Claude Sonnet 5.5 (effort default (no --effort flag) · thinking on) on Price a pet-grooming salon's appointments by weight band and coat, with same-day multi-pet discounts, add-ons and matting time

AClaude Sonnet 5.5default · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-25 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first tryCompare

Estimated cost: $0.05
Wall time: 12s
Human step-ins: 0
Outcome: Pass

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Exact prompt

# Price a pet-grooming salon's appointments by weight band and coat, with same-day multi-pet discounts, add-ons and matting time Inputs: `appointments.csv` (appt_id, pet_id, groomer_id, date, addons, matting_min), `pets.csv` (pet_id, owner_id, name, weight_kg, coat), `owners.csv` (owner_id, name), `groomers.csv` (groomer_id, name) and `prices.json` (bands, coat_pct, addons, matting_per_15, multi_pet_pct). All owners, pets and groomers are synthetic; amounts are in dollars. These rules are the salon's policy; where `front-desk-note.txt` disagrees, the rules win. Rules: - Band: a pet's band is the first entry in bands whose max_kg is at least its weight_kg (null = no limit); base = the band's base plus coat_pct for the pet's coat, rounded half-up to the cent. - Same-day discount: when one owner has two or more appointments on the same date, each of them except the one with that owner's lowest appt_id that date gets multi_pet_pct off its base, rounded half-up to the cent; add-ons and matting are never discounted. - Extras: add-ons is a semicolon-separated list (blank = none), each charged at its addons price; matting is charged at matting_per_15 for each started 15 minutes of matting_min (0 = none); extras = add-ons + matting. - Write `out/grooming.json`: `{"appointments": {"<appt_id>": {"band": "<band>", "base": <dollars>, "discount": <dollars>, "extras": <dollars>, "total": <base − discount + extras>}, ...}, "owners": {"<owner_id>": <sum of the owner's appointment totals>, ...}, "groomers": {"<groomer_id>": <number of appointments>, ...}}`. `appointments` has one entry per row of appointments.csv. - Roll-ups: Owners in owners.csv with no appointments are left out. Groomers in groomers.csv with no appointments are included at 0. ## 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.

Price a synthetic grooming salon's appointments. Pets fall in weight bands (some weights sit exactly on a band limit), coats add a percent, owners with several pets in on the same day get a discount on all but their first appointment, and add-ons and matting time are extras. The prompt says owners with no appointments are left out and idle groomers are listed at 0. A front-desk note gets the discount, matting and roll-up rules wrong. 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: size_band same_day_discount extras owner_totals groomer_counts

Setup notes: Batch 39 case tk03-pet-grooming-invoices (offline, synthetic inputs, seed 1727423892). 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 0.36 (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-sonnet-5.5: $0.050025. 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: 12s
Human step-ins: 0
Turns: 3

Model usage
Model	Input tok	Output tok	Cost
AClaude Sonnet 5.5anthropic/claude-sonnet-5.5effort default (no --effort flag) · thinking on	59,100	1,201	$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: size_band same_day_discount extras owner_totals groomer_counts
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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  "stop_reason": "end_turn",
  "session_id": "[REDACTED]",
  "total_cost_usd": 0.050024500000000006,
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   "cache_read_input_tokens": 50865,
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   "output_tokens_details": {
    "thinking_tokens": 0
   },
   "server_tool_use": {
    "web_search_requests": 0,
    "web_fetch_requests": 0
   },
   "service_tier": "standard",
   "cache_creation": {
    "ephemeral_1h_input_tokens": 8229,
    "ephemeral_5m_input_tokens": 0
   },
   "inference_geo": "global",
   "iterations": [
    {
     "input_tokens": 2,
     "output_tokens": 248,
     "cache_read_input_tokens": 19641,
     "cache_creation_input_tokens": 1127,
     "cache_creation": {
      "ephemeral_5m_input_tokens": 0,
      "ephemeral_1h_input_tokens": 1127
     },
     "type": "message"
    }
   ],
   "speed": "standard",
   "fallback_credit": null
  },
  "modelUsage": {
   "claude-sonnet-5-5": {
    "inputTokens": 6,
    "outputTokens": 1201,
    "cacheReadInputTokens": 50865,
    "cacheCreationInputTokens": 8229,
    "webSearchRequests": 0,
    "costUSD": 0.050024500000000006,
    "contextWindow": 1000000,
    "maxOutputTokens": 128000,
    "thinkingTokens": 0,
    "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,
    "foreground": 0,
    "unset": 0
   },
   "started_in_background": 0,
   "max_depth": 0,
   "spawned_by_subagents": 0,
   "completed": 0,
   "failed": 0,
   "killed": {
    "parent": 0,
    "user": 0,
    "system": 0
   },
   "refused": {
    "depth_limit": 0,
    "concurrency_limit": 0,
    "budget": 0
   },
   "by_type": {}
  },
  "safety_stops": 0,
  "is_error": false,
  "num_turns": 3,
  "subtype": "success",
  "api_error_status": null,
  "result": "I wrote `out/grooming.json` with one entry for each of the 10 rows in `appointments.csv`. I spot-checked the first four entries in the output. I didn't check the rest or the owner and groomer roll-ups.\n\nI followed the written rules wherever `front-desk-note.txt` disagreed with them:\n- **Multi-pet discount:** only the owner's lowest appt_id that day is exempt, not everyone on a multi-pet day.\n- **Matting:** each started 15 minutes is charged, so 16 minutes counts as two blocks.\n- **Roll-ups:** owners with no appointments are left out, and groomers with no appointments are included at 0.\n\nThe script that produced the file is `/tmp/g.py`, outside `out/`.",
  "ttft_ms": 2372,
  "type": "result",
  "duration_ms": 11374,
  "uuid": "[REDACTED]",
  "ttft_stream_ms": 1969,
  "time_to_request_ms": 176,
  "first_content_frame_ms": 1970,
  "queued_turn_count": 0,
  "result_index": 0
 }
]