Epistemic Debt in Coding Agents: Repaying Unsupported Assumptions in Repository-Level Software Engineering

Repository-level coding agents act on provisional judgments while their evidence about a codebase is still incomplete. A wrong assumption about a call chain, a specification, or a test can silently become the premise of later edits, tests, and memory; every dependent action makes correcting it costlier. We call this accumulating exposure epistemic debt: the expected downstream correction cost of deferring verification of an action-dependent repository assumption. Existing agents verify reactively after a failure or indiscriminately before every write; neither selects which assumption is worth checking. We treat verification as a budgeted selection problem: a dynamic assumption graph links each falsifiable assumption to its evidence and dependent actions, and a budgeted controller runs the assumption–check pair whose expected avoided rework exceeds its cost. A paired counterfactual protocol measures that value by branching from the same checkpoint with and without a targeted check. On SWE-bench Lite (300 instances, three seeds), the debt-aware agent raises resolution from 31.9% to 48.8% with fewer agent steps and lower dollar cost. The gain replicates across three agent scaffolds and two backbones. The exposure-aware heuristic already provides a substantial improvement, while a learned scorer adds a further 4.5 percentage points on the full benchmark as an exploratory in-sample estimate; its held-out end-to-end transfer remains a limitation.