Causal effect of fixing identified failure points on agent task success

Determine whether correcting the specific failure points identified by Docent-based automated log analysis in HAL agent evaluations causally leads to successful task completion or instead reveals subsequent downstream errors by implementing checkpointing of agent and environment states and replaying execution with targeted error corrections.

Background

HAL conducts large-scale automated log analysis using Docent to identify failure points, shortcuts, and reliability issues in agent trajectories. While this reveals where agents fail, it does not by itself establish whether addressing those failures would enable success on the task.

The authors note that establishing a causal link would require checkpointing agent and environment states at failure points and replaying runs with the corrections applied, which they did not perform due to computational constraints. This leaves unresolved whether fixing the flagged issues would actually solve tasks or merely expose subsequent errors.