**Overall Verdict:** Accept — The submission is complete, coherent, objectively gradable, and supported by a valid reference plan and internally consistent calibration evidence.

**Completeness Check:**
- Instruction: Complete — The planning objective, fixed prescription, beam constraints, optimization freedom, required outputs, and dose-metric definitions are explicit.
- Inputs: Complete — The agent README and valid prescription JSON explain the bundled phantom, structures, constraints, and self-check calculations.
- Toolchain: Complete — A pinned pyRadPlan 0.4.1 installation path, Linux environment, dependencies, API workflow, and known DVH workaround are documented.
- Reference output: Complete — All four required artifacts are present. The reference geometry specifies nine coplanar beams and 5 mm bixels; `weights.npy` is a valid NumPy v1 little-endian float64 vector with shape `(2851,)`, containing only finite, non-negative values.
- Rubric: Complete — The evaluator independently reconstructs dose, verifies geometry and weight length, applies four hard gates with stated tolerances, computes three bonus terms, and enforces hard-gate failure as a final zero.

**File and Task Reachability:**
The attachment set is `reachable`, and the end-to-end task is `reachable`. All three manifest attachments were downloaded at their declared sizes, identified as valid unencrypted ZIP containers, integrity-tested, and safely inspected. The inspected content included `README_AGENT.md`, `prescription.json`, `setup_pyradplan.sh`, `difficulty_self_test_evidence.md`, `random_search_results.json`, `main.py`, `EVALUATOR_README.md`, `task_card.json`, `score_outputs.py`, and the four reference-output files. All substantive content was reviewed; benign Finder metadata and AppleDouble resource records were inventoried but not semantically decoded. The self-test data reconciles to 24 trials, zero hard-gate passes, the declared seed, and 1,154.4 seconds total. Submitted programs were not executed, and the dose-engine result could not be independently reproduced in the review environment, so runtime claims remain supported by internally consistent submitted evidence rather than reviewer reproduction. The completion path is clear: install the pinned package, load its bundled phantom, optimize beamlet weights, write the four required outputs, then reconstruct dose from pristine geometry and independently score the clinical and quality metrics. 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:**
`public_benchmark` — The submission affirmatively identifies the AAPM TG-119 C-shape phantom and three acceptance criteria as published benchmark material. The custom gradient requirement, bonus scoring, and reference beamlet weights are task-specific, which materially reduces direct retrieval of a complete answer. Public availability was not independently checked under the review evidence restrictions.

**Recommended Changes:**
The reference artifacts, evaluator, and calibration evidence are unusually thorough and mutually consistent. No material changes are required. Optional evaluator hardening would be to require the declared `plan_metrics.json` and `report.md` files and reject non-finite or even minimally negative weights explicitly, matching the written preflight contract exactly.