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Claude Haiku 5.5 (effort default (no --effort flag) · thinking on) on Answer 8 business questions against a SQLite shop database

AClaude Haiku 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
$0.0057
Wall time
22s
Human step-ins
0
Outcome
Pass

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Summary

Exact prompt

# Task: answer business questions from a SQLite database `shop.db` is a SQLite database (use python's sqlite3; inspect the schema yourself). Only orders with status 'shipped' count as sales. Revenue = qty * unit_price from order_items (NOT list_price). Write `answer.json` with keys q1..q8: - q1: total shipped revenue (round 2) - q2: customer country with the highest shipped revenue (2-letter code) - q3: product category with highest shipped revenue NET of returns (subtract returned qty * that line's unit_price) - q4: number of customers with zero shipped orders - q5: returned units / shipped units, over shipped orders only (round 4) - q6: month (YYYY-MM) with highest shipped revenue - q7: number of distinct discontinued products that appear in shipped orders dated on/after 2026-07-01 - q8: average shipped order value (round 2) Also write `queries.sql` with the SQL you used. No network.

Answer eight business questions from a small SQLite shop database. Traps include using the order line's unit price instead of the list price, counting only shipped orders, netting out returns per line, and finding customers with no shipped orders. 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. All 8 answers (q1–q8) must be correct: numeric answers within 0.01 (q5 within 0.0005); text answers exact match, case-insensitive. 2. Pass requires 8/8.

Setup notes: Use Case Scout batch 3 case c12-sqlite-business-questions (offline fixture). Prepared with batch3/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/answer.json KEYDIR/key.json`. Tools: Read/Write/Edit/Glob/Grep/Bash, web disabled. Single run, no retries. Claude Code's own reported cost for claude-haiku-5.5: $0.005722. Score: 8/8. 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
$0.0057
Wall time
22s
Human step-ins
0
Turns
5
Model usage
ModelInput tokOutput tokCost
AClaude Haiku 5.5anthropic/claude-haiku-5.5effort default (no --effort flag) · thinking on108,7484,616$0.0057

Reproduce this run

  1. Use the use case prompt on the use case page.
  2. 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.
  3. It counts as a success only if it meets every success criterion: 1. All 8 answers (q1–q8) must be correct: numeric answers within 0.01 (q5 within 0.0005); text answers exact match, case-insensitive. 2. Pass requires 8/8.
  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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   "server_tool_use": {
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    "canonicalModel": "claude-haiku-5-5",
    "provider": "firstParty",
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  "permission_denials": [],
  "terminal_reason": "completed",
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  "result": "I wrote `answer.json` and `queries.sql` in the working directory. Each answer comes from a query in `queries.sql`, and I ran every query against `shop.db`.\n\n```json\n{\n  \"q1\": 2520896.86,\n  \"q2\": \"DE\",\n  \"q3\": \"input\",\n  \"q4\": 2,\n  \"q5\": 0.0443,\n  \"q6\": \"2026-09\",\n  \"q7\": 3,\n  \"q8\": 994.44\n}\n```\n\nChoices I made where the request left room:\n- **Returns (q3, q5):** I only counted returns on shipped orders, since the sales base is shipped orders. Returns attached to cancelled or pending orders (121 units across 78 returns) are excluded.\n- **q3:** \"input\" wins whether or not returns are subtracted, so that answer doesn't depend on the choice above.\n- **q6:** September 2026 is the top month, but the data runs only to 2026-09-28, so September is a partial month. January 2026 is a close second ($315k vs. $313k).\n\nData checks: no null quantities or prices, no duplicate order lines, no orphaned foreign keys, and no returns larger than the quantity sold on that line.",
  "ttft_ms": 1421,
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 }
]

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