Claude Opus 5.5 (effort default (no --effort flag) · thinking on) on Rebalance to target weights with whole shares and highest-cost-first tax lots

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

Trust 80%Fully autonomoussuccess · first tryCompare

Estimated cost: $0.15
Wall time: 24s
Human step-ins: 0
Outcome: Pass

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Exact prompt

# Rebalance to target weights with whole shares and highest-cost-first tax lots `input.json` is a **synthetic** portfolio: cash, prices, target weights and the tax lots held. Write `solve.py` (Python 3 standard library only) so that `python solve.py input.json answer.json` plans the rebalancing trades and their tax effect. Nothing is traded; this only computes a plan. We re-run it on fresh inputs, so do not hard-code anything. ## Input `as_of` (ISO date), `cash`, `prices` (symbol -> price), `targets` (symbol -> weight; weights sum to 1; a held symbol missing from `targets` has target 0; a target symbol may have no lots), `lots` (each `{"id", "symbol", "shares", "cost_per_share", "acquired"}`), `short_term_rate`, `long_term_rate`. ## Rules 1. Use `decimal.Decimal` for money (convert numbers with `Decimal(str(x))`); round with ROUND_HALF_UP to cents when writing. 2. total_value = cash + sum over symbols of (shares held * price). Current value and target value (= weight * total_value) of each symbol are computed once, before any trade. 3. Work through symbols in alphabetical order. **Sells first:** if current > target, sell floor((current - target) / price) shares (never more than held). Then **buys**, again alphabetically: if target > current, buy floor(min(target - current, cash available now) / price) shares, where cash available includes all sale proceeds and decreases with each buy. No fees. 4. Lots for a sale are used highest `cost_per_share` first, ties by earlier `acquired`, then by `id`; a lot can be partly sold. 5. A lot slice's gain = (price - cost_per_share) * shares sold. It is long-term if (as_of - acquired) in days is greater than 365, otherwise short-term. 6. realized_short_term and realized_long_term are the sums of gains (can be negative). estimated_tax = max(realized_short_term, 0) * short_term_rate + max(realized_long_term, 0) * long_term_rate (no netting between the two). 7. weights_after[symbol] = shares held after trades * price / total_value (6 decimals), for every symbol that is held or targeted. ## Output `answer.json`: ``` {"total_value": ..., "trades": [{"symbol", "side": "sell"|"buy", "shares"}, ...] sorted by symbol then side, "lot_sales": [{"lot_id", "shares", "gain", "term": "short"|"long"}, ...] in the order lots are used (symbols alphabetically), "realized_short_term": ..., "realized_long_term": ..., "estimated_tax": ..., "cash_after": ..., "weights_after": {symbol: weight}} ``` Only trades with at least 1 share are listed. ## Scoring Hidden checks (partial credit = fraction passed; all must pass), money within 0.011, weights within 0.000001, shares and labels exact: `trades` (with total_value), `lot_selection`, `gains_and_tax`, `cash_and_weights` on the given input; `fresh_run_1` and `fresh_run_2_sell_out` (a symbol with target 0 must be sold out; lots held exactly 365 and 366 days appear) on fresh inputs. Each run has a 60-second limit.

Sells before buys with cash carried, floor to whole shares, lot order with ties, the 365-vs-366-day holding boundary, a held symbol with no target, and no netting in the tax estimate. 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).

These are synthetic test cases for comparing AI models, not financial advice.

Success criteria: 1. trades 2. lot_selection 3. gains_and_tax 4. cash_and_weights 5. fresh_run_1 6. fresh_run_2_sell_out

Setup notes: Use Case Scout batch 9 case j12-rebalance-tax-lots (offline fixture). Prepared with batch9/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-opus-5.5: $0.15096. Score: 6/6. 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: $0.15
Wall time: 24s
Human step-ins: 0
Turns: 5

Model usage
Model	Input tok	Output tok	Cost
AClaude Opus 5.5anthropic/claude-opus-5.5effort default (no --effort flag) · thinking on	81,842	2,745	$0.15

Reproduce this run

Use the use case prompt on the use case page.
Same setup: Claude Opus 5.5 (anthropic/claude-opus-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. trades 2. lot_selection 3. gains_and_tax 4. cash_and_weights 5. fresh_run_1 6. fresh_run_2_sell_out
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 `solve.py` and ran it on `input.json`, which produced `answer.json`. It uses only the standard library and doesn't hard-code anything.\n\n**Result on the given input:**\n- **Total value:** $329,077.48.\n- **Trades:** sell 345 GLD, then buy 9 AAA, 134 EMK and 212 TIPS.\n- **Lots sold:** L005 (277 shares) and L006 (68 shares). Both are short-term, for a realized short-term gain of $12,301.29.\n- **Tax and cash:** estimated tax is $3,936.41, and $303.43 of cash is left after the trades.\n- **Weights after:** each is within about 0.001 of its target.\n\nI also ran a small made-up case for the sell-out scenario. A symbol with target 0 was sold out completely. A lot held exactly 366 days came out long-term and one held 365 days came out short-term. A target symbol with no lots was bought.\n\nTwo assumptions you should know about:\n- **Prices:** the script assumes every held or targeted symbol has a price in `prices`. If one is missing, it stops with an error.\n- **Share counts:** whole numbers are written as integers. Fractional lot sizes would come out as decimals.",
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