{"case_id": "challenge-coding-001", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "parser", "state"], "scorer": "code_python_tests", "expected": {"tests": ["lines = ['# comment', '[db]', ' host = localhost ', 'port=5432', '', '[feature]', 'enabled=true', 'enabled = false']\nassert solution.solve(lines) == {'db': {'host': 'localhost', 'port': '5432'}, 'feature': {'enabled': 'false'}}", "assert solution.solve(['[x]', 'a=1', 'a=2', '[y]', 'b = hi']) == {'x': {'a': '2'}, 'y': {'b': 'hi'}}"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(lines: list[str]) -> dict。lines 是简化 INI：空行和以 # 开头的行忽略；[section] 开始新 section；key=value 写入当前 section；key/value 两侧空白要去掉；同一 section 内重复 key 后者覆盖前者。返回嵌套 dict。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "2ca132befd6923601a17f24e5efb427ea787e3ae63ae265dd45f0c700cd895d6", "started_at": "2026-06-16T10:58:35.754320+00:00", "latency_ms": 20506, "output": " ```python\ndef solve(lines: list[str]) -> dict:\n result = {}\n section = None\n for raw in lines:\n line = raw.strip()\n if not line or line.startswith('#'):\n continue\n if line.startswith('[') and line.endswith(']'):\n section = line[1:-1].strip()\n result.setdefault(section, {})\n continue\n if '=' in line and section is not None:\n key, value = line.split('=', 1)\n result[section][key.strip()] = value.strip()\n return result\n```", "usage": {"prompt_tokens": 111, "completion_tokens": 1181, "total_tokens": 1292, "cost": 0.00482945, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00482945, "upstream_inference_prompt_cost": 0.00010545, "upstream_inference_completions_cost": 0.004724}, "completion_tokens_details": {"reasoning_tokens": 1323, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607518-10CyMXJycIE2SGgMxyqi", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-002", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "ledger", "state"], "scorer": "code_python_tests", "expected": {"tests": ["events = ['a credit 100', 'b debit 40', 'a credit 999', 'rev b', 'c debit 10']\nassert solution.solve(events) == 90", "events = ['x debit 5', 'rev y', 'rev x', 'rev x', 'z credit 7']\nassert solution.solve(events) == 7"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(events: list[str]) -> int。事件格式：\" credit \" 增加余额，\" debit \" 减少余额，\"rev \" 撤销此前尚未撤销过的同 id 事件。重复交易 id 只保留第一次，未知撤销忽略。返回最终余额。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "3d2d5a46a600444476b5ddfd04634035ff394bcb76fcd230d785597c9cf295ae", "started_at": "2026-06-16T10:58:56.298987+00:00", "latency_ms": 21745, "output": "```python\ndef solve(events: list[str]) -> int:\n balance = 0\n active = {}\n seen = set()\n for ev in events:\n parts = ev.split()\n if not parts:\n continue\n if parts[0] == \"rev\":\n if len(parts) != 2:\n continue\n tid = parts[1]\n if tid in active:\n balance -= active[tid]\n del active[tid]\n continue\n if len(parts) != 3:\n continue\n tid, typ, amt_str = parts\n if tid in seen:\n continue\n seen.add(tid)\n amt = int(amt_str)\n if typ == \"credit\":\n signed = amt\n elif typ == \"debit\":\n signed = -amt\n else:\n continue\n balance += signed\n active[tid] = signed\n return balance\n```", "usage": {"prompt_tokens": 113, "completion_tokens": 1207, "total_tokens": 1320, "cost": 0.0049314, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 5, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0049314, "upstream_inference_prompt_cost": 0.0001034, "upstream_inference_completions_cost": 0.004828}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607538-vmJLJfpEgwlK7MhbST8T", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-003", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "topological-sort"], "scorer": "code_python_tests", "expected": {"tests": ["deps = {'build': ['lint', 'test'], 'test': ['install'], 'lint': ['install']}\nassert solution.solve(deps) == [['install'], ['lint', 'test'], ['build']]", "assert solution.solve({'a': ['b'], 'b': ['a']}) == []", "assert solution.solve({'deploy': ['build'], 'build': []}) == [['build'], ['deploy']]"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(deps: dict[str, list[str]]) -> list[list[str]]。deps 表示 task -> prerequisites。返回可并行执行的拓扑层，每层任务按字典序排序；如果存在环，返回空列表。所有只出现在 prerequisites 中的任务也要包含。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "413c5b602b0fd1ae1e9c3a49b09ecf03c61769fce4b34dbd96b5d8c6a2c68f90", "started_at": "2026-06-16T10:59:18.090314+00:00", "latency_ms": 11669, "output": "```python\nfrom typing import Dict, List\n\n\ndef solve(deps: Dict[str, List[str]]) -> List[List[str]]:\n nodes = set(deps)\n for prereqs in deps.values():\n nodes.update(prereqs)\n\n indeg = {node: 0 for node in nodes}\n adj = {node: [] for node in nodes}\n\n for task, prereqs in deps.items():\n for p in prereqs:\n adj[p].append(task)\n indeg[task] += 1\n\n result = []\n current = sorted([node for node in nodes if indeg[node] == 0])\n\n while current:\n result.append(current)\n nxt = []\n for node in current:\n for nb in adj[node]:\n indeg[nb] -= 1\n if indeg[nb] == 0:\n nxt.append(nb)\n current = sorted(nxt)\n\n if sum(len(layer) for layer in result) != len(nodes):\n return []\n\n return result\n```", "usage": {"prompt_tokens": 101, "completion_tokens": 729, "total_tokens": 830, "cost": 0.00301195, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00301195, "upstream_inference_prompt_cost": 9.595e-05, "upstream_inference_completions_cost": 0.002916}, "completion_tokens_details": {"reasoning_tokens": 576, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607560-QBDPH83KkiC24PmUMg06", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-004", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "lru"], "scorer": "code_python_tests", "expected": {"tests": ["ops = ['put a 1', 'put b 2', 'get a', 'put c 3', 'get b', 'get a', 'get c']\nassert solution.solve(2, ops) == [1, -1, 1, 3]", "assert solution.solve(0, ['put a 1', 'get a']) == [-1]", "assert solution.solve(1, ['put a 1', 'put a 2', 'get a']) == [2]"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(capacity: int, ops: list[str]) -> list[int]，模拟 LRU cache。ops 包含 \"put key value\" 和 \"get key\"。get 返回 value，不存在返回 -1。put 已存在 key 要更新并变成最近使用。容量为 0 时所有 get 都返回 -1。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "840e7b4d0c404f3d7b34ebc9931e87612608d6339755d5f1066fda55bd957375", "started_at": "2026-06-16T10:59:29.814983+00:00", "latency_ms": 7437, "output": " ```python\nfrom collections import OrderedDict\n\ndef solve(capacity: int, ops: list[str]) -> list[int]:\n cache: OrderedDict[int, int] = OrderedDict()\n res: list[int] = []\n if capacity <= 0:\n for op in ops:\n if op.startswith(\"get\"):\n res.append(-1)\n return res\n for op in ops:\n parts = op.split()\n if parts[0] == \"put\":\n key = int(parts[1])\n value = int(parts[2])\n if key in cache:\n cache.move_to_end(key)\n elif len(cache) >= capacity:\n cache.popitem(last=False)\n cache[key] = value\n else:\n key = int(parts[1])\n if key in cache:\n cache.move_to_end(key)\n res.append(cache[key])\n else:\n res.append(-1)\n return res\n```", "usage": {"prompt_tokens": 117, "completion_tokens": 483, "total_tokens": 600, "cost": 0.00177825, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00177825, "upstream_inference_prompt_cost": 8.775e-05, "upstream_inference_completions_cost": 0.0016905}, "completion_tokens_details": {"reasoning_tokens": 288, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607572-XA0qY0vytQlYlAWy3T71", "finish_reason": "stop", "score": {"passed": false, "score": 0.0, "details": {"returncode": 1, "stdout": "", "stderr": "Traceback (most recent call last):\n File \"/var/folders/x_/4cht1kfj1_j31gdv5w01sgmw0000gn/T/dracobench-code-ahvjkf0e/test_solution.py\", line 4, in \n assert solution.solve(2, ops) == [1, -1, 1, 3]\n ^^^^^^^^^^^^^^^^^^^^^^\n File \"/private/var/folders/x_/4cht1kfj1_j31gdv5w01sgmw0000gn/T/dracobench-code-ahvjkf0e/solution.py\", line 14, in solve\n key = int(parts[1])\n ^^^^^^^^^^^^^\nValueError: invalid literal for int() with base 10: 'a'\n"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-005", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "json", "copy"], "scorer": "code_python_tests", "expected": {"tests": ["base = {'a': 1, 'b': {'x': 1, 'y': 2}, 'c': 3}\npatch = {'b': {'y': None, 'z': 4}, 'c': None}\nassert solution.solve(base, patch) == {'a': 1, 'b': {'x': 1, 'z': 4}}\nassert base == {'a': 1, 'b': {'x': 1, 'y': 2}, 'c': 3}", "assert solution.solve({'a': {'b': 1}}, {'a': 5}) == {'a': 5}"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(base: dict, patch: dict) -> dict，执行 JSON Merge Patch：patch 中值为 None 表示删除该 key；两个值都是 dict 时递归合并；其他值覆盖。