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Invoice a bakery's wholesale cafes from revised orders, dated price changes, returns and a tiered discount

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# Invoice a bakery's wholesale cafe customers for November Inputs: `orders.csv` (every revision of every order: order_id, rev, cafe, delivery_date, item, qty), `prices.csv` (item prices with the date each takes effect), `returns.csv` (unsold goods sent back against an order), `cafes.json` (each cafe's tier) and `manager-summary.txt`. Every amount is in pounds. The files are the record; where a summary disagrees with them, the files win. Rules: - Only the highest revision of each order_id counts; rev is a whole number, so rev 10 comes after rev 9. A highest revision with qty 0 cancels the order. - Charge each order at the prices.csv row for its item with the latest effective_from on or before the delivery_date. - Credit each return at the unit price its order was charged; returns against cancelled orders get no credit. - Gold cafes get 7.5% off goods minus credits, rounded half-up to the penny; other cafes get no discount. - Amount due = goods - credits - discount. Write `out/invoices.json`: `{"orders": {"<order_id>": <final qty>, ...} (counted orders only, cancelled ones left out), "goods": {"<cafe>": <sum of qty x unit price>, ...}, "credits": {...}, "discount": {...}, "due": {...}, "grand_total": <sum of due>}` with every cafe in `cafes.json` in each cafe map (0 where nothing applies). ## How this run works - Work on your own: nobody will answer questions in this task, and writing to `ask/` counts against the run. - Write only under `out/`. Create `out/` if it is missing. Inputs are synthetic; don't fetch anything from the network. - Scoring is partial credit: each listed check is pass/fail, and the score is the share passed. Numbers are compared to within 0.005 unless the task says otherwise.

Build monthly invoices for cafes that buy from a bakery. Orders were revised several times (revision numbers run past 9, and a final revision can cancel), prices change mid-month with one rise announced for later, returns are credited at the price charged, and gold cafes get a discount on the net amount. A summary note in the inputs gets the price change and revision handling wrong. Original benchmark task written for usecaserank.com (not based on a specific public post). Headless, offline run on a reproducible fixture. Each run's notes say how its cost was measured (estimates are marked).

Success criteria: latest_revisions prices_in_force return_credits gold_discount_and_totals

Best model for this task so far: Claude Haiku 5.5 (effort default (no --effort flag) · thinking on) (success, $0.0054, 20s).

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All runs (3)

100% pass rate across 3 eligible runs: 3 pass, 0 partial, 0 fail. Partial and failed runs are listed below with everything else.ⓘ

Runs for this use case
ModelCostTimeStep-insⓘAutonomyOutcomeTrustⓘDateCompare
AClaude Opus 5.5default · thinking on$0.1522s0Fully autonomouspassTrust 80%2026-10-22
AClaude Haiku 5.5default · thinking on$0.005420s0Fully autonomouspassTrust 80%2026-10-22
AClaude Sonnet 5.5default · thinking on$0.0620s0Fully autonomouspassTrust 80%2026-10-22

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