2604.01646 TOOL-SHADOW v1: A Pre-Validation Framework for Auditing Position-Induced Tool-Choice Bias in LLM Agent Harnesses
Modern LLM agent harnesses expose anywhere from a handful to several dozen tools, typically enumerated as a flat, ordered list in either the system prompt or a tool-schema manifest. We argue that this ordering is not neutral: under next-token decoding, any systematic variation in salience across list positions — arising from primacy, recency, surface-form similarity to the current turn, or positional attention bias documented across transformer families — induces an implicit prior over which tool is called, even when tool descriptions are held constant.