不能修改输入对象。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "8dc22406b418d74ea74b50692fe086d4f80748258269dc93f82290e6c344b5a3", "started_at": "2026-06-16T10:59:37.300114+00:00", "latency_ms": 5045, "output": "```python\nimport copy\n\ndef solve(base: dict, patch: dict) -> dict:\n result = copy.deepcopy(base)\n for key, value in patch.items():\n if value is None:\n result.pop(key, None)\n elif isinstance(value, dict) and isinstance(result.get(key), dict):\n result[key] = solve(result[key], value)\n else:\n result[key] = copy.deepcopy(value)\n return result\n```", "usage": {"prompt_tokens": 92, "completion_tokens": 213, "total_tokens": 305, "cost": 0.0009394, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0009394, "upstream_inference_prompt_cost": 8.74e-05, "upstream_inference_completions_cost": 0.000852}, "completion_tokens_details": {"reasoning_tokens": 148, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607579-u3esTnS6ajzeygs6QfoC", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-006", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "regex", "duration"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve('1h 30m 500ms') == 5400500", "assert solution.solve('2d 1h 2s') == 176402000", "assert solution.solve('100ms 2s 3ms') == 2103"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(text: str) -> int，把时长字符串转换成毫秒。支持整数单位 d、h、m、s、ms，可有空格，单位可重复，顺序任意。例如 \"1h 30m 500ms\"。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "ce87366a2f6f080a35c0fdd0872b6a8304a8233e0c5c9361c19fec614c0d1fcb", "started_at": "2026-06-16T10:59:42.387692+00:00", "latency_ms": 6030, "output": "```python\nimport re\n\ndef solve(text: str) -> int:\n units = {\"d\": 86400000, \"h\": 3600000, \"m\": 60000, \"s\": 1000, \"ms\": 1}\n total = 0\n for m in re.finditer(r\"(\\d+)\\s*(ms|d|h|m|s)\", text or \"\"):\n total += int(m.group(1)) * units[m.group(2)]\n return total\n```", "usage": {"prompt_tokens": 93, "completion_tokens": 525, "total_tokens": 618, "cost": 0.00218835, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00218835, "upstream_inference_prompt_cost": 8.835e-05, "upstream_inference_completions_cost": 0.0021}, "completion_tokens_details": {"reasoning_tokens": 414, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607584-1KKHckhbWfCNdtZ1hCZE", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-007", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "parser", "quotes"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve('{a:[(1)]}') is True", "assert solution.solve(\"{'x': '(]'}\") is True", "assert solution.solve(\"['unterminated]\") is False", "assert solution.solve('([)]') is False", "assert solution.solve(\"\\\"paren \\\\\\\" ) still quoted\\\"\") is True"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(s: str) -> bool，检查括号 ()[]{} 是否配对。单引号或双引号内部的括号忽略；反斜杠会转义引号。输入字符串可以包含普通字符。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "2f2e8f01533244c8104f74b3f9c9bc261154f2ff4c46c03a031258f6a5706f9f", "started_at": "2026-06-16T10:59:48.468103+00:00", "latency_ms": 34028, "output": " ```python\ndef solve(s: str) -> bool:\n stack = []\n quote = None\n pairs = {'(': ')', '[': ']', '{': '}'}\n i = 0\n n = len(s)\n while i < n:\n c = s[i]\n if c == '\\\\':\n i += 2\n continue\n if quote is None:\n if c in \"'\\\"\":\n quote = c\n elif c in pairs:\n stack.append(c)\n elif c in pairs.values():\n if not stack or pairs[stack.pop()] != c:\n return False\n else:\n if c == quote:\n quote = None\n i += 1\n return not stack and quote is None\n```", "usage": {"prompt_tokens": 91, "completion_tokens": 3049, "total_tokens": 3140, "cost": 0.01073975, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.01073975, "upstream_inference_prompt_cost": 6.825e-05, "upstream_inference_completions_cost": 0.0106715}, "completion_tokens_details": {"reasoning_tokens": 3197, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607590-milwsub74UP05akrLUNS", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-008", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "dedupe", "sorting"], "scorer": "code_python_tests", "expected": {"tests": ["rows = [{'user':'b','ts':1,'value':'old'}, {'user':'a','ts':2,'value':'x'}, {'user':'b','ts':3,'value':'new'}]\nassert solution.solve(rows) == [{'user':'a','ts':2,'value':'x'}, {'user':'b','ts':3,'value':'new'}]", "rows = [{'user':'a','ts':1,'value':'first'}, {'user':'a','ts':1,'value':'second'}]\nassert solution.solve(rows) == [{'user':'a','ts':1,'value':'second'}]"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(rows: list[dict]) -> list[dict]。每行有 user、ts、value。对每个 user 保留 ts 最大的一行；若 ts 相同，保留在输入中更靠后的行。输出按 user 字典序排序。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "2a9a2d40a756627e38d28a8ac6afc98311acbafa718d7b3aaaecbedb9f020179", "started_at": "2026-06-16T11:00:22.545766+00:00", "latency_ms": 11797, "output": "```python\ndef solve(rows: list[dict]) -> list[dict]:\n best = {}\n for i, row in enumerate(rows):\n user = row[\"user\"]\n ts = row[\"ts\"]\n if user not in best or ts > best[user][0][\"ts\"] or (ts == best[user][0][\"ts\"] and i > best[user][1]):\n best[user] = (row, i)\n return [row for user, (row, _) in sorted(best.items(), key=lambda x: x[0])]\n```", "usage": {"prompt_tokens": 99, "completion_tokens": 512, "total_tokens": 611, "cost": 0.00214205, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00214205, "upstream_inference_prompt_cost": 9.405e-05, "upstream_inference_completions_cost": 0.002048}, "completion_tokens_details": {"reasoning_tokens": 455, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607624-lfE84GOomqJN6ySipcOT", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-001", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "iterator-default", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*def\\s+summarize\\(items=None\\)\\s*:", "flags": "is"}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "下面代码在 total 之后再次读取数据会变成空列表。请指出根因，并给出最小修复。最后单独一行写 FIX: <修复后的第一行函数定义>。\n\n```python\ndef summarize(items=iter([1, 2, 3])):\n return sum(items)\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "7b02a617eebe49b179cee84c9b8347c6bebe382f42a2b199d92b3aa9ed844102", "started_at": "2026-06-16T11:00:34.387137+00:00", "latency_ms": 9390, "output": " 根因：默认参数 `items=iter([1, 2, 3])` 在函数定义时只执行一次，生成的是**同一个迭代器对象**。`sum()` 会把这个迭代器耗尽，之后再次调用默认参数时用的就是已耗尽的迭代器，所以结果为空。\n\n最小修复：用 `None` 作为默认哨兵，每次调用时在函数内部重新创建可迭代对象。