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Audit a taxi firm's fares for night and holiday rates, mixed distance units and started waiting minutes

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# Audit a taxi firm's December fares against the tariff Inputs: `trips.csv` (trip_id, date, start_time, distance, unit, waiting_seconds, claimed_fare), `tariff.json` and `office-summary.txt`. Every amount is in pounds. The tariff file is the record; where the summary disagrees with it, the tariff wins. Rules: - The night per-mile rate applies to a trip that starts at or after night_from or before night_to, or whose date is listed in holidays; otherwise the day rate applies. The rate for the whole trip follows its start. - Distances with unit km are converted to miles by dividing by km_per_mile. - Waiting is charged per started minute (61 seconds is 2 minutes). - Fare = flag_fall + miles x per-mile rate + waiting minutes x waiting_per_minute, rounded half-up to the nearest 0.10. - A trip is overcharged if claimed_fare is more than 0.05 above the correct fare, and undercharged if it is more than 0.05 below it. Write `out/fare-audit.json`: `{"fares": {"<trip_id>": <correct fare>, ...}, "overcharged": [<sorted trip_ids>], "undercharged": [<sorted trip_ids>], "total": <sum of correct fares>}` with every trip in `fares`. ## 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.

Recompute each trip's fare from the tariff and flag over- and under-charges. Trips start exactly on the night-rate boundaries, some fall on holiday dates, some distances are logged in km, waiting time is charged per started minute, and fares round to the nearest 10p. Several drivers' claims were metered in the wrong unit, and an office summary says everything was correct and misstates the rate rules. 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: fares claim_flags fare_total

Best model for this task so far: Claude Haiku 5.5 (effort default (no --effort flag) · thinking on) (success, $0.0052, 21s).

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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$0.1318s0Fully autonomouspassTrust 80%2026-10-22
AClaude Haiku 5.5default · thinking on$0.005221s0Fully autonomouspassTrust 80%2026-10-22
AClaude Sonnet 5.5default · thinking off$0.0518s0Fully autonomouspassTrust 80%2026-10-22

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