GPT-6.1 Sol (effort default (no reasoning-effort override) · thinking on) on Sailing regatta series scoring with codes, dead heats, redress, discards and tie-breaks
OGPT-6.1 Soldefault · thinking on · Codex CLI 0.163.0 (codex exec --json) · cloud · 2026-10-22 · by @bobsiopener
- Estimated cost
- $0.06
- Wall time
- 56s
- Human step-ins
- 0
- Outcome
- Pass
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Summary
Exact prompt
# Sailing regatta series scoring (low-point system) `input.json` (synthetic) has `entries` (`sail`), `races` (each with `finishes` in finishing order), `discards` ({"min races": discards}), and `penalty_pct`. Write `solve.py` (Python 3 standard library only); `python solve.py input.json answer.json` writes `answer.json` and `results.html`. Fresh series are generated. ## Rules (N = number of entries) 1. A finish item is `{"sail": s}` or `{"sail": [s1, s2, ...]}` (a dead heat), with optional `code` (case-insensitive) and `points`. Sails not in `entries` are ignored. A boat already seen in that race is ignored (only its first item counts). 2. Codes DNC, DNS, OCS, DNF, RET, DSQ, DNE, UFD, BFD score **N + 1** and do **not** take a finishing place (boats behind move up). 3. Other boats take places 1, 2, 3, ... in item order; a dead heat of k boats takes the next k places and each scores their average (e.g. 2.5). 4. ZFP and SCP: place points + round_half_up(N * penalty_pct / 100), capped at N + 1. DPI: place points + `points`, capped at N + 1. 5. RDG with `points`: that score. RDG without `points`: the average of that boat's scores in all other races, excluding its other averaged-RDG races, rounded half-up to 1 decimal; N + 1 if there are none. 6. An entry missing from a race's items scores N + 1 with code DNC. A boat's code for a race is the upper-cased code (`""` if none). 7. Discards: d = the value for the largest key k with races sailed >= k (0 if none). Exclude the boat's d worst scores, never a DNE score; among equal scores exclude the later race first. `total` = sum of all scores; `net` = total - excluded. 8. Ranking: lower net first. Ties: (A8.1) compare each boat's non-excluded scores sorted best to worst, first difference wins; (A8.2) then compare scores in the last race, then the race before, and so on (excluded scores included). Still tied: entry order. ## Visual output: results.html A static, self-contained page (no `<script>`, `<img>`, `<link>`, `<iframe>`/`<object>`/`<embed>`, `on*` handlers, external URLs, CSS url(http)/@import or fetches; renders headless) with `<table id="results">` and one `<tr id="row-<sail>">` per boat, **in rank order**. Layout and styling are not graded. ## answer.json `{"boats": {sail: {"points": [per race], "codes": [per race], "discarded": [0-based race indices, ascending], "total", "net", "rank"}}, "order": [sails in rank order], "discards_applied": d}` ## Scoring Hidden checks (partial credit; all must pass; numbers within 0.001): `codes_and_dnc`, `race_points_incl_ties_penalties`, `discards_and_totals`, `ranking_with_tiebreaks`, `results_html_static` (exists, static rules, ids, row order) on the given series; `fresh_run_1`, `fresh_run_2`. 30-second limit per run.
Each rule is small, but the tests are layered: one place-counting slip changes every later boat's points, discards and the final order. Original benchmark task written for usecaserank.com. Headless, offline run on a reproducible fixture. Cost shown is a list-price API-equivalent estimate (run on a ChatGPT subscription, not billed).
Success criteria: 1. codes_and_dnc 2. race_points_incl_ties_penalties 3. discards_and_totals 4. ranking_with_tiebreaks 5. results_html_static 6. fresh_run_1 7. fresh_run_2
Setup notes: Use Case Scout batch12 case m06-regatta-scoring (offline fixture). Prepared with batch12/prepare.sh on the shared box; only TASK.md + starting files were copied to the agent machine, hidden key/tests stayed on the box. Prompt = TASK.md verbatim on stdin. Flags: --json -s workspace-write --skip-git-repo-check --ephemeral --ignore-user-config --ignore-rules -C <workdir>. Scored on the box with the scout's scorer: `python score.py WORKDIR KEYDIR`. Single run, no retries. User-level AGENTS.md (846 bytes, sha256 83ec4fe50da8) may have been in context; --ignore-user-config does not document excluding it. Visual output (results.html) rendered offline to PNG with google-chrome headless, network blocked, 1280x800 at ~3 s after load. Serving model not confirmed: requested via -m; the event log does not echo the serving model id. Price source is secondary (pricing.json verification='secondary', https://www.actuia.com/en/news/ai-api-pricing-in-october-2026-050-to-50-for-output/), not an official OpenAI price page. Score: 7/7. Cost is an ESTIMATE: measured tokens x pricing.json list price (ChatGPT plan, nothing billed); input_tokens include cached reads; output_tokens include reasoning tokens. Tool calls 4 (1 failed, recovered). Single run.
