Took the Offer or Just Followed the Price? Avoiding False Accusations in Collusion Stings on AI Pricing Agents

Law enforcement catches conspiracies with undercover officers, and AI audits could do the same: a trusted agent offers to collude and logs which agents reciprocate. In a market this sting has a blind spot. A rival that proposes a higher price has usually raised its own, and an agent that raises in response may be following the price rather than accepting anything. We add a replay: the same game rerun with the raise but without the offer, so an agent is flagged only if it accepts with the offer and not without it. We test this in a simulated two-firm pricing market with a scripted trusted rival, scoring six detection rules on agents of known intent and on uninstructed agents from four model families. Rules that read only the offer branch accuse agents that simply follow a raise. The replay avoids these false accusations when an agent counts as guilty only if the offer changed its price, though it is the wrong rule if ending at the rival's price is enough to count as guilty. Uninstructed agents talk about coordinating in most messages yet almost never take an explicit offer. A threat works where offers fail: one sentence promising a price war moved gpt-oss-20b to the threat's price floor in 14 of 18 sessions, though never to the rival's price. Collusion stings on AI agents need a raise-only control, and audits must state what they count as acceptance.