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Claude Haiku 5.5 (effort default (no --effort flag) · thinking on) on Work out arrival times, layovers and tight connections for a multi-leg trip across time zones

AClaude Haiku 5.5default · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-20 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first try
Estimated cost
$0.0034
Wall time
13s
Human step-ins
0
Outcome
Pass

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Summary

Exact prompt

# Work out a multi-leg trip itinerary across time zones Input: `itinerary.json`, a list of flight legs in travel order. Each leg has a local departure time (`depart_local`, wall-clock time at the departure airport), the departure and arrival time zones (IANA names) and the block time in minutes. Rules: - Arrival time = departure instant + duration_min, written as wall-clock time in the arrival airport's zone, format `YYYY-MM-DDTHH:MM`. - Use the real time-zone rules for the travel dates, including daylight-saving changes. - Layover = minutes from a leg's arrival to the next leg's departure (real elapsed minutes). - A connection is tight when its layover is under 60 minutes. - total_elapsed_min = real minutes from the first departure to the last arrival. - date_change_legs = the legs whose local arrival date differs from their local departure date, in travel order. Write `out/itinerary.json`: `{"arrivals": {"<leg>": "<YYYY-MM-DDTHH:MM>", ...}, "layovers_min": {"<leg>": <int>, ...}, "tight": [<leg>, ...], "total_elapsed_min": <int>, "date_change_legs": [<leg>, ...]}` `layovers_min` and `tight` are keyed by the leg that arrives before the connection (every leg except the last), and `tight` is in travel order. ## 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.

Turn 4-6 flight legs given in local departure times and block minutes into local arrival times, layovers, tight-connection flags, total trip time and date-change legs. The travel window spans the late-October and early-November daylight-saving changes, and routes include half-hour and 45-minute offset zones. Departures that fall on ambiguous or skipped local times are redrawn. 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: arrival_local_times dst_rules_applied layover_minutes tight_connections total_elapsed date_change_legs

Setup notes: Batch 16 case r02-timezone-itinerary (offline, synthetic inputs, seed 1827814707). Autonomous case: no stand-in user and no step-ins expected; any file the solver wrote to ask/ is counted as a measured intervention (0) and blocks a pass. Prompt = TASK.md verbatim. Hidden key kept outside the solver's work dir. Scored with the case's scorer (python3 score.py WORKDIR KEYDIR, absolute paths); pass = every check true and no ask/ files. Tools: Read/Write/Edit/Glob/Grep/Bash, web disabled. Single run, no retries. 1-min load average at scoring 0.14 (8 cores). Time-zone results depend on the system time-zone database: tzdata 2026c-0+deb13u1 (Python zoneinfo). Claude Code's own reported cost for claude-haiku-5.5: $0.003396. Score: 6/6. Cost is an ESTIMATE: measured tokens x pricing.json list price (Claude Pro subscription, nothing billed); input_tokens include cache reads and writes. Single run.

Estimated cost List-price estimate; not actually billed.

Metrics

Estimated cost
$0.0034
Wall time
13s
Human step-ins
0
Turns
3
Model usage
ModelInput tokOutput tokCost
AClaude Haiku 5.5anthropic/claude-haiku-5.5effort default (no --effort flag) · thinking on60,7702,196$0.0034

Reproduce this run

  1. Use the use case prompt on the use case page.
  2. Same setup: Claude Haiku 5.5 (anthropic/claude-haiku-5.5, effort default (no --effort flag) · thinking on) via Claude Code 2.1.299 (headless -p), cloud.
  3. It counts as a success only if it meets every success criterion: arrival_local_times dst_rules_applied layover_minutes tight_connections total_elapsed date_change_legs
  4. Log model, tokens, wall time, human step-ins and the evidence log, then submit it as a reproduction. A different model? Submit a head-to-head rerun.

How runs are scored: Methodology.

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Automated checks

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Evidence log
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  "permission_denials": [],
  "terminal_reason": "completed",
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  "result": "I wrote `out/itinerary.json` with the computed itinerary. I checked the key figures by hand against UTC.\n\n- **Arrivals:** L1 `2026-11-02T07:05`, L2 `2026-11-02T17:36`, L3 `2026-11-04T01:56`, L4 `2026-11-03T20:56`.\n- **Layovers:** L1 341 min, L2 35 min, L3 455 min.\n- **Tight connections:** L2 (35 min is under 60).\n- **Total elapsed:** 3411 min, from the L1 departure to the L4 arrival.\n- **Date-change legs:** L1, L3, L4. L2 stays on the same local date.\n\nThe time zone rules applied correctly for these dates. The US clocks fell back on Nov 1, so the LAX and Chicago legs use standard time. Europe changes on Oct 25, so Berlin is on CET. Sydney is on daylight time (AEDT).\n\nI computed these with Python's `zoneinfo` in a single inline command and did not save a script, since the task only allows writing under `out/`.",
  "ttft_ms": 1603,
  "type": "result",
  "duration_ms": 12027,
  "uuid": "[REDACTED]",
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  "time_to_request_ms": 256,
  "first_content_frame_ms": 1401,
  "queued_turn_count": 0,
  "result_index": 0
 }
]

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