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This paper identifies memory confabulation in Reflexion-style agents, where agents store incorrect task interpretations and persist in errors across environment resets. The authors introduce the Reflection Repetition Rate (RRR) metric to detect this and propose a mitigation that replaces open-ended self-diagnosis with programmatic failure signal extraction.