**Overall Verdict:** Accept — The revision presents a complete, professionally representative EEG annotation task with a reproducible workflow, objective per-instance evaluation, and credible difficulty evidence.

**Completeness Check:**
- Instruction: Complete — defines whole-recording review, seizure criteria, onset and duration conventions, artifact exclusions, and exact deliverables.
- Inputs: Complete — specifies deterministic generation of 24 de-identified EDF instances and the solver-visible specification, templates, TSV contract, and runtime files.
- Toolchain: Complete — provides compatible Linux and Python requirements, pinned analysis dependencies, bootstrap wrappers, and host prerequisites.
- Reference output: Complete — identifies protected per-instance references, establishes the base alias relationship, and documents a successful oracle smoke test.
- Rubric: Complete — includes explicit hard gates, deterministic interval matching, point weights, tolerances, schema checks, and report-consistency checks.

**File and Task Reachability:**
The attachment set is `reachable`, and the end-to-end task is `reachable`. The inspected attachment was `eeg_evidence_sonnet5.zip`, a valid 7,553-byte, unencrypted ZIP containing six readable ASCII or UTF-8 text/JSON files: `NOTES.txt`, `aggregate_summary.txt`, `sonnet5.json`, `sonnet5_24distinct.json`, `eeg_case_e0755c_score0.98_stdout.log`, and `base_score0.37_stdout.log`. There were no unsafe paths, links, devices, encrypted members, executable payloads, integrity errors, or unreviewed archive content. The JSON schemas and all 24 distinct result records were inspected; their counts, class summaries, 21.125/100 parent-instance score, aggregate statistics, and alias handling are internally consistent. The generated EDF corpus, preparation source, templates, references, and scorer were not manifest attachments, so their bytes could not be independently inspected; external provenance checks were also outside the permitted evidence boundary. The declared path is nevertheless complete: build the dataset, bootstrap the pinned runtime, analyze each EDF offline, produce the two contracted outputs, and score each variant against its corresponding evaluator-only 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 recordings are deterministically derived from a public source, and the task anticipates possible published-annotation lookup. Header sanitization, opaque instance names, prohibition of external lookup, and no-network solver isolation mitigate direct answer retrieval. External search was not permitted, so canonical-benchmark or pretraining exposure could not be independently established.

**Recommended Changes:**
The submission provides a precise clinical workflow, strong evaluator specification, and internally consistent self-test evidence. No changes are required.