\n\nFIX: def summarize(items=None):", "usage": {"prompt_tokens": 99, "completion_tokens": 858, "total_tokens": 957, "cost": 0.00307725, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00307725, "upstream_inference_prompt_cost": 7.425e-05, "upstream_inference_completions_cost": 0.003003}, "completion_tokens_details": {"reasoning_tokens": 844, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607636-y0tDMTPbCcGPTLCnWcXP", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*def\\s+summarize\\(items=None\\)\\s*:"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-002", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "defaultdict", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*counts\\s*=\\s*defaultdict\\(lambda\\s*:\\s*\\{'seen'\\s*:\\s*\\[\\]\\}\\)\\s*`?", "flags": "is"}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "下面代码期望统计每个用户的事件数，但所有用户计数会互相影响。请指出根因，并给出最小修复。最后单独一行写 FIX: <修复后的 defaultdict 初始化行>。\n\n```python\nfrom collections import defaultdict\nshared = {'seen': []}\ncounts = defaultdict(lambda: shared)\n\ndef add(user, event):\n counts[user]['seen'].append(event)\n return counts[user]\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "fc1eb426cf811456432a61a306862f8bf804417edb8c8fca6dd3b86c1f9a9940", "started_at": "2026-06-16T11:00:43.785846+00:00", "latency_ms": 4810, "output": "根因：`defaultdict(lambda: shared)` 对所有缺失键都返回同一个 `shared` dict 对象，因此所有用户共享同一个 `{'seen': []}`，追加事件会互相影响。\n\n最小修复：让默认值工厂每次返回一个新的 dict。\n\nFIX: `counts = defaultdict(lambda: {'seen': []})`", "usage": {"prompt_tokens": 121, "completion_tokens": 242, "total_tokens": 363, "cost": 0.00108295, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00108295, "upstream_inference_prompt_cost": 0.00011495, "upstream_inference_completions_cost": 0.000968}, "completion_tokens_details": {"reasoning_tokens": 199, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607646-4XzTOU733VsRdPzxFjA7", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*counts\\s*=\\s*defaultdict\\(lambda\\s*:\\s*\\{'seen'\\s*:\\s*\\[\\]\\}\\)\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-003", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "off-by-one", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*for\\s+start\\s+in\\s+range\\(0,\\s*len\\(items\\),\\s*page_size\\)\\s*:", "flags": "is"}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "下面分页代码会漏掉最后不足 page_size 的一页。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 range 行>。\n\n```python\ndef pages(items, page_size):\n out = []\n for start in range(0, len(items) - page_size, page_size):\n out.append(items[start:start + page_size])\n return out\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "c6fe209d60968a3b2d253a065c8ce8255865f73575665a685d957cb52ce82011", "started_at": "2026-06-16T11:00:48.600949+00:00", "latency_ms": 4285, "output": "Bug：`range` 的终止值写成了 `len(items) - page_size`，当最后一页不足 `page_size` 时，起始索引会超过该终止值，导致最后一页被跳过。切片 `items[start:start + page_size]` 本身可以安全处理末尾不足一页的情况，所以终止值应直接用 `len(items)`。\n\nFIX: `for start in range(0, len(items), page_size):`", "usage": {"prompt_tokens": 121, "completion_tokens": 285, "total_tokens": 406, "cost": 0.001251, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 5, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.001251, "upstream_inference_prompt_cost": 0.000111, "upstream_inference_completions_cost": 0.00114}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607650-U0z1ltTj53tL5f8lX03v", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*for\\s+start\\s+in\\s+range\\(0,\\s*len\\(items\\),\\s*page_size\\)\\s*:"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-004", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "sorting", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*return\\s+sorted\\(ids,\\s*key\\s*=\\s*int\\)\\s*`?", "flags": "is"}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "下面代码期望把数字字符串按数值排序，但结果是字典序。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 return 行>。\n\n```python\ndef order(ids):\n return sorted(ids)\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "b3f10943f43eaa04524058b0dd7fb30cbd21740003559e79de619ae210a697e4", "started_at": "2026-06-16T11:00:52.891344+00:00", "latency_ms": 8597, "output": " bug：`sorted(ids)` 默认按字符串的字典序比较，而不是按数值大小比较。\n\n最小修复：使用 `key=int` 把每个元素先转成整数再比较。\n\nFIX: return sorted(ids, key=int)", "usage": {"prompt_tokens": 88, "completion_tokens": 171, "total_tokens": 259, "cost": 0.0006645, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0006645, "upstream_inference_prompt_cost": 6.6e-05, "upstream_inference_completions_cost": 0.0005985}, "completion_tokens_details": {"reasoning_tokens": 122, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607655-OeCD8MFAwsvNAnrZQWx3", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*return\\s+sorted\\(ids,\\s*key\\s*=\\s*int\\)\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-005", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "memoization", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*key\\s*=\\s*\\(fn\\.__name__,\\s*args,\\s*(?:tuple\\(sorted\\(kwargs\\.items\\(\\)\\)\\)|frozenset\\(kwargs\\.items\\(\\)\\))\\)\\s*`?", "flags": "is"}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "下面缓存装饰器会把不同参数的调用混在一起。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 key 赋值行>。\n\n```python\ncache = {}\ndef memo(fn):\n def wrapper(*args, **kwargs):\n key = fn.__name__\n if key not in cache:\n cache[key] = fn(*args, **kwargs)\n return cache[key]\n return wrapper\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "fdaf2df9bffeacf442086f01d24eb1fce336e874cebec386f24acd9175c42fc6", "started_at": "2026-06-16T11:01:01.493534+00:00", "latency_ms": 12763, "output": "Bug：`key` 只使用了函数名 `fn.__name__`，没有包含 `args` 和 `kwargs`，所以不同参数的调用会命中同一条缓存。\n\n最小修复：把参数也加入 `key`，例如把 `args` 和 `kwargs` 转成可哈希的元组。\n\nFIX: `key = (fn.__name__, args, tuple(sorted(kwargs.items())))`", "usage": {"prompt_tokens": 125, "completion_tokens": 557, "total_tokens": 682, "cost": 0.00234675, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00234675, "upstream_inference_prompt_cost": 0.00011875, "upstream_inference_completions_cost": 0.002228}, "completion_tokens_details": {"reasoning_tokens": 552, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607663-bci2b7jwA7Iy5HLleJMW", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*key\\s*=\\s*\\(fn\\.__name__,\\s*args,\\s*(?:tuple\\(sorted\\(kwargs\\.items\\(\\)\\)\\)|frozenset\\(kwargs\\.items\\(\\)\\))\\)\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-006", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "aliasing", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*copied\\s*=\\s*(?:items\\.copy\\(\\)|items\\[:\\]|list\\(items\\))\\s*`?", "flags": "is"}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "下面代码期望浅拷贝列表后独立追加，但原列表也被修改。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 copy 行>。\n\n```python\ndef append_copy(items, value):\n copied = items\n copied.append(value)\n return copied\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "d79d9daa2c034ff1badc1d0951de62e17f2421bac20433e520a48c2992cae000", "started_at": "2026-06-16T11:01:14.267755+00:00", "latency_ms": 3731, "output": " Bug：`copied = items` 只是让 `copied` 和 `items` 指向同一个列表对象，没有创建副本，所以对 `copied` 的修改会反映到原列表上。\n\n最小修复：使用 `list.copy()` 进行浅拷贝。