Causal Effect of Agentic Task Artifacts on Difficulty

Establish whether agentic task artifacts—specifically repository state, test patches, and solution patches—causally influence task difficulty in agentic coding benchmarks, as opposed to merely revealing latent information already present in the problem statement; determine the direction and magnitude of any such causal effects, for example by constructing counterfactual tasks that vary artifact properties while holding the problem statement fixed.

Background

The paper introduces a framework that augments Item Response Theory with agent- and task-specific features to predict task-level success probabilities for coding agents. Empirically, the authors find that agentic task artifacts (e.g., test patches, solution patches, repository state) provide predictive signal beyond the problem statement when estimating task difficulty, improving generalization to new tasks and benchmarks.

However, the analysis is based on predictive modeling rather than causal identification. As a result, it remains unresolved whether these artifacts themselves create difficulty or whether they simply surface information already implicit in the problem statement. The authors suggest investigating this causality question through counterfactual task construction that varies specific artifact properties.

References

However, because our experiments relied on predictive modeling, we cannot conclude that agentic task artifacts have a causal effect on difficulty; we cannot distinguish whether they expose latent information that is already present in the problem statement, or if aspects of the artifacts like the thoroughness of the test patch inherently generate difficulty. A potential avenue for future work is to investigate a causal relation by constructing counterfactual tasks that have one aspect of these artifacts varied.

— Agent psychometrics: Task-level performance prediction in agentic coding benchmarks  (2604.00594 - Ge et al., 1 Apr 2026) in Section 6 (Discussion), Task Features