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Claude Sonnet 5.5 (effort default (no --effort flag) · thinking on) on Spreadsheet-grade loan amortization for 8 loans incl. rate reset and extra payments

AClaude Sonnet 5.5default · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-16 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first try
Estimated cost
$0.05
Wall time
19s
Human step-ins
0
Outcome
Pass

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Summary

Exact prompt

# Task: loan amortization (spreadsheet-grade precision) `loans.csv` lists 8 loans: principal, annual_rate_pct (nominal, compounded monthly), years, extra_monthly (extra principal paid each month from `extra_from_month` on, 1-based), optional `rate_reset_month` + `new_rate_pct`. Rules (follow exactly, use decimal arithmetic, round HALF-UP to cents at each step): 1. Scheduled payment = P·i/(1−(1+i)^−n) with i = rate/12/100, n = years·12, rounded to cents. If rate is 0, payment = P/n rounded. 2. Each month: interest = round(balance·i); principal part = payment − interest; plus the extra payment if active. 3. If principal part + extra ≥ remaining balance, the final payment = interest + remaining balance (no extra that month) and the loan ends. 4. At `rate_reset_month` (before computing that month's interest), switch to the new rate and recompute the payment on the current balance over the ORIGINAL remaining term (n − reset_month + 1 months). Write `results.json`: {"L1": {"monthly_payment": "1234.56" (the initial scheduled payment, string), "total_interest": "…" (string, 2dp), "payoff_month": int}, ...} and `L3_schedule.csv` with header `month,payment,interest,principal,balance` (payment includes extra; principal includes extra; strings with 2dp). No network.

Exact-to-the-cent with HALF_UP per-step rounding, 0% loans, final-payment adjustment (one 60-month loan pays off in month 61 due to rounding), payment recompute at rate reset. 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: 1. For each of the 8 loans: monthly_payment and total_interest must equal the key exactly to the cent (Decimal compare), and payoff_month must be exactly right. 2. L3_schedule.csv must have header month,payment,interest,principal,balance and the exact number of rows, with every month and every amount matching exactly.

Setup notes: Use Case Scout batch 4 case d09-loan-amortization-finance (offline fixture). Prepared with batch4/prepare.sh; hidden key/tests kept outside the agent's work dir. Prompt = TASK.md verbatim. Scored with the scout's scorer: `python score.py WORKDIR KEYDIR/key.json`. Tools: Read/Write/Edit/Glob/Grep/Bash, web disabled. Single run, no retries. Claude Code's own reported cost for claude-sonnet-5.5: $0.050253. Score: 2/2 checks. 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
19s
Human step-ins
0
Turns
3
Model usage
ModelInput tokOutput tokCost
AClaude Sonnet 5.5anthropic/claude-sonnet-5.5effort default (no --effort flag) · thinking on57,0451,519$0.05

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. For each of the 8 loans: monthly_payment and total_interest must equal the key exactly to the cent (Decimal compare), and payoff_month must be exactly right. 2. L3_schedule.csv must have header month,payment,interest,principal,balance and the exact number of rows, with every month and every amount matching exactly.
  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.

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Automated checks

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Evidence log
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  "result": "I wrote `results.json` and `L3_schedule.csv` in the working directory, following your rules with decimal arithmetic and half-up rounding to cents at each step. I haven't checked the figures against a spreadsheet.\n\n| Loan | Initial payment | Total interest | Payoff month |\n|---|---|---|---|\n| L1 | 666.67 | 0.00 | 180 |\n| L2 | 2734.25 | 429664.00 | 297 |\n| L3 | 42.46 | 1316.13 | 54 |\n| L4 | 2000.00 | 0.00 | 60 |\n| L5 | 184.75 | 30423.20 | 300 |\n| L6 | 5835.89 | 42814.62 | 61 |\n| L7 | 48.61 | 9498.22 | 360 |\n| L8 | 4171.56 | 300879.30 | 180 |\n\n- **L6:** it pays off in month 61, one month past its 60-month term. After the rate reset, rounding leaves a small balance that needs one more payment under your rules.\n- **L1:** the payment rounds up from 666.666\u2026, so the final payment is smaller than the others.\n\nI used the script at `../scripts/a.py` to generate both files.",
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 }
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