\n\nFIX: copied = items.copy()", "usage": {"prompt_tokens": 101, "completion_tokens": 163, "total_tokens": 264, "cost": 0.00064625, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00064625, "upstream_inference_prompt_cost": 7.575e-05, "upstream_inference_completions_cost": 0.0005705}, "completion_tokens_details": {"reasoning_tokens": 97, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607676-jaaCK9XpMeaM40zssbDZ", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*copied\\s*=\\s*(?:items\\.copy\\(\\)|items\\[:\\]|list\\(items\\))\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-007", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "json", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*data\\s*=\\s*(payload\\s+if\\s+isinstance\\(payload,\\s*dict\\)\\s+else\\s+json\\.loads\\(payload\\)|json\\.loads\\(payload\\)\\s+if\\s+isinstance\\(payload,\\s*\\(str,\\s*bytes,\\s*bytearray\\)\\)\\s+else\\s+payload|json\\.loads\\(payload\\)\\s+if\\s+isinstance\\(payload,\\s*str\\)\\s+else\\s+payload)\\s*`?", "flags": "is"}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "下面代码期望解析 JSON 字符串，但传入已经是 dict 时会报错。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 data 赋值行>。\n\n```python\nimport json\n\ndef load(payload):\n data = json.loads(payload)\n return data['id']\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "dae0481dbfca35623cf6eaf5f44910cc59204edc238411f6ec1221586215b6a3", "started_at": "2026-06-16T11:01:18.008193+00:00", "latency_ms": 10898, "output": "Bug：`json.loads` 只接受字符串/bytes，当 `payload` 已经是 `dict` 时会抛 `TypeError`。\n\n最小修复：先判断类型，字符串才解析，否则直接使用。\n\n```python\nimport json\n\ndef load(payload):\n data = json.loads(payload) if isinstance(payload, str) else payload\n return data['id']\n```\n\nFIX: data = json.loads(payload) if isinstance(payload, str) else payload", "usage": {"prompt_tokens": 101, "completion_tokens": 296, "total_tokens": 397, "cost": 0.00127995, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00127995, "upstream_inference_prompt_cost": 9.595e-05, "upstream_inference_completions_cost": 0.001184}, "completion_tokens_details": {"reasoning_tokens": 204, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607680-YItDy1xiPK4HHaREnwGS", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*data\\s*=\\s*(payload\\s+if\\s+isinstance\\(payload,\\s*dict\\)\\s+else\\s+json\\.loads\\(payload\\)|json\\.loads\\(payload\\)\\s+if\\s+isinstance\\(payload,\\s*\\(str,\\s*bytes,\\s*bytearray\\)\\)\\s+else\\s+payload|json\\.loads\\(payload\\)\\s+if\\s+isinstance\\(payload,\\s*str\\)\\s+else\\s+payload)\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-008", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "finally", "debugging"], "scorer": "contains_any", "expected": {"answers": ["删除 finally 中的 return None", "去掉 finally 的 return None", "不要在 finally 里 return None", "remove return None", "去掉 finally 中的 return None", "删除或替换 finally 中的 return None", "去掉 finally 中的 `return None`", "删除或替换 finally 中的 `return None`", "删除 finally 块中的 `return None`", "删除 finally 块中的 return None", "删除 finally 中的 `return None`", "删除 `finally` 块中的 `return None`", "删除 `finally` 中的 `return None`", "删除 `finally: return None`", "将 `finally:` 中的 `return None` 删除", "finally 中的 return None 删除", "finally: 中的 return None 删除", "删除 finally 块中的 'return None'", "删除 finally 子句中的 `return None`", "删除 finally 子句中的 return None", "delete the line `return None` inside the finally block", "delete the line return None inside the finally block", "finally 块不应包含 return 语句", "finally 块不应包含 return", "finally 不应包含 return"]}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "下面代码期望 finally 后仍保留 try 中返回值，但实际总是返回 None。请指出 bug，并给出最小修复。最后单独一行写 FIX: <要删除或替换的 finally 行说明>。\n\n```python\ndef read_value():\n try:\n return 42\n finally:\n return None\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "3cc6ae8fe4f15528225f040b759f5535e31e0ee3dab226c836ed3b9c19707a57", "started_at": "2026-06-16T11:01:28.917489+00:00", "latency_ms": 5085, "output": " bug：`finally` 块里写了 `return None`。在 Python 中，如果 `finally` 执行了 `return`，它会覆盖 `try` 中待返回的值，所以函数总是返回 `None`。\n\n最小修复：去掉 `finally` 里的 `return None`，让它只做清理而不返回值；如果不需要清理，也可以直接删掉整个 `finally`。\n\nFIX: 删除 finally 子句中的 `return None`（或删除整个 `finally`）", "usage": {"prompt_tokens": 105, "completion_tokens": 243, "total_tokens": 348, "cost": 0.00107175, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00107175, "upstream_inference_prompt_cost": 9.975e-05, "upstream_inference_completions_cost": 0.000972}, "completion_tokens_details": {"reasoning_tokens": 178, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607691-SBItNBPoz7XVWB4Pmytz", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"matched": ["删除 finally 子句中的 `return None`"]}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-reasoning-001", "suite": "reasoning", "case_version": "0.2.0", "tags": ["arithmetic", "multi-step"], "scorer": "exact", "expected": {"answer": "125", "normalize": true}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只回答最终数字：有 A、B、C、D 四个服务。A 每分钟处理 6 个请求，B 比 A 少 2 个，C 是 B 的 2 倍，D 是 A 和 C 的平均值。四个服务 5 分钟一共处理多少请求？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "06f9a3eb3666e5854b2b742553674373622a42e326be166231a39c67b5604810", "started_at": "2026-06-16T11:01:34.012155+00:00", "latency_ms": 2096, "output": " 125", "usage": {"prompt_tokens": 108, "completion_tokens": 74, "total_tokens": 182, "cost": 0.00034, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00034, "upstream_inference_prompt_cost": 8.1e-05, "upstream_inference_completions_cost": 0.000259}, "completion_tokens_details": {"reasoning_tokens": 71, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607696-yDL7mFrRVyK4sqa5Pl4L", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"expected": "125", "actual": " 125"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-reasoning-002", "suite": "reasoning", "case_version": "0.2.0", "tags": ["constraint-solving"], "scorer": "exact", "expected": {"answer": "D", "normalize": true}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只回答一个字母：五个任务 A、B、C、D、E 排队。A 必须在 B 前，B 必须在 C 前；D 不能在两端；E 必须紧挨在 C 后面。在所有满足条件的队列中，按字典序最小的队列第三个任务是谁？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "e273e5a0cd57aef19af9e4ccfcd445a7523180f5cab62526c14aa0e62d5c1cc9", "started_at": "2026-06-16T11:01:36.119703+00:00", "latency_ms": 6530, "output": "D", "usage": {"prompt_tokens": 100, "completion_tokens": 572, "total_tokens": 672, "cost": 0.00235693, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 33, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00235693, "upstream_inference_prompt_cost": 6.893e-05, "upstream_inference_completions_cost": 0.002288}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607698-HHOkzwkvYiCJpIcDAFAy", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"expected": "D", "actual": "D"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-reasoning-003", "suite": "reasoning", "case_version": "0.2.0", "tags": ["binary", "symbolic"], "scorer": "exact", "expected": {"answer": "0", "normalize": true}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只回答最终数字：一个 4 位二进制数从 1011 开始，先左移一位并只保留低 4 位，再与 0110 做异或，最后转成十进制。结果是多少？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "813f5aead205f4aa7a9d2a1e7b7085daae002a54592edd8d8aad2e7d7551897c", "started_at": "2026-06-16T11:01:42.659581+00:00", "latency_ms": 3980, "output": " 0", "usage": {"prompt_tokens": 87, "completion_tokens": 84, "total_tokens": 171, "cost": 0.00041865, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00041865, "upstream_inference_prompt_cost": 8.265e-05, "upstream_inference_completions_cost": 0.000336}, "completion_tokens_details": {"reasoning_tokens": 62, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607704-LZK4j1Pj1H0uWOg3wu4Z", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"expected": "0", "actual": " 0"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-reasoning-004", "suite": "reasoning", "case_version": "0.2.0", "tags": ["set", "operations"], "scorer": "exact", "expected": {"answer": "18", "normalize": true}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只回答最终数字：一个集合最初为 {1,2,3,4,5}。