Estimated cost List-price estimate; not actually billed.
Output
Metrics
- Estimated cost
- $0.06
- Wall time
- 56s
- Human step-ins
- 0
- Turns
- 1
| Model | Input tok | Output tok | Cost |
|---|---|---|---|
| OGPT-6.1 Solopenai/gpt-6.1-soleffort default (no reasoning-effort override) · thinking on | 91,315 | 2,315 | $0.06 |
Reproduce this run
- Use the use case prompt on the use case page.
- Same setup: GPT-6.1 Sol (openai/gpt-6.1-sol, effort default (no reasoning-effort override) · thinking on) via
Codex CLI 0.163.0 (codex exec --json), cloud. - It counts as a success only if it meets every success criterion: 1. codes_and_dnc 2. race_points_incl_ties_penalties 3. discards_and_totals 4. ranking_with_tiebreaks 5. results_html_static 6. fresh_run_1 7. fresh_run_2
- 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
{"type": "thread.started", "thread_id": "01a16409-0001-77a3-b577-f141cecfdf22"}
{"type": "turn.started"}
{"type": "item.completed", "item": {"id": "item_0", "type": "agent_message", "text": "I\u2019ll implement the scorer with decimal arithmetic for half-up rounding, then check the scoring rules and HTML output.\n"}}
{"type": "item.started", "item": {"id": "item_1", "type": "command_execution", "command": "/bin/bash -lc 'ls -la'", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_1", "type": "command_execution", "command": "/bin/bash -lc 'ls -la'", "aggregated_output": "total 16\ndrwxr-xr-x 6 bob bob 4096 Oct 22 10:34 .\ndrwxrwxr-x 3 bob bob 4096 Oct 22 10:34 ..\ndr-xr-xr-x 2 bob bob 40 Oct 22 10:34 .agents\ndr-xr-xr-x 2 bob bob 40 Oct 22 10:34 .aws\ndr-xr-xr-x 2 bob bob 40 Oct 22 10:34 .codex\ndr-xr-xr-x 2 bob bob 40 Oct 22 10:34 .git\n-rw-r--r-- 1 bob bob 2756 Oct 22 10:08 TASK.md\n-rw-r--r-- 1 bob bob 3678 Oct 22 10:08 input.json\n", "exit_code": 0, "status": "completed"}}
{"type": "item.started", "item": {"id": "item_2", "type": "command_execution", "command": "/bin/bash -lc 'cat input.json'", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_2", "type": "command_execution", "command": "/bin/bash -lc 'cat input.json'", "aggregated_output": "{\n \"entries\": [\n {\n \"sail\": \"USA79\"\n },\n {\n \"sail\": \"NZL851\"\n },\n {\n \"sail\": \"FRA668\"\n },\n {\n \"sail\": \"FRA367\"\n },\n {\n \"sail\": \"NZL287\"\n },\n {\n \"sail\": \"NZL538\"\n },\n {\n \"sail\": \"NZL128\"\n },\n {\n \"sail\": \"GBR651\"\n },\n {\n \"sail\": \"FRA91\"\n },\n {\n \"sail\": \"GBR205\"\n },\n {\n \"sail\": \"GBR719\"\n },\n {\n \"sail\": \"GBR309\"\n }\n ],\n \"races\": [\n {\n \"name\": \"R1\",\n \"finishes\": [\n {\n \"sail\": \"USA79\",\n \"code\": \"DNS\"\n },\n {\n \"sail\": \"NZL538\"\n },\n {\n \"sail\": \"GBR309\"\n },\n {\n \"sail\": \"FRA91\"\n },\n {\n \"sail\": \"NZL851\"\n },\n {\n \"sail\": \"NZL287\"\n },\n {\n \"sail\": \"FRA367\"\n },\n {\n \"sail\": \"GBR719\"\n },\n {\n \"sail\": \"FRA668\",\n \"code\": \"SCP\"\n },\n {\n \"sail\": \"NZL128\"\n },\n {\n \"sail\": \"GBR651\"\n }\n ]\n },\n {\n \"name\": \"R2\",\n \"finishes\": [\n {\n \"sail\": \"GBR309\"\n },\n {\n \"sail\": \"NZL128\"\n },\n {\n \"sail\": \"FRA91\"\n },\n {\n \"sail\": \"NZL287\"\n },\n {\n \"sail\": [\n \"USA79\",\n \"NZL851\"\n ]\n },\n {\n \"sail\": \"GBR719\"\n },\n {\n \"sail\": \"GBR205\"\n },\n {\n \"sail\": \"NZL538\"\n },\n {\n \"sail\": \"FRA367\"\n },\n {\n \"sail\": \"FRA668\"\n }\n ]\n },\n {\n \"name\": \"R3\",\n \"finishes\": [\n {\n \"sail\": \"GBR309\"\n },\n {\n \"sail\": \"FRA91\"\n },\n {\n \"sail\": \"GBR205\",\n \"code\": \"DPI\",\n \"points\": 1\n },\n {\n \"sail\": \"USA79\"\n },\n {\n \"sail\": \"NZL538\"\n },\n {\n \"sail\": \"NZL287\"\n },\n {\n \"sail\": \"GBR651\"\n },\n {\n \"sail\": \"FRA668\"\n },\n {\n \"sail\": \"GBR719\"\n },\n {\n \"sail\": \"NZL851\"\n },\n {\n \"sail\": \"NZL128\",\n \"code\": \"DSQ\"\n }\n ]\n },\n {\n \"name\": \"R4\",\n \"finishes\": [\n {\n \"sail\": \"FRA91\"\n },\n {\n \"sail\": \"GBR651\"\n },\n {\n \"sail\": \"GBR309\",\n \"code\": \"OCS\"\n },\n {\n \"sail\": [\n \"NZL287\",\n \"NZL851\"\n ]\n },\n {\n \"sail\": \"USA79\",\n \"code\": \"RET\"\n },\n {\n \"sail\": \"GBR205\"\n },\n {\n \"sail\": \"FRA367\"\n },\n {\n \"sail\": \"NZL538\"\n },\n {\n \"sail\": \"GBR719\"\n },\n {\n \"sail\": \"NZL128\",\n \"code\": \"SCP\"\n }\n ]\n },\n {\n \"name\": \"R5\",\n \"finishes\": [\n {\n \"sail\": \"NZL287\"\n },\n {\n \"sail\": \"NZL128\"\n },\n {\n \"sail\": \"FRA91\"\n },\n {\n \"sail\": \"USA79\"\n },\n {\n \"sail\": \"GBR309\",\n \"code\": \"DNS\"\n },\n {\n \"sail\": \"GBR205\"\n },\n {\n \"sail\": \"GBR651\"\n },\n {\n \"sail\": \"FRA367\"\n },\n {\n \"sail\": \"GBR719\",\n \"code\": \"OCS\"\n },\n {\n \"sail\": \"NZL851\"\n }\n ]\n },\n {\n \"name\": \"R6\",\n \"finishes\": [\n {\n \"sail\": [\n \"NZL128\",\n \"GBR309\"\n ]\n },\n {\n \"sail\": \"FRA91\"\n },\n {\n \"sail\": \"GBR719\"\n },\n {\n \"sail\": \"FRA367\"\n },\n {\n \"sail\": \"NZL287\"\n },\n {\n \"sail\": \"USA79\"\n },\n {\n \"sail\": \"NZL538\"\n },\n {\n \"sail\": \"FRA668\"\n },\n {\n \"sail\": \"NZL851\"\n },\n {\n \"sail\": \"USA79\"\n }\n ]\n },\n {\n \"name\": \"R7\",\n \"finishes\": [\n {\n \"sail\": \"GBR719\"\n },\n {\n \"sail\": \"GBR309\"\n },\n {\n \"sail\": \"USA79\",\n \"code\": \"ZFP\"\n },\n {\n \"sail\": \"FRA91\",\n \"code\": \"RDG\"\n },\n {\n \"sail\": \"NZL538\"\n },\n {\n \"sail\": \"NZL287\"\n },\n {\n \"sail\": \"GBR205\"\n },\n {\n \"sail\": \"FRA367\"\n },\n {\n \"sail\": \"NZL851\",\n \"code\": \"dne\"\n },\n {\n \"sail\": \"GBR651\"\n },\n {\n \"sail\": \"FRA668\",\n \"code\": \"DSQ\"\n }\n ]\n }\n ],\n \"discards\": {\n \"4\": 1,\n \"7\": 2\n },\n \"penalty_pct\": 20\n}", "exit_code": 0, "status": "completed"}}
{"type": "item.started", "item": {"id": "item_3", "type": "command_execution", "command": "/bin/bash -lc \"cat > solve.py <<'PY'\n#\"'!/usr/bin/env python3\n\"\"\"Score a low-point regatta and write JSON and a standalone HTML table.\"\"\"\nimport json\nimport sys\nfrom decimal import Decimal, ROUND_HALF_UP\nfrom html import escape\nfrom pathlib import Path\n\nNONFINISH = {'\"'DNC', 'DNS', 'OCS', 'DNF', 'RET', 'DSQ', 'DNE', 'UFD', 'BFD'}\n\n\ndef dec(value):\n return Decimal(str(value))\n\n\ndef number(value):\n return int(value) if value == value.to_integral_value() else float(value)\n\n\ndef score(data):\n sails = [str(entry['sail']) for entry in data['entries']]\n n = len(sails)\n races = data.get('races', [])\n limit = Decimal(n + 1)\n penalty = (Decimal(n) * dec(data.get('penalty_pct', 0)) / 100).quantize(\n Decimal('1'), rounding=ROUND_HALF_UP)\n points = {s: [] for s in sails}\n codes = {s: [] for s in sails}\n for race in races:\n seen = set()\n race_points = {}\n race_codes = {}\n place = 1\n for item in race.get('finishes', []):\n members = item['sail'] if isinstance(item['sail'], list) else [item['sail']]\n boats = []\n for member in members:\n s = str(member)\n if s in points and s not in seen:\n seen.add(s)\n boats.append(s)\n if not boats:\n continue\n code = str(item.get('code') or '').upper()\n if code in NONFINISH:\n value = limit\n else:\n value = Decimal(2 * place + len(boats) - 1) / 2\n place += len(boats)\n if code in {'ZFP', 'SCP'}:\n value = min(limit, value + penalty)\n elif code == 'DPI':\n value = min(limit, value + dec(item.get('points', 0)))\n elif code == 'RDG':\n value = dec(item['points']) if 'points' in item else None\n for s in boats:\n race_points[s] = value\n race_codes[s] = code\n for s in sails:\n points[s].append(race_points.get(s, limit))\n codes[s].append(race_codes.get(s, 'DNC'))\n for s in sails:\n known = [p for p in points[s] if p is not None]\n average = ((sum(known, Decimal(0)) / len(known)).quantize(\n Decimal('0.1'), rounding=ROUND_HALF_UP) if known else limit)\n points[s] = [average if p is None else p for p in points[s]]\n thresholds = [(int(k), int(v)) for k, v in data.get('discards', {}).items()\n if int(k) <= len(races)]\n d = max(thresholds, default=(0, 0), key=lambda pair: pair[0])[1]\n boats = {}\n keys = {}\n for index, s in enumerate(sails):\n eligible = [i for i in range(len(races)) if codes[s][i] \"'!= '\"'DNE']\n discarded = sorted(sorted(eligible, key=lambda i: (points[s][i], i),\n reverse=True)[:max(0, d)])\n excluded = set(discarded)\n total = sum(points[s], Decimal(0))\n net = total - sum((points[s][i] for i in discarded), Decimal(0))\n keys[s] = (net, sorted(p for i, p in enumerate(points[s]) if i not in excluded),\n list(reversed(points[s])), index)\n boats[s] = {'points': [number(p) for p in points[s]], 'codes': codes[s],\n 'discarded': discarded, 'total': number(total), 'net': number(net)}\n order = sorted(sails, key=keys.__getitem__)\n for rank, s in enumerate(order, 1):\n boats[s]['rank'] = rank\n return {'boats': boats, 'order': order, 'discards_applied': d}\n\n\ndef render(result):\n count = len(next(iter(result['boats'].values()))['points']) if result['boats'] else 0\n headers = ['Rank', 'Sail'] + ['R' + str(i + 1) for i in range(count)] + ['Total', 'Net']\n rows = []\n for s in result['order']:\n boat = result['boats'][s]\n cells = [str(boat['rank']), escape(s)]\n for i, p in enumerate(boat['points']):\n label = str(p) + (' ' + boat['codes'][i] if boat['codes'][i] else '')\n cells.append(('<del>' + escape(label) + '</del>') if i in boat['discarded'] else escape(label))\n cells += [str(boat['total']), str(boat['net'])]\n rows.append('<tr id=\\\"row-' + escape(s, quote=True) + '\\\">' +\n ''.join('<td>' + c + '</td>' for c in cells) + '</tr>')\n return ('<\"'!doctype html><html lang=\"en\"><meta charset=\"utf-8\">'\"'\n '<title>Regatta results</title><style>body{font-family:system-ui;margin:2rem}'\n 'table{border-collapse:collapse}th,td{padding:.5rem;border:1px