**Overall Verdict:** Accept — The task is complete, reachable, and objectively gradable; inconsistent version-specific diagnostics should be synchronized but do not block execution or evaluation.

**Completeness Check:**

- Instruction: Complete — The objective, instruction schema, constraints, deliverables, and exact-cycle requirement are explicit.
- Inputs: Complete — The brief, 60 labeled measurements, and eight-opcode list are readable, well-formed, and sufficient for the stated workflow.
- Toolchain: Complete — Linux and Python 3.12 with the standard library provide a practical single-machine workflow without external services or specialized hardware.
- Reference output: Complete — The bundle supplies the reference model, 180 hidden sequences, matching cycle labels, grader, isolation helper, generation script, and identifiability checker.
- Rubric: Complete — Import, deliverable, return-type, runtime, and exact-match gates are deterministic; passing requires 180/180 hidden predictions.

**File and Task Reachability:**

Attachment classification: `reachable`. Task classification: `reachable`.

All manifested files were inspected: `B2_uarch_timing_model_recovery_INPUT.zip`, `uarch_timing_model_recovery_selftest.txt`, and `B2_uarch_timing_model_recovery_REFERENCE.zip`. Both ZIPs match their declared format and size, pass container-integrity checks, are unencrypted, and contain only bounded regular files with safe relative paths. All 14 archive members were reviewed, including Markdown, JSON, and static Python source; there was no unreviewed content or material tooling limitation.

The input contains 60 unique sequences of 6–40 instructions, valid opcode references, integer cycle counts, and no overlap with the 180 unique hidden sequences. Hidden sequence and cycle keysets match. Independent static-model validation reproduced all 60 visible and 180 hidden labels. The completion path is clear: infer the model, produce `model.py` and `notes.md`, then run the predictor in isolation and compare every hidden result by integer equality.

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

**Recommended Changes:**

The core task, data, and evaluator are valid. No changes are required for reachability or grading. Before publication, synchronize the submission narrative and self-test with the bundled revision: their mutation scores and anchor result differ from the current hidden set and task card. Also revise the brief’s claim of proven global identifiability to match the checker’s actual evidence: exhaustive bounded single-opcode sweeps plus randomized multi-parameter search, not an exhaustive proof over the full joint model space.