依次执行：删除所有偶数；加入 6 和 7；把每个元素乘以 2；删除大于 10 的元素。最终集合元素之和是多少？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "3077e41c160e4ebe361234b76e647f42583619ef446b73e7c1e25858312f328e", "started_at": "2026-06-16T11:01:46.652851+00:00", "latency_ms": 2988, "output": "18", "usage": {"prompt_tokens": 94, "completion_tokens": 98, "total_tokens": 192, "cost": 0.0004813, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0004813, "upstream_inference_prompt_cost": 8.93e-05, "upstream_inference_completions_cost": 0.000392}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607708-Y39qqyzAFiH1sMiKTiqh", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"expected": "18", "actual": "18"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-reasoning-005", "suite": "reasoning", "case_version": "0.2.0", "tags": ["logic", "sat"], "scorer": "exact", "expected": {"answer": "可满足", "normalize": true}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只回答“可满足”或“不可满足”：有三个布尔变量 x、y、z。约束为：x 或 y 为真；如果 x 为真则 z 为假；如果 y 为真则 z 为真；x 和 y 不能同时为真。是否存在赋值满足全部约束？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "1e534bd21af5e75f0c9fd61e3d5a3f660355d4555e34e16a06744234da47e006", "started_at": "2026-06-16T11:01:49.653100+00:00", "latency_ms": 2433, "output": " 可满足", "usage": {"prompt_tokens": 105, "completion_tokens": 100, "total_tokens": 205, "cost": 0.00042875, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00042875, "upstream_inference_prompt_cost": 7.875e-05, "upstream_inference_completions_cost": 0.00035}, "completion_tokens_details": {"reasoning_tokens": 97, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607711-cXhVP35z8PgpgW0AwPP3", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"expected": "可满足", "actual": " 可满足"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-001", "suite": "rag_long_context", "case_version": "0.2.0", "tags": ["rag", "grounded"], "scorer": "text_rules", "expected": {"required": ["人工抽检"], "required_any": [["默认使用", "默认判分", "默认采用", "作为默认判分"]], "forbidden": ["因为成本太高", "因为不支持中文"], "max_chars": 160}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只根据资料回答。\n\n资料 A：DracoBench v0.2 的目标是提高区分度，优先增加 coding、debugging、RAG 和 instruction_following 题。\n资料 B：DracoBench v0.2 不会默认使用 LLM-as-judge；开放中文写作题只做少量规则校验和人工抽检。\n资料 C：v0.2 的 HTML 报告必须展示通过率、成本、reasoning tokens、失败样例和逐题明细。\n\n问题：v0.2 为什么没有把 LLM-as-judge 作为默认判分？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "7a40b395b42a59b621957d70755d39fca26dba23f4e0c46743018935350319d3", "started_at": "2026-06-16T11:01:52.098577+00:00", "latency_ms": 4157, "output": "根据资料 B，v0.2 不默认使用 LLM-as-judge，但资料中并未说明具体原因，只提到开放中文写作题采用少量规则校验和人工抽检。", "usage": {"prompt_tokens": 157, "completion_tokens": 333, "total_tokens": 490, "cost": 0.00148115, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00148115, "upstream_inference_prompt_cost": 0.00014915, "upstream_inference_completions_cost": 0.001332}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607714-N40VFbfuWCJLrxSwLm7T", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 68, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-002", "suite": "rag_long_context", "case_version": "0.2.0", "tags": ["rag", "tradeoff", "abstain"], "scorer": "text_rules", "expected": {"required": ["Beta", "成本", "延迟", "判断"], "forbidden": ["Alpha 更适合", "多模态更强"], "max_chars": 180}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只根据资料回答，不要自行补充。\n\n资料：模型 Alpha 在 30 道 challenge 题中通过 24 道，成本 0.08 美元，平均延迟 9 秒。模型 Beta 通过 22 道，成本 0.02 美元，平均延迟 3 秒。资料没有给出两者在多模态任务上的表现。\n\n问题：如果要写低成本高吞吐摘要服务，资料更支持选择哪个模型？另外，多模态表现能否判断？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "b25dfce277314b219ab8ccef6f02fb644e23cd169765867993ae58ccd7258c4a", "started_at": "2026-06-16T11:01:56.269212+00:00", "latency_ms": 4993, "output": "资料更支持选择 **Beta**：成本低（0.02 美元 vs 0.08 美元）、延迟低（3 秒 vs 9 秒），更适合低成本高吞吐场景；通过率虽略低（22 vs 24），但资料未说明这与摘要任务的实际质量直接相关。\n\n多模态表现**无法判断**，因为资料没有给出两者在多模态任务上的表现。", "usage": {"prompt_tokens": 140, "completion_tokens": 291, "total_tokens": 431, "cost": 0.001297, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.001297, "upstream_inference_prompt_cost": 0.000133, "upstream_inference_completions_cost": 0.001164}, "completion_tokens_details": {"reasoning_tokens": 226, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607718-tslsLvaIgSkdHm2JTvK9", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 145, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-003", "suite": "rag_long_context", "case_version": "0.2.0", "tags": ["rag", "nuance"], "scorer": "text_rules", "expected": {"required": ["题面歧义"], "required_any": [["47/50", "47 题", "47题"], ["空输出", "输出为空", "未输出"]], "forbidden": ["满分", "完全失败"], "max_chars": 240}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只根据资料回答。\n\n资料：一次评测中，K 模型在 smoke set 上 7/7，通过率 100%；在 hard set 上原始结果 47/50，其中 2 题后来被认定为题面歧义，单独复测通过。另有 1 题因 reasoning tokens 用尽而空输出。\n\n问题：更公平的文字结论应该如何描述 K 模型这次 hard set 表现？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "12db30955792c48368632f01aa0a9c06e9fc27004c4dbf12ce602cb8488494e6", "started_at": "2026-06-16T11:02:01.273925+00:00", "latency_ms": 10433, "output": " 更公平的描述是：\n\nK 模型在 hard set 上的有效成绩应为 **49/50（98%）**。原始 47/50 中，有 2 题因题面歧义经单独复测通过；另有 1 题因 reasoning tokens 用尽而空输出，应视为未通过。因此，唯一未通过的题目是 token 限制导致的，而非解题能力问题。", "usage": {"prompt_tokens": 125, "completion_tokens": 925, "total_tokens": 1050, "cost": 0.00381875, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00381875, "upstream_inference_prompt_cost": 0.00011875, "upstream_inference_completions_cost": 0.0037}, "completion_tokens_details": {"reasoning_tokens": 923, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607723-TDIL39y6gERKEOVW7cES", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 151, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-004", "suite": "rag_long_context", "case_version": "0.2.0", "tags": ["rag", "abstain"], "scorer": "text_rules", "expected": {"required": ["不能", "不包含", "利润率"], "forbidden": ["可以判断", "训练数据"], "max_chars": 100}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只根据资料回答，不要使用资料外知识。\n\n资料：报告字段包括 pass_rate、avg_latency_ms、total_cost、prompt_tokens、completion_tokens、reasoning_tokens。报告不包含模型训练数据来源，也不包含供应商真实利润率。\n\n问题：根据资料，能否从报告判断供应商利润率？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "cb2d9baeb98b0b4836972058965359b461f03aaba6cd096f40ffc813ce331880", "started_at": "2026-06-16T11:02:11.720539+00:00", "latency_ms": 4749, "output": "不能。报告不包含供应商真实利润率，因此无法从报告中判断供应商利润率。", "usage": {"prompt_tokens": 95, "completion_tokens": 124, "total_tokens": 219, "cost": 0.00058625, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00058625, "upstream_inference_prompt_cost": 9.025e-05, "upstream_inference_completions_cost": 0.000496}, "completion_tokens_details": {"reasoning_tokens": 136, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607733-cG9Grf8ZHfIxyBhXbwEg", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 34, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-if-001", "suite": "instruction_following", "case_version": "0.2.0", "tags": ["json", "nested"], "scorer": "json_schema_lite", "expected": {"schema": {"type": "object", "required": ["status", "scores", "note"], "additionalProperties": false, "properties": {"status": {"type": "string", "const": "review"}, "scores": {"type": "object", "required": ["coding", "debugging", "rag"], "additionalProperties": false, "properties": {"coding": {"type": "integer"}, "debugging": {"type": "integer"}, "rag": {"type": "integer"}}}, "note": {"type": "string"}}}}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 JSON 对象，不要 Markdown。