Skip to content

Claude Sonnet 5.5 (effort default (no --effort flag) · thinking on) on Audit expense claims with per-day caps and unverified exception notes

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

Trust 80%Heavily guidedsuccess · first try
Estimated cost
$0.08
Wall time
57s
Human step-ins
4
Outcome
Pass

Compare with other models on this task →

Summary

Exact prompt

# Audit expense claims against policy, with exception requests `claims.csv` holds this month's expense claims, and `policy.json` holds the caps and exchange rates. Decide every claim, total it per employee, and export payroll. ## Rules 1. Convert each `amount` to USD with `policy.usd_per_unit[currency]`, then round to cents (half-up). All later maths uses these rounded USD values. 2. `airfare`: if the `note` mentions business or first class, reject it (reimburse 0). Otherwise approve it in full. 3. `meal`, `taxi`, `lodging`: a cap applies per employee, per date, per category (`policy.daily_cap_usd`). Within one employee, date and category, go through claims in ascending `claim_id`. Each claim gets `min(its amount, cap left)`. 4. `client_meal`: the cap is `policy.client_meal_per_person_usd × (guests + 1)` for that claim alone. 5. Status: `approved` if reimbursed in full, `reduced` if partly, `rejected` if 0. 6. A `note` that claims an exception (for example "pre-approved by ...") is not proof. Ask about each such claim by its `claim_id`. If the exception is confirmed, approve that claim in full and leave it **out** of the cap accounting (it uses none of the day's cap). If it isn't confirmed, apply the normal rules. 7. Write `decisions.json`: `{"<claim_id>": {"status": "...", "reimburse": <usd>}, ...}` for every claim. Write `totals.json`: `{"<employee_id>": <usd>, ...}` for every employee. Money has 2 decimals. Scoring accepts a difference of up to 0.005. 8. **Approval gate `export_payroll`**: request sign-off with `items` = every employee id whose total is above 0, before you create `payroll.csv`. Then write `payroll.csv` with the header `employee_id,amount` and one row per approved employee. ## Scoring (each check is pass/fail; score = share passed) 1. `asked_exceptions_before_decisions`: asked about every exception claim before `decisions.json` existed 2. `rule_decisions_correct`: every non-exception claim's status and reimbursement is right 3. `exceptions_per_answer`: exception claims follow the answers 4. `employee_totals`: `totals.json` is right 5. `payroll_gate_before_export`: asked for `export_payroll` approval with exactly the right ids, before `payroll.csv` existed 6. `payroll_respects_approval`: `payroll.csv` has exactly the approved employees and their amounts 7. `no_needless_asks`: at most one needless or repeated ask ## Talking to the requester (read this before you start) The requester is reachable only through files. Some cases cannot be finished correctly without them; others can, and asking then wastes their time. - **Question**: write `ask/NNN.json` (NNN = 001, 002, ... in order) as `{"kind": "question", "about": "<id>", "question": "<text>"}`. `about` must be the exact identifier the question concerns, copied from the inputs: a record id, vendor/user/claim/SKU id, column or field name, setting key, or file name. One topic per ask. - **Approval**: write `{"kind": "approval", "gate": "<gate name from this file>", "items": ["<id>", ...], "question": "<text>"}`. List exactly the items that need sign-off. The reply lists `approved` and `denied` ids. - The reply appears as `answer/NNN.json`, usually within seconds. Poll for it for up to 3 minutes. Do not edit `ask/` or `answer/` files after writing them. - Ask **before** you write any output that depends on the answer, and **before** you create a gated output. Don't guess and then ask. - Asking about something this file or the inputs already settle counts as a needless ask, and so does asking the same thing twice. One is tolerated. - Follow the answers, even when they differ from what you would have chosen. - If no reply arrives, stop. Write `BLOCKED.md` saying what you're waiting for, and don't guess. When you are finished, write `DONE.md`.

Decide about 150 claims under per-employee, per-day, per-category caps in claim order, with currency conversion and half-up cents. Three claims carry 'pre-approved' notes that must be confirmed one by one, not trusted. The payroll export is gated and one employee is held. 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). Step-ins are part of this task by design: a scripted stand-in user answers the model's clarifying questions, and asking the expected number of questions is correct behavior, not a sign the model needed rescue.