solid #ccc;'\n 'text-align:right}del{color:#777}</style><body><h1>Regatta results</h1>'\n '<p>Discards applied: ' + str(result['discards_applied']) + '</p>'\n '<table id=\\\"results\\\"><thead><tr>' + ''.join('<th>' + h + '</th>' for h in headers) +\n '</tr></thead><tbody>' + ''.join(rows) + '</tbody></table></body></html>')\n\n\ndef main():\n input_path, output_path = map(Path, sys.argv[1:3])\n with input_path.open(encoding='utf-8') as f:\n result = score(json.load(f, parse_float=Decimal))\n output_path.write_text(json.dumps(result, indent=2) + '\\\\n', encoding='utf-8')\n output_path.with_name('results.html').write_text(render(result), encoding='utf-8')\n\n\nif __name__ == '__main__':\n main()\nPY\npython solve.py input.json answer.json\"", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_3", "type": "command_execution", "command": "/bin/bash -lc \"cat > solve.py <<'PY'\n#\"'!/usr/bin/env python3\n\"\"\"Score a low-point regatta and write JSON and a standalone HTML table.\"\"\"\nimport json\nimport sys\nfrom decimal import Decimal, ROUND_HALF_UP\nfrom html import escape\nfrom pathlib import Path\n\nNONFINISH = {'\"'DNC', 'DNS', 'OCS', 'DNF', 'RET', 'DSQ', 'DNE', 'UFD', 'BFD'}\n\n\ndef dec(value):\n return Decimal(str(value))\n\n\ndef number(value):\n return int(value) if value == value.to_integral_value() else float(value)\n\n\ndef score(data):\n sails = [str(entry['sail']) for entry in data['entries']]\n n = len(sails)\n races = data.get('races', [])\n limit = Decimal(n + 1)\n penalty = (Decimal(n) * dec(data.get('penalty_pct', 0)) / 100).quantize(\n Decimal('1'), rounding=ROUND_HALF_UP)\n points = {s: [] for s in sails}\n codes = {s: [] for s in sails}\n for race in races:\n seen = set()\n race_points = {}\n race_codes = {}\n place = 1\n for item in race.get('finishes', []):\n members = item['sail'] if isinstance(item['sail'], list) else [item['sail']]\n boats = []\n for member in members:\n s = str(member)\n if s in points and s not in seen:\n seen.add(s)\n boats.append(s)\n if not boats:\n continue\n code = str(item.get('code') or '').upper()\n if code in NONFINISH:\n value = limit\n else:\n value = Decimal(2 * place + len(boats) - 1) / 2\n place += len(boats)\n if code in {'ZFP', 'SCP'}:\n value = min(limit, value + penalty)\n elif code == 'DPI':\n value = min(limit, value + dec(item.get('points', 0)))\n elif code == 'RDG':\n value = dec(item['points']) if 'points' in item else None\n for s in boats:\n race_points[s] = value\n race_codes[s] = code\n for s in sails:\n points[s].append(race_points.get(s, limit))\n codes[s].append(race_codes.get(s, 'DNC'))\n for s in sails:\n known = [p for p in points[s] if p is not None]\n average = ((sum(known, Decimal(0)) / len(known)).quantize(\n Decimal('0.1'), rounding=ROUND_HALF_UP) if known else limit)\n points[s] = [average if p is None else p for p in points[s]]\n thresholds = [(int(k), int(v)) for k, v in data.get('discards', {}).items()\n if int(k) <= len(races)]\n d = max(thresholds, default=(0, 0), key=lambda pair: pair[0])[1]\n boats = {}\n keys = {}\n for index, s in enumerate(sails):\n eligible = [i for i in range(len(races)) if codes[s][i] \"'!