字段 status 必须是 \"review\"；字段 scores 必须是对象，包含 coding、debugging、rag 三个整数；字段 note 必须是不超过 12 个汉字的中文字符串。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "7f670ae329c67bf1957a977815256b403ae7965cb15f2d2db520256cc3f2eb77", "started_at": "2026-06-16T11:02:16.480103+00:00", "latency_ms": 5827, "output": " {\"status\": 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个汉字。必须同时包含“难题”和“区分度”，不能包含“最强”“吊打”“遥遥领先”。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "63d393d3332e09c8d34bfa5fceb4812734bf76c2333f7e6d1585cf977944f0db", "started_at": "2026-06-16T11:02:25.653257+00:00", "latency_ms": 2303, "output": " 这道难题的区分度很高，能拉开考生水平。", "usage": {"prompt_tokens": 71, "completion_tokens": 186, "total_tokens": 257, "cost": 0.00070425, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00070425, "upstream_inference_prompt_cost": 5.325e-05, "upstream_inference_completions_cost": 0.000651}, "completion_tokens_details": {"reasoning_tokens": 172, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607747-nyXVVcnPAEGcEM6IXb0V", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 19, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-zh-writing-001", "suite": "chinese_writing", "case_version": "0.2.0", "tags": ["wechat", "conclusion"], "scorer": "text_rules", "expected": {"required": ["简单题", "真实能力", "失败样例"], "forbidden": ["吊打"], "max_chars": 120}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "写一段不超过 120 个汉字的公众号结论，主题是“模型在简单题满分不代表真实强”。必须包含“简单题”“真实能力”“失败样例”，不能出现“吊打”。", "parameters": {"temperature": 0.2, "max_tokens": 16384, "seed": null}, "prompt_hash": "f330d4a7913b830c15df0d2a36cf0a9e5c07628ef6fa52408cc1bd2e90074762", "started_at": "2026-06-16T11:02:27.969417+00:00", "latency_ms": 3721, "output": " 简单题满分只是基础，不等于模型真实能力过硬。一旦遇到复杂场景，失败样例便会暴露其推理短板。评价模型，不能只看满分，更要关注真实能力。", "usage": {"prompt_tokens": 78, "completion_tokens": 259, "total_tokens": 337, "cost": 0.000965, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.000965, "upstream_inference_prompt_cost": 5.85e-05, "upstream_inference_completions_cost": 0.0009065}, "completion_tokens_details": {"reasoning_tokens": 153, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607750-qiP66WCTspgjDGfYT4Ay", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 66, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-zh-writing-002", "suite": "chinese_writing", "case_version": "0.2.0", "tags": ["rewrite", "zh"], "scorer": "text_rules", "expected": {"required": ["复杂调试", "稳定性"], "forbidden": ["猛", "掉链子"], "max_chars": 80}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "把下面口语句改写成专业表达，不超过 80 个汉字：这个模型看起来很猛，但一遇到复杂调试就开始掉链子。必须包含“复杂调试”和“稳定性”，不能包含“猛”“掉链子”。", "parameters": {"temperature": 0.2, "max_tokens": 16384, "seed": null}, "prompt_hash": "1628d5e9cbea22d0750b547f0818eafa82d503dcad8fdc41ef2f523f9fbb55a1", "started_at": "2026-06-16T11:02:31.700797+00:00", "latency_ms": 8173, "output": " 该模型在常规场景下表现优异，但在复杂调试中稳定性不足。", "usage": {"prompt_tokens": 85, "completion_tokens": 223, "total_tokens": 308, "cost": 0.00097275, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00097275, "upstream_inference_prompt_cost": 8.075e-05, "upstream_inference_completions_cost": 0.000892}, "completion_tokens_details": {"reasoning_tokens": 191, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607753-nfWBG2MVHqKYeZqTuxFN", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 27, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-009", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "aggregation", "dirty-input"], "scorer": "code_python_tests", "expected": {"tests": ["events=[{'user':'b','type':'add','amount':'5'},{'user':'a','type':'add','amount':3},{'user':'b','type':'remove','amount':2},{'user':'a','type':'remove','amount':3}]\nassert solution.solve(events) == {'b': 3}", "assert solution.solve([]) == {}", "assert solution.solve([{'user':'x','type':'remove','amount':'2'}]) == {'x': -2}"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(events: list[dict]) -> dict[str, int]。每个事件包含 user、type、amount；type 为 \"add\" 或 \"remove\"。按 user 汇总 add 减 remove 后的库存，结果中去掉库存为 0 的用户，按 key 字典序返回普通 dict。amount 可能是字符串数字。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "9b81c7f8e34dbf12cfabd35ebb618802fe09200deca1d146558b4e1c12e6fd1e", "started_at": "2026-06-16T11:02:39.886735+00:00", "latency_ms": 7375, "output": "```python\nfrom collections import defaultdict\n\ndef solve(events: list[dict]) -> dict[str, int]:\n inventory = defaultdict(int)\n for event in events:\n user = event[\"user\"]\n amount = int(event[\"amount\"])\n if event[\"type\"] == \"add\":\n inventory[user] += amount\n else:\n inventory[user] -= amount\n return dict(sorted((k, v) for k, v in inventory.items() if v != 0))\n```", "usage": {"prompt_tokens": 116, "completion_tokens": 400, "total_tokens": 516, "cost": 0.0017102, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0017102, "upstream_inference_prompt_cost": 0.0001102, "upstream_inference_completions_cost": 0.0016}, "completion_tokens_details": {"reasoning_tokens": 355, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607762-rwKk7Euw7ebUsVBObHA6", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-010", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "parser", "expression"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve('1 + 2 - 3') == 0", "assert solution.solve('10 - (2 + 3) + 4') == 9", "assert solution.solve('(1+(4+5+2)-3)+(6+8)') == 23"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(expr: str) -> int。expr 只包含非负整数、+、-、空格和括号，计算表达式结果。不要使用 eval。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "662cadd9b4e3fdcfdf38e1d7338201fe3049d948576c89303695cff58950b3b4", "started_at": "2026-06-16T11:02:47.316082+00:00", "latency_ms": 43554, "output": "```python\ndef solve(expr: str) -> int:\n s = expr\n n = len(s)\n i = 0\n\n def parse_expr():\n nonlocal i\n val = parse_term()\n while i < n and s[i].isspace():\n i += 1\n while i < n and s[i] in '+-':\n op = s[i]\n i += 1\n rhs = parse_term()\n val = val + rhs if op == '+' else val - rhs\n while i < n and s[i].isspace():\n i += 1\n return val\n\n def parse_term():\n nonlocal i\n while i < n and s[i].isspace():\n i += 1\n sign = 1\n while i < n and s[i] in '+-':\n if s[i] == '-':\n sign = -sign\n i += 1\n while i < n and s[i].isspace():\n i += 1\n while i < n and s[i].isspace():\n i += 1\n if i < n and s[i] == '(':\n i += 1\n val = parse_expr()\n while i < n and s[i].isspace():\n i += 1\n if i < n and s[i] == ')':\n i += 1\n else:\n val = 0\n while i < n and s[i].isdigit():\n val = val * 10 + (ord(s[i]) - 48)\n i += 1\n return sign * val\n\n return parse_expr()\n```", "usage": {"prompt_tokens": 77, "completion_tokens": 2807, "total_tokens": 2884, "cost": 0.01130115, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.01130115, "upstream_inference_prompt_cost": 7.315e-05, "upstream_inference_completions_cost": 0.011228}, "completion_tokens_details": {"reasoning_tokens": 2485, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607769-5CtZVauQoZYzrWlrI71A", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-011", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "sorting", "dedupe"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve(['alice 10','bob 12','alice 15','','bob 11']) == [('alice',15),('bob',12)]", "assert solution.solve(['x -1','a -1','b 0']) == [('b',0),('a',-1),('x',-1)]"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(rows: list[str]) -> list[tuple[str, int]]。