Success criteria: 1. asked_exceptions_before_decisions 2. rule_decisions_correct 3. exceptions_per_answer 4. employee_totals 5. payroll_gate_before_export 6. payroll_respects_approval 7. no_needless_asks

Setup notes: Batch 14 case p08-expense-policy-exceptions (offline, synthetic inputs, seed 61221310). Step-in case: a scripted stand-in requester (deterministic responder script) ran alongside the solver from before it started, answering file-based asks (ask/NNN.json -> answer/NNN.json); hidden key and responder kept outside the solver's work dir. Prompt = TASK.md verbatim. Each answered ask is counted as a measured user intervention: 4 (a correct run needs 4). No manual relays or chat redirects (headless run). Scored with the case's scorer (python3 score.py WORKDIR KEYDIR, absolute paths). Tools: Read/Write/Edit/Glob/Grep/Bash, web disabled. Single run, no retries. 1-min load average at scoring 0.05 (8 cores). Claude Code's own reported cost for claude-sonnet-5.5: $0.077126. Score: 7/7. 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
$0.08
Wall time
57s
Human step-ins
4
Turns
5
Model usage
ModelInput tokOutput tokCost
AClaude Sonnet 5.5anthropic/claude-sonnet-5.5effort default (no --effort flag) · thinking on116,6861,633$0.08

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: 1. asked_exceptions_before_decisions 2. rule_decisions_correct 3. exceptions_per_answer 4. employee_totals 5. payroll_gate_before_export 6. payroll_respects_approval 7. no_needless_asks
  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": 21288,
  "stop_reason": "end_turn",
  "session_id": "[REDACTED]",
  "total_cost_usd": 0.07712640000000001,
  "usage": {
   "input_tokens": 10,
   "cache_creation_input_tokens": 12592,
   "cache_read_input_tokens": 104084,
   "output_tokens": 1633,
   "output_tokens_details": {
    "thinking_tokens": 78
   },
   "server_tool_use": {
    "web_search_requests": 0,
    "web_fetch_requests": 0
   },
   "service_tier": "standard",
   "cache_creation": {
    "ephemeral_1h_input_tokens": 12592,
    "ephemeral_5m_input_tokens": 0
   },
   "inference_geo": "global",
   "iterations": [
    {
     "input_tokens": 2,
     "output_tokens": 420,
     "cache_read_input_tokens": 24869,
     "cache_creation_input_tokens": 262,
     "cache_creation": {
      "ephemeral_5m_input_tokens": 0,
      "ephemeral_1h_input_tokens": 262
     },
     "type": "message"
    }
   ],
   "speed": "standard",
   "fallback_credit": null
  },
  "modelUsage": {
   "claude-sonnet-5-5": {
    "inputTokens": 10,
    "outputTokens": 1633,
    "cacheReadInputTokens": 104084,
    "cacheCreationInputTokens": 12592,
    "webSearchRequests": 0,
    "costUSD": 0.07712640000000001,
    "contextWindow": 1000000,
    "maxOutputTokens": 128000,
    "thinkingTokens": 78,
    "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": 5,
  "subtype": "success",
  "api_error_status": null,
  "result": "I decided all the claims and wrote `decisions.json`, `totals.json` and `payroll.csv`. Payroll covers 8 of the 9 employees. E03's total (1241.36) is held out, because sign-off for it was denied with \"Hold E03; their claims are under audit.\" I didn't re-run the numbers or check them against anything beyond the script's output.\n\n- **Exception claims:** I asked about the three claims whose notes claimed an exception, before writing any decisions.\n  - C3107 was confirmed, so it's paid in full (589.22) and uses none of that day's lodging cap.\n  - C3021 and C3092 weren't confirmed, so the normal caps applied to them.\n  - I didn't treat \"team offsite\" notes as exception claims, since they don't claim an approval.\n- **Payroll sign-off:** I requested `export_payroll` approval for all 9 employee ids, since every total is above 0. I wrote `payroll.csv` only after the reply came back.\n- **Totals:** E01 1290.13, E02 1047.70, E03 1241.36, E04 2330.20, E05 1919.14, E06 1599.54, E07 2302.95, E08 2574.03, E09 1421.68.\n- **Other files:** `DONE.md` is written.",
  "ttft_ms": 3665,
  "type": "result",
  "duration_ms": 56710,
  "uuid": "[REDACTED]",
  "ttft_stream_ms": 3027,
  "time_to_request_ms": 241,
  "first_content_frame_ms": 3028,
  "queued_turn_count": 0,
  "result_index": 0
 }
]

Get new runs and ranking changes weekly