Claude Sonnet 5.5 (effort default (no --effort flag) · thinking on) on Report quarter-end headcount and attrition from an effective-dated HR export with corrections, rehires, future-dated leavers and contractors

AClaude Sonnet 5.5default · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-21 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first tryCompare

Estimated cost: $0.06
Wall time: 15s
Human step-ins: 0
Outcome: Pass

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Exact prompt

# Quarter-end headcount and attrition from the HR system export Inputs: `job_history.csv` (one row per change to a worker's record: each row is the full state of the record from its effective date) and `request.json` (the reporting date and window). Report headcount and FTE by department as of the reporting date, and voluntary attrition over the trailing 12 months. - A record's state on a date is its row with the latest effective date on or before that date. Rows effective after that date haven't happened yet. - When two rows share an employee and an effective date, the one entered later is a correction and replaces the other. - Count people, not employee ids: someone who left and came back has a new employee id but the same person id. Contractors are not headcount. - Voluntary attrition = voluntary leavers in the window / average of the headcount at the window's start date and at the reporting date x 100. A leaver is a person whose employee record changes to terminated with a voluntary reason and an effective date inside the window (after the start date, on or before the reporting date). A person who left and was rehired within the window still counts as a leaver. Write `out/headcount.json`: `{"headcount_by_dept": {"<dept>": <n>, ...}, "fte_by_dept": {"<dept>": <sum, 2 decimals>, ...}, "total_headcount": <n>, "voluntary_leavers": <n>, "voluntary_attrition_pct": <2 decimals half-up>}`. Leave out departments with no headcount. ## 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.

Reconstruct each worker record as of a reporting date from about 300 shuffled snapshot rows. Same-day corrections (including rescinded terminations) replace earlier entries, terminations dated after the reporting date have not happened, rehired people carry a new employee id, and contractors are mixed in. Taking each id's latest row, ignoring corrections, or counting ids instead of people each gives a different headcount or attrition rate. 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). Folder-restore note: this run's output files under work/out/ were lost in a 1:22 AM ET restore on Oct 21, 2026. The trace, step-in exchanges and output-hash list were checked against the recorded SHA-256 values and match; the hashes of the individual output files inside that list can no longer be recomputed. Measured data unchanged.

Success criteria: headcount fte as_of_and_corrections attrition

Setup notes: Batch 19 case u06-effective-dated-headcount (offline, synthetic inputs, seed 372520621). 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 0.31 (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: $0.055019. Score: 4/4. 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: $0.06
Wall time: 15s
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	58,141	1,804	$0.06

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: headcount fte as_of_and_corrections attrition
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 `out/headcount.json`. At 2026-09-30 there are 68 people on headcount, with 2 voluntary leavers in the window and attrition of 3.05%.\n\n| Department | Headcount | FTE |\n|---|---|---|\n| Engineering | 10 | 8.30 |\n| Support | 12 | 10.70 |\n| Sales | 17 | 14.10 |\n| People | 17 | 14.40 |\n| Finance | 4 | 3.60 |\n| Operations | 8 | 5.60 |\n\nHeadcount at the window start (2025-09-30) was 63, so the average is 65.5 and 2 \u00f7 65.5 \u00d7 100 = 3.05.\n\n- **Headcount:** I took each employee record's state on the date, ignoring rows effective after it. I kept only active, non-contractor records and counted each person once. My script printed nothing for the check on people holding two active ids, so none turned up.\n- **Corrections:** Where two rows shared an employee and effective date, I kept the one entered later.\n- **Leavers:** A leaver is a person whose employee record goes from active to terminated with a voluntary reason, effective after 2025-09-30 and on or before 2026-09-30. I counted each person once. Contractor terminations are excluded.",
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