An analysis of GPT-5.5 Codex metadata reveals that its reasoning output tokens are disproportionately clustering at exact numerical boundaries like 516, 1034, and 1552. This unusual anomaly suggests the model may be artificially truncating its internal thought processes at these fixed limits. Consequently, this token-clustering issue is believed to be contributing to degraded overall performance.