每行格式为 \"name score\"，空白数量不定；同名保留最高分；输出按分数降序、同分按 name 升序。忽略空行。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "332bccf5652506856c633d7093431279279a22b2d3a99762f6cba55df7d884af", "started_at": "2026-06-16T11:03:30.965633+00:00", "latency_ms": 5505, "output": "```python\ndef solve(rows: list[str]) -> list[tuple[str, int]]:\n best: dict[str, int] = {}\n for line in rows:\n parts = line.split()\n if not parts:\n continue\n name, score = parts[0], int(parts[1])\n if name not in best or score > best[name]:\n best[name] = score\n return sorted(best.items(), key=lambda x: (-x[1], x[0]))\n```", "usage": {"prompt_tokens": 95, "completion_tokens": 301, "total_tokens": 396, "cost": 0.00129425, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00129425, "upstream_inference_prompt_cost": 9.025e-05, "upstream_inference_completions_cost": 0.001204}, "completion_tokens_details": {"reasoning_tokens": 241, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607813-XpBlCsxyd9mwjjwBJqOP", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-012", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "wildcard", "dp"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve('a*b?d', 'axxxbc d'.replace(' ','')) is True", "assert solution.solve('a*c', 'ab') is False", "assert solution.solve('*', '') is True", "assert solution.solve('file-??.txt', 'file-ab.txt') is True"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(pattern: str, text: str) -> bool。pattern 支持 ? 匹配任意单字符，* 匹配任意长度字符串。必须匹配完整 text。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "0ac24584e5856726a6e962c43819ac539910b115bdabb48f973f04258dd562d6", "started_at": "2026-06-16T11:03:36.514536+00:00", "latency_ms": 4368, "output": " ```python\ndef solve(pattern: str, text: str) -> bool:\n m, n = len(pattern), len(text)\n dp = [[False] * (n + 1) for _ in range(m + 1)]\n dp[0][0] = True\n for i in range(1, m + 1):\n if pattern[i - 1] == '*':\n dp[i][0] = dp[i - 1][0]\n for j in range(1, n + 1):\n p = pattern[i - 1]\n if p == '*':\n dp[i][j] = dp[i - 1][j] or dp[i][j - 1]\n elif p == '?' or p == text[j - 1]:\n dp[i][j] = dp[i - 1][j - 1]\n return dp[m][n]\n```", "usage": {"prompt_tokens": 81, "completion_tokens": 413, "total_tokens": 494, "cost": 0.00172895, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00172895, "upstream_inference_prompt_cost": 7.695e-05, "upstream_inference_completions_cost": 0.001652}, "completion_tokens_details": {"reasoning_tokens": 193, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607818-lL6udR98VpEYOVzNdqYO", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-013", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "recursion", "flatten"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve({'a': {'b': 1, 'c': 'x'}, 'd': 2}) == ['a.b=1','a.c=x','d=2']", "assert solution.solve({'z': {'a': {'b': 3}}}) == ['z.a.b=3']", "assert solution.solve({}) == []"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(tree: dict) -> list[str]。tree 是嵌套字典，叶子是字符串或数字。返回所有叶子的路径，路径用点连接，按字典序排序。例如 {'a': {'b': 1}} -> ['a.b=1']。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "e658784bcc7118c9f5e1375c7f1f92aa8147c38fb8790138603de7f2b3722c98", "started_at": "2026-06-16T11:03:40.927185+00:00", "latency_ms": 4825, "output": "```python\ndef solve(tree: dict) -> list[str]:\n out = []\n\n def dfs(node, path):\n for k, v in node.items():\n cur = f\"{path}.{k}\" if path else k\n if isinstance(v, dict):\n dfs(v, cur)\n else:\n out.append(f\"{cur}={v}\")\n\n dfs(tree, \"\")\n return sorted(out)\n```", "usage": {"prompt_tokens": 103, "completion_tokens": 241, "total_tokens": 344, "cost": 0.00106185, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00106185, "upstream_inference_prompt_cost": 9.785e-05, "upstream_inference_completions_cost": 0.000964}, "completion_tokens_details": {"reasoning_tokens": 154, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607823-yRhmPe3tP3ukrNltv7Ja", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-014", "suite": "coding", "case_version": "0.2.0", "tags": ["python", "dynamic-programming"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve([1,-2,0,3]) == 4", "assert solution.solve([1,-2,-2,3]) == 3", "assert solution.solve([-1,-1,-1]) == -1", "assert solution.solve([2,1,-2,3]) == 6"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(nums: list[int]) -> int。返回删除恰好一个元素后，剩余数组的最大连续子数组和。nums 长度至少为 2，可以全为负数。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "a7a5de11dacd1864c7d44a3ce983c2f127d1bcff88bec3b15f8727c513f56ea2", "started_at": "2026-06-16T11:03:45.797515+00:00", "latency_ms": 212429, "output": " ```python\ndef solve(nums: list[int]) -> int:\n n = len(nums)\n left_end = [0] * n\n left_best = [0] * n\n left_end[0] = left_best[0] = nums[0]\n for i in range(1, n):\n left_end[i] = max(nums[i], left_end[i - 1] + nums[i])\n left_best[i] = max(left_best[i - 1], left_end[i])\n\n right_start = [0] * n\n right_best = [0] * n\n right_start[-1] = right_best[-1] = nums[-1]\n for i in range(n - 2, -1, -1):\n right_start[i] = max(nums[i], right_start[i + 1] + nums[i])\n right_best[i] = max(right_best[i + 1], right_start[i])\n\n ans = float('-inf')\n for i in range(n):\n cur = float('-inf')\n if i > 0:\n cur = max(cur, left_best[i - 1])\n if i + 1 < n:\n cur = max(cur, right_best[i + 1])\n if i > 0 and i + 1 < n:\n cur = max(cur, left_end[i - 1] + right_start[i + 1])\n ans = max(ans, cur)\n return ans\n```", "usage": {"prompt_tokens": 84, "completion_tokens": 7342, "total_tokens": 7426, "cost": 0.0294478, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0294478, "upstream_inference_prompt_cost": 7.98e-05, "upstream_inference_completions_cost": 0.029368}, "completion_tokens_details": {"reasoning_tokens": 6722, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781607828-5FBV5vMuphILITKP8GuA", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-009", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "parsing", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*return\\s+\\[part\\.strip\\(\\)\\s+for\\s+part\\s+in\\s+s\\.split\\('\\,'\\)\\s+if\\s+part\\.strip\\(\\)\\]\\s*`?", "flags": "is"}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "下面代码期望把输入按逗号拆分并去掉空白，但会把空字段也保留下来。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 return 行>。\n\n```python\ndef parse(s):\n return [part.strip() for part in s.split(',')]\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "fc78c43e70a6a2fe59904be00b93d579300af6ba72fe5a9629bfe5bd82fad3d6", "started_at": "2026-06-16T11:07:18.270118+00:00", "latency_ms": 5819, "output": "Bug：`s.split(',')` 在输入为空或包含连续逗号时会产生空字符串，`part.strip()` 后仍是空字符串，但列表推导式没有过滤掉它们。\n\n最小修复：在推导式中加入 `if part.strip()` 条件。\n\nFIX: return [part.strip() for part in s.split(',') if part.strip()]", "usage": {"prompt_tokens": 102, "completion_tokens": 299, "total_tokens": 401, "cost": 0.0012929, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0012929, "upstream_inference_prompt_cost": 9.69e-05, "upstream_inference_completions_cost": 0.001196}, "completion_tokens_details": {"reasoning_tokens": 225, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608040-XT4XZ1iJKkZFT43h1PjB", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*return\\s+\\[part\\.strip\\(\\)\\s+for\\s+part\\s+in\\s+s\\.split\\('\\,'\\)\\s+if\\s+part\\.strip\\(\\)\\]\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-010", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "datetime", "debugging"], "scorer": "contains_any", "expected": {"answers": ["datetime.fromisoformat", "dateutil.parser", "解析 ts 后排序", "parse ts", "fromisoformat", "int(r['ts'])", "float(r['ts'])", "key=lambda r: int(r['ts'])", "key=lambda r: float(r['ts'])"]}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "下面代码期望用 UTC 时间戳排序，但字符串排序会错。