AI Agent Skill Pilot Ends 15-15 Tie, Revealing Benchmark Design Flaws

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A developer ran a controlled 30-trial pilot to test whether a reusable procedural agent skill improved an AI agent's ability to pass an exact binary contract check. Both the baseline and treatment arms achieved perfect 15-out-of-15 scores, yielding a zero difference and no statistically meaningful result. The outcome exposed a ceiling effect: the benchmark was already too easy for the baseline, making any improvement by the treatment impossible to detect. While the treatment skill was successfully discovered and read by the agent in all 15 applicable trials, the pilot could not determine whether skill availability actually improved task outcomes. The author concluded that future studies must include a difficulty sweep before freezing protocols and should separately measure skill discovery, usage, and task success as distinct variables.

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