SCIPE is a tool designed to enhance the reliability of LLM-powered applications by identifying underperforming nodes within LLM chains. Developed by Ankush Garg and Shreya Shankar, SCIPE conducts error analysis on each node in an LLM chain to determine which node's improved accuracy would most significantly enhance the downstream output. It does this by calculating independent and dependent failure probabilities without requiring labeled data or ground truth examples. The tool identifies nodes whose failures have the largest impact on the output, allowing developers to address and fix root causes more effectively. SCIPE uses a compiled graph from LangGraph, application responses, and predefined configurations to analyze failure probabilities and debug paths, ultimately helping developers improve the performance and reliability of their applications.