The Agent Harness framework provides a structured environment for testing and evaluating autonomous AI agents. It focuses on deterministic execution and reproducible benchmarks to eliminate the randomness typical of LLM outputs. Developers can now isolate specific agent behaviors. This tool helps practitioners move from anecdotal success to verifiable performance metrics in agentic workflows.