A study on the effectiveness of using off-the-shelf small language models (SLMs) in agent harnesses, finding an eligibility gap for microtasks involving large language models. The study proposes a benchmark and analysis framework to assess SLMs and suggests using a baseline that meets a context-informed (CI-backed) threshold.