= '\"'DNE']\n discarded = sorted(sorted(eligible, key=lambda i: (points[s][i], i),\n reverse=True)[:max(0, d)])\n excluded = set(discarded)\n total = sum(points[s], Decimal(0))\n net = total - sum((points[s][i] for i in discarded), Decimal(0))\n keys[s] = (net, sorted(p for i, p in enumerate(points[s]) if i not in excluded),\n list(reversed(points[s])), index)\n boats[s] = {'points': [number(p) for p in points[s]], 'codes': codes[s],\n 'discarded': discarded, 'total': number(total), 'net': number(net)}\n order = sorted(sails, key=keys.__getitem__)\n for rank, s in enumerate(order, 1):\n boats[s]['rank'] = rank\n return {'boats': boats, 'order': order, 'discards_applied': d}\n\n\ndef render(result):\n count = len(next(iter(result['boats'].values()))['points']) if result['boats'] else 0\n headers = ['Rank', 'Sail'] + ['R' + str(i + 1) for i in range(count)] + ['Total', 'Net']\n rows = []\n for s in result['order']:\n boat = result['boats'][s]\n cells = [str(boat['rank']), escape(s)]\n for i, p in enumerate(boat['points']):\n label = str(p) + (' ' + boat['codes'][i] if boat['codes'][i] else '')\n cells.append(('<del>' + escape(label) + '</del>') if i in boat['discarded'] else escape(label))\n cells += [str(boat['total']), str(boat['net'])]\n rows.append('<tr id=\\\"row-' + escape(s, quote=True) + '\\\">' +\n ''.join('<td>' + c + '</td>' for c in cells) + '</tr>')\n return ('<\"'!doctype html><html lang=\"en\"><meta charset=\"utf-8\">'\"'\n '<title>Regatta results</title><style>body{font-family:system-ui;margin:2rem}'\n 'table{border-collapse:collapse}th,td{padding:.5rem;border:1px solid #ccc;'\n 'text-align:right}del{color:#777}</style><body><h1>Regatta results</h1>'\n '<p>Discards applied: ' + str(result['discards_applied']) + '</p>'\n '<table id=\\\"results\\\"><thead><tr>' + ''.join('<th>' + h + '</th>' for h in headers) +\n '</tr></thead><tbody>' + ''.join(rows) + '</tbody></table></body></html>')\n\n\ndef main():\n input_path, output_path = map(Path, sys.argv[1:3])\n with input_path.open(encoding='utf-8') as f:\n result = score(json.load(f, parse_float=Decimal))\n output_path.write_text(json.dumps(result, indent=2) + '\\\\n', encoding='utf-8')\n output_path.with_name('results.html').write_text(render(result), encoding='utf-8')\n\n\nif __name__ == '__main__':\n main()\nPY\npython solve.py input.json answer.json\"", "aggregated_output": "/bin/bash: line 123: python: command not found\n", "exit_code": 127, "status": "failed"}}
{"type": "item.started", "item": {"id": "item_4", "type": "command_execution", "command": "/bin/bash -lc \"python3 solve.py input.json answer.json\npython3 - <<'PY'\nfrom solve import score\nfrom html.parser import HTMLParser\nimport json\nx=score({'entries':[{'sail':s} for s in 'ABCD'], 'races':[\n {'finishes':[{'sail':'X'},{'sail':'A','code':'dns'},{'sail':['B','B','C'],'code':'SCP'},{'sail':'A'},{'sail':'D','code':'RDG'}]},\n {'finishes':[{'sail':'D','code':'RDG','points':2.25},{'sail':'B','code':'DNE'},{'sail':'C','code':'DPI','points':8}]}], 'penalty_pct':12.5,'discards':{'2':1}})\nassert x['boats']['B']['points']==[2.5,5]\nassert x['boats']['B']['discarded']==[0]\nassert x['boats']['D']['points']==[2.3,2.25]\nassert x['boats']['C']['points']==[2.5,5]\nassert x['boats']['A']['codes']==['DNS','DNC']\nassert x['boats']['A']['discarded']==[1]\ny=score({'entries':[{'sail':s} for s in 'AB'], 'races':[{'finishes':[{'sail':'A'},{'sail':'B'}]},{'finishes':[{'sail':'B'},{'sail':'A'}]}], 'discards':{'2':1}})\nassert y['order']==['B','A']\nclass Check(HTMLParser):\n def __init__(self): super().