CAN AGENTS ADAPT WORLDS WITHOUT BREAKING WHAT WORKS? BENCHMARKING ROBOT-CONDITIONED ENVIRONMENT AUTHORING

An authoring agent should adapt an environment to a changed robot or task while preserving useful functions. We introduce a benchmark for robot-conditioned environment authoring centered on paired functional adaptation. The frozen source and edited world are evaluated under the same changed contract, requiring completion of a main job and retention of an independent protected job certified after the change but before editing. Each job starts from a separate reset of the submitted initial state. Acceptance requires complete motion witnesses for each declared test condition and distinguishes certification, directly established violations, and unresolved verification. Shared tools and explicit resource accounting support fixed-backbone policy comparisons, including our dependency-aware reference authoring workflow, and separate within-backbone Base/Ours comparisons. Frozenworld and literal-translation controls test certification gains from editing and when simple shifts suffice. Nested verifier budgets assess the sensitivity of conclusions to evaluation effort. Creation and valid position variation serve as auxiliary tracks. Main-only repair isolates the gap between main completion and joint completion, making protected-job retention an explicit evaluation target.