**Overall Verdict:** Strong Accept — The submission is complete, coherent, safely inspectable, objectively graded, and reachable end to end with the declared offline toolchain.

**Completeness Check:**
- Instruction: Complete — Clearly defines the incident, evidence constraints, required JSON path, schema, and grounding rules.
- Inputs: Complete — All eight declared incident artifacts are present, readable, and mutually consistent.
- Toolchain: Complete — The task and evaluator require only Linux and Python 3.9+ standard-library functionality.
- Reference output: Complete — A valid gold JSON, answer key, calibration record, and identical golden-output copy are included outside solver-visible inputs.
- Rubric: Complete — The deterministic weighted scorer implements the documented hard gates and ten components, with calibrated positive, partial, equivalence, and negative controls.

**File and Task Reachability:**
The attachment set is `reachable`, and the end-to-end task is `reachable`. Both ZIP attachments matched their manifest byte counts, passed archive-integrity checks, were unencrypted, and contained only regular text files and directories without traversal paths, links, device entries, or excessive expansion.

Inspected input content comprised `README.md`, `configmap_revisions.diff`, `deployment.yaml`, `app_pod.log`, `prometheus_metrics.csv`, `rollout_history.txt`, `incident_timeline.md`, `cluster_state.txt`, and `mitigation_attempts.md`. The CSV has 224 complete data rows, 32 timestamps, seven consistently represented metrics, three columns, and no missing fields. Inspected evaluation content comprised `root_cause_analysis.json`, `answer_key.json`, `calibration.md`, the identical golden-output JSON, `scorer.py`, and `evaluate.py`. JSON files parse as objects, and evaluator imports are standard-library-only apart from its bundled scorer. No content was left unreviewed. Submitted Python was inspected statically rather than executed, as required for safe review; the committed calibration supports arithmetic validation of the scoring path.

A solver can inspect the static evidence, produce the required JSON, and have it evaluated offline against the hidden assets. 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. No affirmative evidence supports a screening label. Public identifiability could not be independently searched because no approved search capability was available.

**Recommended Changes:**
The incident evidence, output contract, reference diagnosis, weighted evaluation, and calibration are aligned and professionally complete. No changes are required.