In the latest part of the blog post on using Keyhole to analyze MongoDB clusters, Ken Chen introduces the Full Time Diagnostic Data Capture (FTDC) Assessment panel, which provides visualized presentation of FTDC data and scoring features to identify potential problems quickly. The panel uses scoring algorithms to evaluate metrics, with scores ranging from 0 to 100, where higher scores indicate better performance. Watermarks are used to set low and high usage thresholds for certain metrics, allowing for more accurate scoring. Keyhole also provides examples of how to calculate scores for metrics with known behavior or derived values. The blog post highlights several bottleneck patterns, including "Lost in Space," "Dream Weaver," "Vikings Attack," and "New York, New York," which illustrate common issues that can arise when using MongoDB, such as improper indexes, inadequate data access use cases, and excessive resource utilization. Chen emphasizes the importance of proper schema design and resource provisioning to avoid these issues.