Agent evaluation harnesses are software: they run a test suite, drive a test input generator, and decide outcomes with a test oracle. We audit them for defects a score table cannot show. First, a systematic oracle-integrity auditing approach - five state-integrity invariants and three known-answer controls - is measured by injecting seven oracle defect classes across two task domains and a synthetic domain. Every class is detected, and on the 57 separable variant-target combinations it detects 54; the repaired oracle yields no false positive. On a widely used agent benchmark, it exposes a reward function that resets the database to build a ground-truth hash and never restores it, so a harness scoring afterwards reads the reference solution's state: recorded labels report 4,194 database passes over 4,320 episodes, replay gives 2,883, and success falls from 94.3% to 65.5%. The correction is not a uniform offset; it removes 24 to 34 points from each agent and changes which agent this matrix measures as strongest. Second, more weakly, localising the apparatus is a property of the measurement: a 3,240-episode ablation associates the three documents with lower collapse in the tested configuration, without ordering them, and a second task domain reverses the language effect. Third, the method did not transfer to a second, independently implemented benchmark; we name the contract required. A replication package recomputes every analysis offline with no model calls.

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