Claude Haiku 5.5 (effort default (no --effort flag) · thinking on) on Q1 budget-vs-actual variance table and CFO memo from a raw ledger (out-of-period lines, intercompany, legacy codes, reversals)

AClaude Haiku 5.5default · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-19 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first tryCompare

Estimated cost: $0.0079
Wall time: 27s
Human step-ins: 0
Outcome: Pass

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Exact prompt

# Task: Q1 budget variance report and memo Finance needs a Q1 2026 budget-vs-actual review. You have `budget.csv` (Q1 budget per department), `ledger.csv` (raw expense lines) and `dept_remap.csv` (legacy department codes still used by some systems). Produce `variance.csv` and `memo.md` in this directory. You may use any method (script or by hand). No network. ## Rules for actuals 1. Only ledger lines dated 2026-01-01 to 2026-03-31 inclusive count; lines dated outside Q1 are excluded whatever their memo says. 2. Lines whose `account` starts with `9` are intercompany transfers and are excluded. 3. A `dept_code` listed as a `legacy_code` in `dept_remap.csv` belongs to the mapped `dept_code`. 4. Amounts may contain thousands separators; an amount in parentheses, e.g. `(1,250.00)`, is negative (a reversal/credit) and reduces the total. ## variance.csv 5. Header `dept_code,budget,actual,variance,variance_pct`, one row per department in `budget.csv`, sorted by `dept_code`. 6. `variance = actual - budget` (positive = overspent). `variance_pct = variance / budget x 100`, rounded half-up to 1 decimal. Money columns with exactly 2 decimals; no `$`, `%` or thousands separators; negative numbers with a leading `-`. Every value must equal the exact result rounded as stated. ## memo.md 7. At most 200 words (counted as whitespace-separated tokens), written for the CFO. 8. It must name the three departments with the highest positive `variance_pct` using their `dept_name` from `budget.csv`, and the first mention of each of those three names must appear in descending order of overspend. Each of the three must be accompanied somewhere in the memo by its percentage written with a sign and one decimal followed by `%`, e.g. `+16.4%`. 9. It must also name the department with the lowest (most negative) `variance_pct` and give its percentage in the same format, e.g. `-7.2%`. 10. Optional (reported, not scored): a line starting with `Recommendation:`. The grader compares `variance.csv` with the correct values and checks `memo.md` against rules 7-9.

Each department has an out-of-period accrual, an intercompany line and a reversal pair; three departments use legacy codes. Missing any rule changes the variance table and usually the top-3 ranking the memo must report. 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. variance_csv_correct: all 8 rows exact (2-decimal money, 1-decimal pct). 2. memo_word_limit: 1-200 whitespace tokens. 3. memo_top3_in_order: the three largest overspenders named in descending order, each with its signed percentage. 4. memo_names_largest_underspend: the largest underspender named with its signed percentage.

Setup notes: Use Case Scout batch 7 case g08-budget-variance-memo (offline fixture). Prepared with batch7/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`. Tools: Read/Write/Edit/Glob/Grep/Bash, web disabled. Single run, no retries. Claude Code's own reported cost for claude-haiku-5.5: $0.007935. Score: 4/4 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: $0.0079
Wall time: 27s
Human step-ins: 0
Turns: 8

Model usage
Model	Input tok	Output tok	Cost
AClaude Haiku 5.5anthropic/claude-haiku-5.5effort default (no --effort flag) · thinking on	211,138	4,925	$0.0079

Reproduce this run

Use the use case prompt on the use case page.
Same setup: Claude Haiku 5.5 (anthropic/claude-haiku-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: 1. variance_csv_correct: all 8 rows exact (2-decimal money, 1-decimal pct). 2. memo_word_limit: 1-200 whitespace tokens. 3. memo_top3_in_order: the three largest overspenders named in descending order, each with its signed percentage. 4. memo_names_largest_underspend: the largest underspender named with its signed percentage.
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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  "result": "I wrote `variance.csv` and `memo.md` in the work directory. The memo is 125 words, under the 200-word limit.\n\n**Variance by department** (budget / actual / variance / %):\n\n| Dept | Budget | Actual | Variance | % |\n|---|---|---|---|---|\n| ENG | 420,000.00 | 433,020.00 | 13,020.00 | 3.1 |\n| FIN | 70,000.00 | 68,530.00 | -1,470.00 | -2.1 |\n| HR | 60,000.00 | 65,340.00 | 5,340.00 | 8.9 |\n| LEG | 45,000.00 | 47,115.00 | 2,115.00 | 4.7 |\n| MKT | 180,000.00 | 209,520.00 | 29,520.00 | 16.4 |\n| OPS | 140,000.00 | 121,380.00 | -18,620.00 | -13.3 |\n| SAL | 260,000.00 | 241,280.00 | -18,720.00 | -7.2 |\n| SUP | 95,000.00 | 106,210.00 | 11,210.00 | 11.8 |\n\n**Method:** I wrote a Python script using exact Decimal arithmetic. It kept only lines dated 2026-01-01 to 2026-03-31, dropped the 8 account-9xxx lines and the 16 out-of-quarter lines, mapped the legacy codes (MKT-OLD, CS, PEOPLE), and read parenthesised amounts as negatives. Percentages are rounded half-up to one decimal. The script is in `scripts/variance.py`, outside the work directory.\n\n**Memo:** It names Marketing (+16.4%), Customer Support (+11.8%) and People Operations (+8.9%) in descending overspend order, and gives Operations at -13.3% as the lowest percentage. It also gives the company-wide total, which I checked against the CSV: $1,292,395.00 actual against $1,270,000.00 budget, +1.8%. My first draft of the memo had the wrong totals, and I corrected it before finishing.\n\nThe memo ends with a `Recommendation:` line, which is optional.",
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