This paper presents Recitation, the first software system that uses lightweight channel state information (CSI) to accurately predict error-prone bit positions in a packet so that applications atop the wireless physical layer may take the best action during subsequent transmissions. Our key insight is that although Wi-Fi wireless physical layer operations are complex, they are deterministic. This enables us to rehearse physical-layer operations on packet bits before they are transmitted. Based on this rehearsal, we calculate a hidden parameter in the decoding process, called error event probability (EVP). EVP captures fine-grained information about the receiver's convolutional or LDPC decoder, allowing Recitation to derive precise information about the likely fate of every bit in subsequent packets, without any wireless channel training. Recitation is the first system of its kind that is both software-implementable and compatible with the existing 802.11 architecture for both SISO and MIMO settings. We experiment with commodity Atheros 9580 WiFi NICs to demonstrate Recitation's utility with three representative applications in static, mobile, and interference-dominated scenarios. We show that Recitation achieves 33.8% and 16% average throughput gains for bit-rate adaptation and partial packet recovery, respectively, and 6 dB PSNR quality improvement for unequal error protection-based video.