**Overall Verdict:** Accept — The submission is complete, internally consistent, objectively gradable, and reachable with the declared open-source toolchain.

**Completeness Check:**
- Instruction: Complete — The transformation objective, least-squares method, units, output schema, and rotation constraints are explicit.
- Inputs: Complete — `scene.json` contains 20 equal-length pairs of finite numeric 3D points with nondegenerate geometry and no missing values.
- Toolchain: Complete — Python 3.11, NumPy 1.24+, Linux, and offline execution form a practical, freely obtainable single-machine workflow.
- Reference output: Complete — `result.json` has the required fields and dimensions; its positive scale, proper rotation, translation, optimality conditions, and reported RMS are numerically consistent with the input.
- Rubric: Complete — `grader.py` implements the stated binary checks with explicit tolerances, strict finite-value and shape validation, residual recomputation, and reference comparisons.

**File and Task Reachability:**
Attachment classification: reachable. Task classification: reachable. All four attachments were inspected: `scene.json` (3,944-byte JSON), `SPEC.md` (1,213-byte UTF-8 Markdown), `result.json` (469-byte JSON), and `grader.py` (4,426-byte UTF-8 Python). Their downloaded sizes match the manifest, their actual formats match their declared roles, and there are no containers, encryption barriers, or unreviewed contents. The evaluator was inspected statically rather than executed; its relevant numerical contract and reference values were independently checked. Solver-visible inputs are separated from the reference and evaluator assets by manifest category. End to end, a solver can read the paired points, compute the similarity transform with Python and NumPy, emit the specified JSON, and be evaluated deterministically against the protected reference. 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 task explicitly identifies the canonical Umeyama 1991 method and supplies its closed-form equations. This does not expose the instance-specific numerical answer, which still requires processing the submitted point data; the offline environment further limits answer retrieval.

**Recommended Changes:**
The submission provides coherent inputs, a valid reference, and a hardened evaluator. No changes are required.