Skip to content

Claude Sonnet 5.5 (effort default (no --effort flag) · thinking on) on Work out a music teacher's term fees with credits for lessons the teacher missed and a sibling discount

AClaude Sonnet 5.5default · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-22 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first try
Estimated cost
$0.04
Wall time
15s
Human step-ins
0
Outcome
Pass

Compare with other models on this task →

Summary

Exact prompt

# Work out a music teacher's spring term fees Inputs: `pupils.csv` (each pupil: family, lesson minutes, lessons the teacher missed, lessons the pupil missed) and `rates.json` (the price of one lesson of each length and the number of lessons in the term). Every amount is in pounds. Fee rules: - Term fee = lessons in the term x the lesson price for the pupil's lesson length, minus a full-price credit for each lesson the teacher missed; lessons the pupil missed are not credited. - In a family with more than one pupil, every pupil except the one with the highest term fee gets 10% off their term fee (rounded to the cent half-up); a pupil with no brother or sister in pupils.csv gets no discount. - Due = term fee - sibling discount. Write `out/fees.json`: `{"term_fee": {"<pupil>": <term fee after credits>, ...}, "sibling_discount": {...}, "due": {...}, "family_total": {"<family>": <sum of due>, ...}}` with every pupil and family in `pupils.csv`. ## 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.

Work out a term's fees for music pupils from lesson lengths and missed-lesson counts. Lessons the teacher missed are credited, lessons the pupil missed are not, and in each family every pupil except the one with the highest fee gets 10% off. Crediting pupil absences, discounting every sibling or keeping the wrong sibling at full price each change the fees. 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: teacher_credits_only sibling_discount totals

Setup notes: Batch 25 case a04-music-tuition-term-fees (offline, synthetic inputs, seed 2316931278). 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 0.07 (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: $0.044703. Score: 3/3. 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
$0.04
Wall time
15s
Human step-ins
0
Turns
3
Model usage
ModelInput tokOutput tokCost
AClaude Sonnet 5.5anthropic/claude-sonnet-5.5effort default (no --effort flag) · thinking on57,123987$0.04

Reproduce this run

  1. Use the use case prompt on the use case page.
  2. 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.
  3. It counts as a success only if it meets every success criterion: teacher_credits_only sibling_discount totals
  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.

Was this useful?

⇄ Rerun on another model

Automated checks

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

Evidence log
[
 {
  "duration_api_ms": 14285,
  "stop_reason": "end_turn",
  "session_id": "[REDACTED]",
  "total_cost_usd": 0.044703299999999994,
  "usage": {
   "input_tokens": 6,
   "cache_creation_input_tokens": 7464,
   "cache_read_input_tokens": 49653,
   "output_tokens": 987,
   "output_tokens_details": {
    "thinking_tokens": 129
   },
   "server_tool_use": {
    "web_search_requests": 0,
    "web_fetch_requests": 0
   },
   "service_tier": "standard",
   "cache_creation": {
    "ephemeral_1h_input_tokens": 7464,
    "ephemeral_5m_input_tokens": 0
   },
   "inference_geo": "global",
   "iterations": [
    {
     "input_tokens": 2,
     "output_tokens": 226,
     "cache_read_input_tokens": 18763,
     "cache_creation_input_tokens": 1240,
     "cache_creation": {
      "ephemeral_5m_input_tokens": 0,
      "ephemeral_1h_input_tokens": 1240
     },
     "type": "message"
    }
   ],
   "speed": "standard",
   "fallback_credit": null
  },
  "modelUsage": {
   "claude-sonnet-5-5": {
    "inputTokens": 6,
    "outputTokens": 987,
    "cacheReadInputTokens": 49653,
    "cacheCreationInputTokens": 7464,
    "webSearchRequests": 0,
    "costUSD": 0.044703299999999994,
    "contextWindow": 1000000,
    "maxOutputTokens": 128000,
    "thinkingTokens": 129,
    "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've written `out/fees.json` with all four sections (`term_fee`, `sibling_discount`, `due`, `family_total`) covering all 9 pupils and 4 families. I didn't run any separate checks against the output.\n\nI did the arithmetic in exact decimals and rounded each discount half-up to the cent. No family has a tie for the highest term fee.\n\nThe family totals (sum of due) are:\n\n| Family | Total due |\n|---|---|\n| Delaney | \u00a3651.07 |\n| Grant | \u00a3547.36 |\n| Chowdhury | \u00a3667.71 |\n| Ashworth | \u00a3345.40 |\n\nJude Ashworth is the only pupil in their family, so they get no discount.",
  "ttft_ms": 3862,
  "type": "result",
  "duration_ms": 14639,
  "uuid": "[REDACTED]",
  "ttft_stream_ms": 3047,
  "time_to_request_ms": 243,
  "first_content_frame_ms": 3048,
  "queued_turn_count": 0,
  "result_index": 0
 }
]

Get new runs and ranking changes weekly