__init__(); self.rows=[]\n def handle_starttag(self,tag,attrs):\n assert tag not in {'script','img','link','iframe','object','embed'}\n assert not any(k.startswith('on') for k,v in attrs)\n a=dict(attrs)\n if tag=='tr' and a.get('id','').startswith('row-'): self.rows.append(a['id'][4:])\nc=Check(); c.feed(open('results.html').read())\na=json.load(open('answer.json')); assert c.rows==a['order']\nprint('Edge-case scoring and HTML checks passed.')\nprint('Series order:', ', '.join(a['order']))\nPY\"", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_4", "type": "command_execution", "command": "/bin/bash -lc \"python3 solve.py input.json answer.json\npython3 - <<'PY'\nfrom solve import score\nfrom html.parser import HTMLParser\nimport json\nx=score({'entries':[{'sail':s} for s in 'ABCD'], 'races':[\n {'finishes':[{'sail':'X'},{'sail':'A','code':'dns'},{'sail':['B','B','C'],'code':'SCP'},{'sail':'A'},{'sail':'D','code':'RDG'}]},\n {'finishes':[{'sail':'D','code':'RDG','points':2.25},{'sail':'B','code':'DNE'},{'sail':'C','code':'DPI','points':8}]}], 'penalty_pct':12.5,'discards':{'2':1}})\nassert x['boats']['B']['points']==[2.5,5]\nassert x['boats']['B']['discarded']==[0]\nassert x['boats']['D']['points']==[2.3,2.25]\nassert x['boats']['C']['points']==[2.5,5]\nassert x['boats']['A']['codes']==['DNS','DNC']\nassert x['boats']['A']['discarded']==[1]\ny=score({'entries':[{'sail':s} for s in 'AB'], 'races':[{'finishes':[{'sail':'A'},{'sail':'B'}]},{'finishes':[{'sail':'B'},{'sail':'A'}]}], 'discards':{'2':1}})\nassert y['order']==['B','A']\nclass Check(HTMLParser):\n def __init__(self): super().__init__(); self.rows=[]\n def handle_starttag(self,tag,attrs):\n assert tag not in {'script','img','link','iframe','object','embed'}\n assert not any(k.startswith('on') for k,v in attrs)\n a=dict(attrs)\n if tag=='tr' and a.get('id','').startswith('row-'): self.rows.append(a['id'][4:])\nc=Check(); c.feed(open('results.html').read())\na=json.load(open('answer.json')); assert c.rows==a['order']\nprint('Edge-case scoring and HTML checks passed.')\nprint('Series order:', ', '.join(a['order']))\nPY\"", "aggregated_output": "Edge-case scoring and HTML checks passed.\nSeries order: GBR309, FRA91, NZL287, NZL128, USA79, NZL538, GBR719, GBR205, FRA367, GBR651, NZL851, FRA668\n", "exit_code": 0, "status": "completed"}}
{"type": "item.completed", "item": {"id": "item_5", "type": "agent_message", "text": "Created [solve.py](solve.py), [answer.json](answer.json), and [results.html](results.html).\n\nVerified dead heats, penalties, RDG averaging, DNE protection, discards, tiebreaks, and static HTML row order.\n\nRun with `python3 solve.py input.json answer.json` (`python` is unavailable here)."}}
{"type": "turn.completed", "usage": {"input_tokens": 91315, "cached_input_tokens": 76416, "cache_write_input_tokens": 0, "output_tokens": 2315, "reasoning_output_tokens": 17}}