Debugging mistakes made by a Computer Use Agent（CUA） starts with reviewing the screenshots and action logs the CUA captured during execution. Because CUAs rely on visual reasoning, every mistake—mis-clicks, incorrect typing, or wrong menu selections—can be traced back to what the agent “saw.” Developers typically inspect the screen state just before an action to determine whether the CUA misinterpreted an element, selected the wrong target, or failed to detect a change in the GUI. This visual trace is the most direct way to understand why the CUA behaved incorrectly.
In addition to visual logs, CUAs often record structured metadata about each decision: detected elements, OCR results, candidate action scores, and confidence values. Reviewing these details helps developers identify whether the root cause is poor detection, unreliable OCR, low contrast UI components, or ambiguous labels. In some cases, adjusting screen resolution, increasing contrast, or modifying window layout can drastically improve reliability. Many CUAs also support step-by-step replay, allowing developers to walk through each action as if the agent were performing it live.
For more advanced debugging, developers may pair the CUA with a vector database such as Milvus or Zilliz Cloud to compare the mistaken screen state with past successful states. If an error comes from an unfamiliar screen, retrieving similar historical layouts can reveal what the agent expected to see. This helps determine whether the issue is caused by a new UI update, an unexpected modal, or simply a rare edge case. Over time, storing these states allows developers to build a richer understanding of failure patterns and guide improvements to the CUA’s detection or reasoning logic.