Skip to content

Claude Haiku 5.5 (effort default (no --effort flag) · thinking on) on Price garden centre till baskets with mixed 3-for-2 groups, 2-for-a-price bags, a spend coupon and loyalty points

AClaude Haiku 5.5default · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-22 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first try
Estimated cost
$0.0045
Wall time
17s
Human step-ins
0
Outcome
Pass

Compare with other models on this task →

Summary

Exact prompt

# Price a garden centre's till baskets with multibuy offers Inputs: `baskets.csv` (one row per product line in each basket: basket id, sku, quantity), `products.csv` (shelf price and offer group of each sku) and `offers.json` (what each offer group means, and the coupon). Every amount is in pounds. Pricing rules, per basket: - 3 for 2: put every unit from the same 3-for-2 offer group in the basket in one list (different skus in a group mix), sorted by price from highest to lowest; every third unit in that list is free. - 2 for a fixed price: put every unit of the group in one list sorted by price from highest to lowest and pair them off from the top; each pair costs the group's pair price, and a leftover unit pays its own price. - Products with no offer group pay their shelf price. - Coupon: 5.00 off when the basket total after offers is 40.00 or more. - Loyalty points: 1 point per whole pound of the amount paid. Write `out/baskets.json`: `{"three_for_two_savings": {"<basket_id>": <saving from 3-for-2 groups>, ...}, "pair_savings": {"<basket_id>": <saving from 2-for-a-price groups>, ...}, "offer_savings": {"<basket_id>": <shelf total minus total after offers>, ...}, "paid": {"<basket_id>": <amount paid after offers and coupon>, ...}, "points": {"<basket_id>": <integer>, ...}, "total_paid": <sum of paid>}` with every basket. ## 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.

Reprice a day's till baskets under written offer rules. Units in a 3-for-2 group are pooled across skus with every third cheapest-in-turn unit free, bagged goods pair off from the most expensive at a fixed pair price, a coupon applies on the post-offer total, and points are whole pounds paid. Applying 3 for 2 per sku, pairing the cheapest first or testing the coupon before offers each change the baskets. 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: three_for_two_across_group pairs_from_the_top coupon_after_offers loyalty_points

Setup notes: Batch 24 case z03-multibuy-basket-pricing (offline, synthetic inputs, seed 3198213749). 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 0.39 (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-haiku-5.5: $0.004549. 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
$0.0045
Wall time
17s
Human step-ins
0
Turns
4
Model usage
ModelInput tokOutput tokCost
AClaude Haiku 5.5anthropic/claude-haiku-5.5effort default (no --effort flag) · thinking on86,0852,872$0.0045

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: three_for_two_across_group pairs_from_the_top coupon_after_offers loyalty_points
  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.

Was this useful?

⇄ Rerun on another model

Automated checks

Trust 80% comes from these checks (how Trust % works).

Evidence log
[
 {
  "duration_api_ms": 16509,
  "stop_reason": "end_turn",
  "session_id": "[REDACTED]",
  "total_cost_usd": 0.004549259999999999,
  "usage": {
   "input_tokens": 8,
   "cache_creation_input_tokens": 11851,
   "cache_read_input_tokens": 74226,
   "output_tokens": 2872,
   "output_tokens_details": {
    "thinking_tokens": 876
   },
   "server_tool_use": {
    "web_search_requests": 0,
    "web_fetch_requests": 0
   },
   "service_tier": "standard",
   "cache_creation": {
    "ephemeral_1h_input_tokens": 11851,
    "ephemeral_5m_input_tokens": 0
   },
   "inference_geo": "global",
   "iterations": [
    {
     "input_tokens": 2,
     "output_tokens": 679,
     "cache_read_input_tokens": 21783,
     "cache_creation_input_tokens": 2607,
     "cache_creation": {
      "ephemeral_5m_input_tokens": 0,
      "ephemeral_1h_input_tokens": 2607
     },
     "type": "message"
    }
   ],
   "speed": "standard",
   "fallback_credit": null
  },
  "modelUsage": {
   "claude-haiku-5-5": {
    "inputTokens": 8,
    "outputTokens": 2872,
    "cacheReadInputTokens": 74226,
    "cacheCreationInputTokens": 11851,
    "webSearchRequests": 0,
    "costUSD": 0.004549259999999999,
    "contextWindow": 1000000,
    "maxOutputTokens": 128000,
    "thinkingTokens": 876,
    "canonicalModel": "claude-haiku-5-5",
    "provider": "firstParty",
    "costBasis": "list"
   }
  },
  "permission_denials": [],
  "terminal_reason": "completed",
  "fast_mode_state": "off",
  "fast_mode_disabled_reason": "sdk_opt_in_required",
  "subagent_stats": {
   "spawned": 0,
   "requested": {
    "background": 0,
    "foreground": 0,
    "unset": 0
   },
   "started_in_background": 0,
   "max_depth": 0,
   "spawned_by_subagents": 0,
   "completed": 0,
   "failed": 0,
   "killed": {
    "parent": 0,
    "user": 0,
    "system": 0
   },
   "refused": {
    "depth_limit": 0,
    "concurrency_limit": 0,
    "budget": 0
   },
   "by_type": {}
  },
  "safety_stops": 0,
  "is_error": false,
  "num_turns": 4,
  "subtype": "success",
  "api_error_status": null,
  "result": "I wrote `out/baskets.json` with all 11 baskets (T40210\u2013T40240). The total paid is \u00a3971.65.\n\nI priced each basket with a script kept outside `out/`, using exact decimal arithmetic. The script asserts that shelf total minus offer savings equals the after-offer total, and I spot-checked two baskets by hand (T40219 and T40237) and they matched.\n\nChoices I made where the task was open:\n- **Coupon:** applied to the after-offer total when it is 40.00 or more, and not counted in `offer_savings`.\n- **Points:** rounded down (floor) to whole pounds of the amount paid.\n- **Pair groups:** a pair's saving is its shelf value minus the \u00a314.00 pair price. A leftover unit pays its own price.\n\nI did not check the output against any expected values, so I have no pass/fail result beyond these internal checks.",
  "ttft_ms": 1574,
  "type": "result",
  "duration_ms": 16864,
  "uuid": "[REDACTED]",
  "ttft_stream_ms": 1392,
  "time_to_request_ms": 227,
  "first_content_frame_ms": 1392,
  "queued_turn_count": 0,
  "result_index": 0
 }
]

Get new runs and ranking changes weekly