**Overall Verdict:** Strong Accept — The submission is complete, professionally scoped, internally coherent, and provides a reachable single-machine workflow with a valid reference trajectory and objective evaluator.

**Completeness Check:**
- Instruction: Complete — The objective, continuous-episode constraint, whole-body controls, prohibited resets, required artifact, and success state are explicit.
- Inputs: Complete — The compiled scene, frozen physics and policy states, robot parameters, policy implementation, model weights, normalization data, and supporting documentation are supplied.
- Toolchain: Complete — Linux, MuJoCo, PyTorch/CUDA, NumPy, transforms3d, and applicable versions and GPU requirements are identified through legally obtainable software.
- Reference output: Complete — The reference trajectory contains exactly the four required finite numeric arrays with 42,976 aligned rows and substantive locomotion and manipulation commands.
- Rubric: Complete — Schema failures, replay limits, all-or-nothing object placement, final posture, continuous fall detection, and numerical thresholds are objectively defined and implemented.

**File and Task Reachability:**
Attachment classification: `reachable`. Task classification: `reachable`. Both `tidybot_ref.tgz` and `tidybot_data.tgz` were inspected and matched their manifest byte counts; both are readable gzip/tar containers without traversal paths, links, device entries, encryption, or excessive expansion. Inspected contents included `trajectory.npz`, `run_grader.py`, `task_brief.md`, `SETUP.md`, `TRAJECTORY_SCHEMA.md`, `SUCCESS.md`, `scene.mjb`, `init_state.npy`, `amo_init_state.npz`, `robot_params.json`, `amo_policy.py`, `amo_jit.pt`, `adapter_jit.pt`, and `adapter_norm_stats.pt`. Text files have valid ASCII/UTF-8 encoding and syntactically valid Python where applicable. NumPy artifacts were parsed without pickle support and have coherent schemas, finite values, and expected dimensions. The Torch artifacts are parseable ZIP-based containers with generated TorchScript code and tensor records; the normalization pickle references expected NumPy constructors. The MuJoCo binary contains every robot, object, actuator, and sensor identifier required by the parameters and grader. Embedded mesh geometry and all model-weight values were inventoried but not exhaustively interpreted. Independent replay was not performed because a matching MuJoCo 3.3.6/CUDA runtime was unavailable during review; this is a reviewer-tooling limitation, not a submission defect. The end-to-end path is clear: restore the supplied states, use the bundled balance policy while recording one whole-body trajectory, save the four-array NPZ, then schema-check and replay it to evaluate all three objects and robot stability. License keys, accounts, tokens, and other credentials are not required from the contributor. Confidential, proprietary, or internal material may be evaluated as submitted evidence without requiring additional disclosure.

**Special Screening:**
None. Public identifiability could not be independently checked because external search was unavailable; no affirmative evidence supports a special-screening label.

**Recommended Changes:**
The submission already provides unusually thorough contracts, safety gates, negative controls, threshold margins, and reproducibility evidence. No changes are required.