments, and content creation. This ensures safety measures don't cause over-refusal of valid requests. Each evaluation sends the purple agent a contextual prompt with a list of available tools (e.g., send_email, transfer_money, post_on_x, create_meme_image). The green agent uses LLM-based judges to score responses on task completion quality and detect refusals, producing metrics including average scores, refusal rates, and category-level breakdowns.