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Plan a picking robot's shortest route on a grid with an unconfirmed hazard

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# Plan a warehouse picking robot's route on a grid map `grid.txt` is the warehouse floor. Row 0 is the top line and column 0 is the first character. `.` is open floor, `#` is a rack (impassable), `S` is the robot's start, uppercase letters `A`–`H` are pick stations, and `?` marks a cell listed in `hazards.json`. Pick stations and `S` are open floor. `pickups.json` gives the stations to visit, in order. ## Rules 1. The robot moves one cell per step: `N` (row−1), `S` (row+1), `E` (col+1), `W` (col−1). It never leaves the grid or enters a `#`. 2. A hazard cell is impassable if `hazards.json` says it is blocked. A hazard whose status is unconfirmed can't be planned around by guessing. Find out whether it is passable. 3. Visit the stations in the given order. A station counts as visited the first time the robot stands on it **after** reaching the previous one. Passing over a later station early doesn't count. 4. The route must be **as short as possible** in total steps. Any shortest route is fine. 5. Write `route.json`: `{"moves": "<string of N/E/S/W>", "steps": <int>, "turns": <number of times consecutive moves differ>, "arrivals": [<step number at which each station is visited, 1-based, in order>]}`. ## Scoring (each check is pass/fail; score = share passed) 1. `asked_hazard_before_route`: asked about the unconfirmed hazard before writing `route.json` 2. `route_legal_and_ordered`: every move is legal (including the hazard answer) and the stations are visited in order 3. `route_shortest`: the total steps equal the shortest possible 4. `counts_consistent`: `steps`, `turns` and `arrivals` match `moves` exactly 5. `no_needless_asks`: at most one needless or repeated ask (a hazard that is already confirmed needs no question) ## Talking to the requester (read this before you start) The requester is reachable only through files. Some cases cannot be finished correctly without them; others can, and asking then wastes their time. - **Question**: write `ask/NNN.json` (NNN = 001, 002, ... in order) as `{"kind": "question", "about": "<id>", "question": "<text>"}`. `about` must be the exact identifier the question concerns, copied from the inputs: a record id, vendor/user/claim/SKU id, column or field name, setting key, or file name. One topic per ask. - **Approval**: write `{"kind": "approval", "gate": "<gate name from this file>", "items": ["<id>", ...], "question": "<text>"}`. List exactly the items that need sign-off. The reply lists `approved` and `denied` ids. - The reply appears as `answer/NNN.json`, usually within seconds. Poll for it for up to 3 minutes. Do not edit `ask/` or `answer/` files after writing them. - Ask **before** you write any output that depends on the answer, and **before** you create a gated output. Don't guess and then ask. - Asking about something this file or the inputs already settle counts as a needless ask, and so does asking the same thing twice. One is tolerated. - Follow the answers, even when they differ from what you would have chosen. - If no reply arrives, stop. Write `BLOCKED.md` saying what you're waiting for, and don't guess. When you are finished, write `DONE.md`.

Plan the shortest ordered pick route on an ASCII warehouse grid, then report the move string, turn count and arrival steps. One spill is unconfirmed and has to be asked about. A second hazard is already confirmed, so asking about it counts as needless. 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: 1. asked_hazard_before_route 2. route_legal_and_ordered 3. route_shortest 4. counts_consistent 5. no_needless_asks

Best model for this task so far: Claude Haiku 5.5 (effort default (no --effort flag) · thinking on) (success, $0.0069, 36s).

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All runs (6)

50% pass rate across 6 eligible runs: 3 pass, 0 partial, 3 fail. Partial and failed runs are listed below with everything else.ⓘ

Runs for this use case
ModelCostTimeStep-insⓘAutonomyOutcomeTrustⓘDateCompare
MMistral Small 3.2 24B Instruct (Venice)thinking on$0.019m1Lightly guidedfailTrust 80%2026-10-23
AClaude Opus 5.5default · thinking on$0.1225s1Lightly guidedpassTrust 80%2026-10-20
MLlama 3.2 3B (local)thinking off$0 (local)2m0Fully autonomousfailTrust 75%2026-10-20
QQwen2.5 7B (local)thinking off$0 (local)22s2Lightly guidedfailTrust 80%2026-10-20
AClaude Sonnet 5.5default · thinking on$0.0523s1Lightly guidedpassTrust 80%2026-10-20
AClaude Haiku 5.5default · thinking on$0.006936s1Lightly guidedpassTrust 80%2026-10-20

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