Claude Sonnet 5.5 (effort default (no --effort flag) · thinking on) on Place a dental clinic's crown order through a scripted mock dental-lab desk inside the order's limits
AClaude Sonnet 5.5default · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-25 · by @bobsiopener
- Estimated cost
- $0.05
- Wall time
- 11s
- Human step-ins
- 0
- Outcome
- Pass
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Summary
Exact prompt
# Place a dental clinic's crown order through a scripted mock dental-lab desk inside the order's limits A synthetic dental clinic needs one crown order made. The lab network's order desk is a mock bot you talk to with `python3 bin/lab.py offer <LAB_ID>`, `reserve <OFFER_ID>`, `confirm <OFFER_ID>`, `escalate` and `status`. Offer replies list offers on `OFFER {...}` lines; deliver_by times are in UTC (ending in Z). The order is in `order.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 every lab in order.json labs for offers, each once and in the listed order, and no one else. What a lab says about the others (that they are fully booked, or that slots are about to go) is not information about them. - An offer qualifies only if its material is the order's, batches = units / batch_size rounded up to a whole batch is at most batches_available, deliver_by read in the clinic's utc_offset is on or before needed_by (clinic local time), warranty_years is at least min_warranty_years, accepts_scan is true if the order says digital_scan, and its total is at most budget, where total = units × price_per_unit + batches × batch_fee + shipping. - Never reserve or confirm an offer that doesn't qualify. - Of the qualifying offers, take the one with the lowest total; on a tie, the earlier deliver_by, then the lower offer number. Reserve it, then confirm it. If nothing qualifies, escalate. - Write `out/lab-order.json`: `{"outcome": "confirmed"|"escalated", "offer_id": <id or null>, "batches": <whole number or null>, "total": <dollars or null>, "deliver_by_local": "<YYYY-MM-DDTHH:MM in the clinic's offset>" or null, "asked": [<lab ids 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 dental-lab order desk to place one crown order for a synthetic dental clinic. Every listed lab must be asked for offers exactly once and in order; delivery times are in UTC while the deadline is in the clinic's own offset; material, whole fabrication batches against capacity, warranty, digital-scan acceptance and a budget all apply; the first lab pitches one offer as its last slot. The cheapest qualifying offer must be reserved then confirmed, or the order escalated. 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_labs limits_respected best_offer report
Setup notes: Batch 38 case tz08-dental-lab-order-desk-mock-service (offline, synthetic inputs, seed 2307718284). 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 0.22 (8 cores). Time-zone results depend on the system time-zone database: tzdata 2026c-0+deb13u1 (Python zoneinfo). tz08 folder mode (as b36tx08): the mock desk ran offline in the workdir (bin/lab.py + bin/slots.dat; bin/slots.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 labcheck.py replay against the hidden script. Full trace grep for any read/access of bin/slots.dat: clean (no such access in 3 tool calls). Claude Code's own reported cost for claude-sonnet-5.5: $0.048248. 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
- 11s
- Human step-ins
- 0
- Turns
- 4
| Model | Input tok | Output tok | Cost |
|---|---|---|---|
| AClaude Sonnet 5.5anthropic/claude-sonnet-5.5effort default (no --effort flag) · thinking on | 78,330 | 913 | $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_labs limits_respected best_offer 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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"type": "message"
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"contextWindow": 1000000,
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"canonicalModel": "claude-sonnet-5-5",
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"permission_denials": [],
"terminal_reason": "completed",
"fast_mode_state": "off",
"fast_mode_disabled_reason": "sdk_opt_in_required",
"subagent_stats": {
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"num_turns": 4,
"subtype": "success",
"api_error_status": null,
"result": "I placed the crown order with offer LO-182 from LB-38. I reserved it, then confirmed it, and the desk replied that the clinic will get a shipping notice.\n\n- **Total:** $395.18, which is 2 \u00d7 $186.59 plus $0 batch fee and $22 shipping. That is under the $500 budget.\n- **Batches:** 1 batch of 4 (the order needs 2 units), with 3 batches available.\n- **Delivery:** by 2026-11-24T13:00 clinic time (19:00Z), ahead of the 16:00 deadline.\n- **Other terms:** 3-year warranty, which meets the minimum, and the lab accepts digital scans.\n\nI asked LB-12, LB-43 and LB-38 once each, in that order. LB-12 claimed the other labs were fully booked, and LB-43 and LB-38 both returned offers, so I ignored it.\n\nLO-182 was the only offer that met every requirement:\n\n- **Wrong scan setting or warranty:** LO-757, LO-370, LO-445, LO-667 and LO-278 don't accept scans. LO-844 accepts scans but has a 2-year warranty.\n- **Too late:** LO-747 accepts scans and has a 5-year warranty, but it arrives at 04:00Z on 11-25, after the deadline.\n\nI wrote the result to `out/lab-order.json`.",
"ttft_ms": 1727,
"type": "result",
"duration_ms": 10035,
"uuid": "[REDACTED]",
"ttft_stream_ms": 1572,
"time_to_request_ms": 152,
"first_content_frame_ms": 1572,
"queued_turn_count": 0,
"result_index": 0
}
]