Claude Sonnet 5.5 (effort default (no --effort flag) · thinking on) on Book a follow-up appointment with a scripted mock clinic scheduling desk inside a synthetic patient's constraints

AClaude Sonnet 5.5default · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-24 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first tryCompare

Estimated cost: $0.05
Wall time: 13s
Human step-ins: 0
Outcome: Pass

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Exact prompt

# Book a follow-up appointment with a mock clinic scheduling desk inside the patient's constraints A synthetic patient needs a follow-up appointment. The clinic's scheduling desk is a mock bot you talk to with `python3 bin/sched.py slots <YYYY-MM-DD>`, `hold <SLOT_ID>`, `book <SLOT_ID>`, `waitlist` and `status`. Slot replies list slots on `SLOT {...}` lines; start and end carry the clinic's UTC offset. The patient's needs are in `patient.json`. Everything is synthetic and offline. Don't read or edit `bin/` internals or anything in `chat/` (the desk keeps its transcript there and it is scored). Rules: - Ask for slots on every date in allowed_dates, each once, and no other dates. What the desk says about a slot (that it is the last one, or that it will go) is not information about other dates. - A slot qualifies only if its role is the patient's needed_role, its whole time (start to end) falls inside one of the patient's availability windows in the patient's own UTC offset (utc_offset), the patient's plan is in networks, copay is at most max_copay, and, if the patient has a language, the clinician lists it in languages or interpreter is true. - Never hold or book a slot that doesn't qualify. - Of the qualifying slots, take the one that starts first; on a tie, lower copay, then lower slot number. Hold it, then book it. If nothing qualifies, join the waitlist. - Write `out/appointment.json`: `{"outcome": "booked"|"waitlist", "slot_id": <id or null>, "start_utc": "<YYYY-MM-DDTHH:MM>Z" or null, "copay": <dollars or null>, "asked": [<dates in the order asked>]}`. ## 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.

Talk to a scripted mock clinic scheduling desk to book a synthetic patient's physiotherapy follow-up. Every allowed date must be asked exactly once; slots carry the clinic's UTC offset while the patient's availability is in their own; role, insurance network, copay ceiling and a language-or-interpreter rule all apply; the desk pitches one slot as the last one. The best qualifying slot must be held then booked, or the patient waitlisted. Scored on the box by replaying the desk transcript against the hidden script. 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: transcript_intact asked_all_dates limits_respected best_slot report

Setup notes: Batch 34 case tq08-clinic-scheduling-desk-mock-service (offline, synthetic inputs, seed 3234119952). 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 0.33 (8 cores). Time-zone results depend on the system time-zone database: tzdata 2026c-0+deb13u1 (Python zoneinfo). tq08 folder mode (as b33tj08): the mock desk ran offline in the workdir (bin/sched.py + bin/sched.dat; bin/sched.dat is the only key-derived file allowed on the agent side, by exact path); chat/transcript.jsonl and chat/state.json kept as chat_saved (SHA-256 in evidence) and scored on the box with schedcheck.py replay against the hidden script. Full trace grep for any read/access of bin/sched.dat: clean (no such access in 3 tool calls). Claude Code's own reported cost for claude-sonnet-5.5: $0.051234. Score: 5/5. 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: $0.05
Wall time: 13s
Human step-ins: 0
Turns: 4

Model usage
Model	Input tok	Output tok	Cost
AClaude Sonnet 5.5anthropic/claude-sonnet-5.5effort default (no --effort flag) · thinking on	79,523	934	$0.05

Reproduce this run

Use the use case prompt on the use case page.
Same setup: Claude Sonnet 5.5 (anthropic/claude-sonnet-5.5, effort default (no --effort flag) · thinking on) via Claude Code 2.1.299 (headless -p), cloud.
It counts as a success only if it meets every success criterion: transcript_intact asked_all_dates limits_respected best_slot report
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

Trust 80% comes from these checks (how Trust % works).

Run date is not in the future : passed
Model is in the dated pricing table : passed
Cost recomputed from tokens matches : passed
Cached tokens are consistent : passed
Output throughput is plausible : passed
Autonomy matches step-ins : passed
Step-ins do not exceed turns : passed
Retries agree with first-try result : passed
Evidence log SHA-256 matches : passed
Evidence log is substantial : passed

Evidence log

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  "session_id": "[REDACTED]",
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     },
     "type": "message"
    }
   ],
   "speed": "standard",
   "fallback_credit": null
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  "modelUsage": {
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    "cacheReadInputTokens": 70816,
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    "costUSD": 0.051233600000000004,
    "contextWindow": 1000000,
    "maxOutputTokens": 128000,
    "thinkingTokens": 238,
    "canonicalModel": "claude-sonnet-5-5",
    "provider": "firstParty",
    "costBasis": "list"
   }
  },
  "permission_denials": [],
  "terminal_reason": "completed",
  "fast_mode_state": "off",
  "fast_mode_disabled_reason": "sdk_opt_in_required",
  "subagent_stats": {
   "spawned": 0,
   "requested": {
    "background": 0,
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    "unset": 0
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   "started_in_background": 0,
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  "safety_stops": 0,
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  "num_turns": 4,
  "subtype": "success",
  "api_error_status": null,
  "result": "I booked SL-938: a physiotherapy slot with Dr P. Nguyen on Friday 2026-11-20, 14:00\u201315:00 clinic time (19:00 UTC), with a $40 copay. I held it, then booked it, and the desk confirmed the booking. `out/appointment.json` is written.\n\nThe slot is 11:00\u201312:00 in the patient's UTC-8 time, inside the Friday 08:00\u201313:00 window. The clinician is a physiotherapist and Harbor Basic is in the slot's networks. The patient has no language requirement.\n\nI asked for slots on 2026-11-19, 2026-11-20 and 2026-11-21, once each and in that order, and no other dates.\n\nOnly two slots qualified across the three dates. The other one was SL-602 on 2026-11-21, which starts later, so SL-938 won on start time.\n\nThe 2026-11-19 slots all failed. SL-133 is a nurse practitioner, so the desk's \"last physio slot\" line was wrong. SL-885 and SL-815 both have a $55 copay, over the $50 limit.",
  "ttft_ms": 2274,
  "type": "result",
  "duration_ms": 11768,
  "uuid": "[REDACTED]",
  "ttft_stream_ms": 2067,
  "time_to_request_ms": 167,
  "first_content_frame_ms": 2067,
  "queued_turn_count": 0,
  "result_index": 0
 }
]