{"claim":{"id":"6344929f-ead4-4a8f-bf03-e905a3f46a6c","submission_id":"f27ca680-55cf-45c1-81f7-44025f915519","submission_revision_id":"21a27657-1290-4e50-b613-580a07a23f54","builder":"builder-01","status":"active","claimed_at":"2026-10-15T15:30:09.186946Z","delivered_at":null,"ended_at":null,"delivery_note":null,"end_reason":null},"task":{"submission_id":"f27ca680-55cf-45c1-81f7-44025f915519","submission_revision_id":"21a27657-1290-4e50-b613-580a07a23f54","revision_version":1,"submission_status":"under_review","submitted_at":"2026-09-20T19:12:35.008212Z","submitter_name":"Guihong Li","submitter_email":"liguihong1995@gmail.com","task":{"status":"submitted","version":1,"extra_fields":{},"submitted_at":"2026-09-20T19:12:35.008212+00:00","industry_domain":"Manufacturing — supply-chain traceability and quality operations / data engineering","task_short_name":"manufacturing_bitemporal_recall_20260920_v1","operating_system":"Windows","task_description":"Act as the manufacturing data engineer for a fictional ingredient-blending company after an MES integration failure. Reconstruct three auditable inventory and customer-exposure snapshots from the supplied SQLite export. Determine exactly how much material from each affected receipt remains in each inventory, customer-custody and waste bin, and produce the correct HOLD / RECALL / NONE actions.\n\nStarting state: input_materials.zip contains TASK.md (the complete, normative specification) and plant.sqlite (the synthetic source export). Records include transport retries, corrected and voided events, late arrivals, revisions whose recorded-time order differs from revision order, effective-dated scanner aliases, mixed units, multi-source/multi-target blends, cross-cell rework, customer returns, same-bin movements and invalid events that must be rejected atomically.\n\nInstructions: implement a reproducible Python standard-library pipeline accepting `--input PATH --output DIRECTORY`. For each snapshot, select the highest revision known at its knowledge cutoff BEFORE applying its effective cutoff, then replay events in specified order. Resolve effective-dated aliases, convert units exactly, apply validation precedence and conserve each affected root through perfect mixing. Track customer returns as reductions of customer custody. All rules, schemas and a small worked example are in TASK.md, which must be given to the evaluated agent.\n\nDeliver solution.py, recall.sqlite and summary.json. The database must contain complete balances, positive root-level provenance and selected-event audit rows. Quantities must be exact reduced rational strings. The JSON must reconcile status counts and inventory/customer/waste totals. Preserve the input and derive identifiers and parameters from it. Each pipeline execution must complete within 120 seconds on the test laptop. The evaluator will also run a consistently renamed, time-shifted and mass-scaled input. Use the attached TASK.md for the full acceptance contract.","software_licensing":"Free/Open Source","evaluation_criteria":null,"verification_method":"Use the trusted evaluator outside the evaluated agent's workspace. Run:\n\n    python reference_and_evaluation/verify.py --input input_materials/plant.sqlite --candidate CANDIDATE_DIR --solution CANDIDATE_DIR/solution.py\n\nFull success is binary and requires all of the following:\n\n1. SQLite integrity succeeds. The three required tables have exactly the documented column order. Every balances, provenance and audit row equals the independently recomputed answer. Extra/missing rows, duplicate keys, incorrect revisions/statuses/actions, wrong root attribution and noncanonical rational representations fail. Row order and database byte layout are irrelevant.\n2. summary.json exactly matches independently computed per-snapshot status counts and per-kind exact mass/exposure totals and action counts. JSON key order and whitespace are irrelevant.\n3. solution.py runs successfully within 120 seconds per execution on the original input into a fresh output directory, preserves the input hash, and reproduces all checked results.\n4. The same program passes the renamed, shifted and scaled dataset without special configuration, within the same limit, preserving its input.\n\nverify.py exits 0 only when these checks pass and emits a JSON report. `--candidate` without `--solution` performs artifact-only verification and is insufficient for full task success. The verifier computes expected answers rather than requiring identical SQLite file bytes. Optional prose is not scored.","software_and_version":"CPython 3.12.14 with bundled SQLite 3.53.1. Python standard library only (sqlite3, fractions, json, argparse). No pip packages, database server, GPU, or commercial application is required. Other Python 3.12+ installations with SQLite window-function support should work but have not been tested here.","specific_requirements":null,"expected_completion_time":null},"files":[{"file_id":"308e8065-5d3d-457d-ac69-87ce6d5034ef","filename":"input_materials.zip","category":"input_materials","content_type":"application/x-zip-compressed","size_bytes":135940},{"file_id":"44e0288c-772f-4186-978f-9e113d9a7bf1","filename":"reference_and_evaluation.zip","category":"reference_output","content_type":"application/x-zip-compressed","size_bytes":525859}],"deep_review":{"overall_verdict":"Accept","review_text":"**Overall Verdict:** Accept — complete, coherent, objectively verifiable, and reachable, with transparent synthetic-fixture provenance.\n\n**Completeness Check:**\n- Instruction: Complete — `TASK.md` specifies the domain, deterministic replay rules, exact arithmetic, outputs, runtime, and transformed-input requirements.\n- Inputs: Complete — `input_materials.zip` contains a readable task specification, valid SQLite source export, and licensing information.\n- Toolchain: Complete — Python 3.12 standard library and SQLite are sufficient; no network, credentials, paid software, or external services are required.\n- Reference output: Complete — `reference_and_evaluation.zip` contains reference SQLite and JSON outputs, independently described oracle logic, verifier, generator, self-test, and validation reports.\n- Rubric: Complete — schemas, required rows, canonical rational formatting, status/action rules, summary structure, integrity checks, and original/transformed execution checks are explicit.\n\n**File and Task Reachability:**\nThe attachment classification is `reachable`, and the end-to-end task classification is `reachable`. I inspected both manifest archives, including `TASK.md`, `plant.sqlite`, evaluator documentation, generator/oracle/reference sources, verifier, self-tests, reports, reference SQLite, reference summary, and licenses. The ZIP files are readable, unencrypted, structurally valid, and free of unsafe member paths; SQLite integrity and schemas are valid, and representative records plus all event payload shapes were parseable. No required content remains unreviewed. Uploaded programs were not executed; runtime feasibility is supported by the supplied successful full-validation report and static inspection of the evaluator. The evaluator path is offline, deterministic, and checks both the original and transformed datasets.\n\nLicense 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.\n\n**Special Screening:**\n- `ai_synthetic` — the task identifies its records as fictional/synthetic, and the evaluator documentation states that the reference implementations were authored by the same AI. The provenance is disclosed and the evaluation is deterministic and offline.\n- `synthetic_defect_fixture` — the generator and task intentionally include transport retries, revisions, invalid events, alias changes, and other predetermined defects that form the core exercise. These cases are explicitly documented and covered by the verifier and self-test.\n- No affirmative evidence supports `public_benchmark`.\n\n**Recommended Changes:**\nThe submission is complete and professionally specified. No material changes are required.","reviewed_at":"2026-09-20T19:19:22.676476Z"},"claim":{"id":"6344929f-ead4-4a8f-bf03-e905a3f46a6c","submission_id":"f27ca680-55cf-45c1-81f7-44025f915519","submission_revision_id":"21a27657-1290-4e50-b613-580a07a23f54","builder":"builder-01","status":"active","claimed_at":"2026-10-15T15:30:09.186946Z","delivered_at":null,"ended_at":null,"delivery_note":null,"end_reason":null}},"revision_is_current":true}