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 sort 行>。\n\n```python\nrows.sort(key=lambda r: r['ts'])\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "c0d491a68f215902d8b314423a6ab9aea7ac0782e1a34e6d6997670c2ddb8458", "started_at": "2026-06-16T11:07:24.102290+00:00", "latency_ms": 6474, "output": " Bug：`r['ts']` 是字符串，按字符串字典序排序不能保证时间先后顺序（例如格式不一致、时区不同、缺零补位时都会出错）。\n\n最小修复：把字符串解析成 `datetime` 对象再排序。\n\nFIX: `rows.sort(key=lambda r: datetime.fromisoformat(r['ts'].replace('Z', '+00:00')))`", "usage": {"prompt_tokens": 90, "completion_tokens": 513, "total_tokens": 603, "cost": 0.001863, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.001863, "upstream_inference_prompt_cost": 6.75e-05, "upstream_inference_completions_cost": 0.0017955}, "completion_tokens_details": {"reasoning_tokens": 433, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608046-SGtn9R2OZSk9VCXCMKUF", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"matched": ["datetime.fromisoformat", "fromisoformat"]}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-011", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "truthiness", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*(?:limit\\s*=\\s*10\\s+if\\s+limit\\s+is\\s+None\\s+else\\s+limit|limit\\s*=\\s*limit\\s+if\\s+limit\\s+is\\s+not\\s+None\\s+else\\s+10|if\\s+limit\\s+is\\s+None\\s*:\\s*limit\\s*=\\s*10)\\s*`?", "flags": "is"}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "下面代码在输入包含 0 时会误判为默认值 10。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 limit 赋值行>。\n\n```python\ndef query(limit=None):\n limit = limit or 10\n return list(range(limit))\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "81dfcde4613fe16d52b7386d005b50beaafcb9916e6cb6c0d326eab3c808a843", "started_at": "2026-06-16T11:07:30.590832+00:00", "latency_ms": 5083, "output": "bug 在于 `limit or 10` 会把所有“假值”都当成未传参，包括合法的 `0`。\n\n最小修复是仅在 `limit` 为 `None` 时才使用默认值：\n\n```python\ndef query(limit=None):\n limit = 10 if limit is None else limit\n return list(range(limit))\n```\n\nFIX: limit = 10 if limit is None else limit", "usage": {"prompt_tokens": 98, "completion_tokens": 337, "total_tokens": 435, "cost": 0.0014411, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0014411, "upstream_inference_prompt_cost": 9.31e-05, "upstream_inference_completions_cost": 0.001348}, "completion_tokens_details": {"reasoning_tokens": 260, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608052-wS2IVYCLJ0gE9XCvuQgb", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*(?:limit\\s*=\\s*10\\s+if\\s+limit\\s+is\\s+None\\s+else\\s+limit|limit\\s*=\\s*limit\\s+if\\s+limit\\s+is\\s+not\\s+None\\s+else\\s+10|if\\s+limit\\s+is\\s+None\\s*:\\s*limit\\s*=\\s*10)\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-012", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "deepcopy", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*copied\\s*=\\s*(?:copy\\.deepcopy\\(config\\)|__import__\\(['\\\"]copy['\\\"]\\)\\.deepcopy\\(config\\))\\s*`?", "flags": "is"}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "下面代码期望复制嵌套配置后修改副本，但原配置也被修改。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 copied 赋值行>。\n\n```python\ndef update(config):\n copied = dict(config)\n copied['db']['host'] = 'localhost'\n return copied\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "b9ce1efc39e6db4861310a8b269b4f7a5f68b90016ca7ebbef71eb8b6b011913", "started_at": "2026-06-16T11:07:35.690366+00:00", "latency_ms": 3622, "output": "bug：`dict(config)` 只是浅拷贝，嵌套的 `config['db']` 字典仍被原配置和副本共享，所以修改副本里的嵌套字段会改到原配置。\n\n最小修复：使用深拷贝。\n\nFIX: `copied = copy.deepcopy(config)`", "usage": {"prompt_tokens": 106, "completion_tokens": 137, "total_tokens": 243, "cost": 0.0006487, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0006487, "upstream_inference_prompt_cost": 0.0001007, "upstream_inference_completions_cost": 0.000548}, "completion_tokens_details": {"reasoning_tokens": 93, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608057-HwN96RpZB1w545BhsGar", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*copied\\s*=\\s*(?:copy\\.deepcopy\\(config\\)|__import__\\(['\\\"]copy['\\\"]\\)\\.deepcopy\\(config\\))\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-013", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "generator", "debugging"], "scorer": "regex", "expected": {"pattern": "\\*{0,2}FIX\\*{0,2}:\\*{0,2}\\s*`?\\s*return\\s+next\\(\\(u\\s+for\\s+u\\s+in\\s+users\\s+if\\s+u\\['name'\\]\\s*==\\s*name\\),\\s*None\\)\\s*`?", "flags": "is"}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "下面代码期望找到第一个匹配项，但找不到时会抛 StopIteration。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 return 行>。\n\n```python\ndef find_user(users, name):\n return next(u for u in users if u['name'] == name)\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "3f10be3c52149f96743fe37c0fb7327abfb5c8d4b9310088d76b04282b552f5b", "started_at": "2026-06-16T11:07:39.325987+00:00", "latency_ms": 9762, "output": "Bug：`next()` 在迭代器耗尽且没有提供默认值时会抛出 `StopIteration`。\n\n最小修复：给 `next()` 加上默认值 `None`，并把生成器表达式用括号括起来。\n\nFIX: return next((u for u in users if u['name'] == name), None)", "usage": {"prompt_tokens": 102, "completion_tokens": 401, "total_tokens": 503, "cost": 0.00167562, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 32, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00167562, "upstream_inference_prompt_cost": 7.162e-05, "upstream_inference_completions_cost": 0.001604}, "completion_tokens_details": {"reasoning_tokens": 0, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608061-7TQA6mQR3ayNZtshnHko", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "\\*{0,2}FIX\\*{0,2}:\\*{0,2}\\s*`?\\s*return\\s+next\\(\\(u\\s+for\\s+u\\s+in\\s+users\\s+if\\s+u\\['name'\\]\\s*==\\s*name\\),\\s*None\\)\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-014", "suite": "debugging", "case_version": "0.2.0", "tags": ["python", "mutable-default", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*(?:```(?:python)?\\s*)?`?\\s*def\\s+log_request\\(req,\\s*logs=None\\)\\s*:", "flags": "is"}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "下面代码期望按请求顺序记录日志，但默认参数导致多次调用共用同一个列表。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的函数定义行>。\n\n```python\ndef log_request(req, logs=[]):\n logs.append(req['id'])\n return logs\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "2131fc867d62d7093265e77811a401805ff12d38e7bbdc5e8797b3d01b4c8c59", "started_at": "2026-06-16T11:07:49.096942+00:00", "latency_ms": 15072, "output": " bug：Python 的默认参数在函数定义时求值，`logs=[]` 会让所有调用共享同一个列表对象，导致多次调用的记录互相污染。\n\n最小修复：将默认值改为 `None`，在函数内部按需创建新列表。\n\nFIX: def log_request(req, logs=None): logs = [] if logs is None else logs; logs.append(req['id']); return logs", "usage": {"prompt_tokens": 102, "completion_tokens": 1020, "total_tokens": 1122, "cost": 0.0036465, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0036465, "upstream_inference_prompt_cost": 7.65e-05, "upstream_inference_completions_cost": 0.00357}, "completion_tokens_details": {"reasoning_tokens": 955, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608071-BlYhbHKEiPsxhPzUlPEr", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*(?:```(?:python)?\\s*)?`?\\s*def\\s+log_request\\(req,\\s*logs=None\\)\\s*:"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-reasoning-006", "suite": "reasoning", "case_version": "0.2.0", "tags": ["symbolic", "sequence"], "scorer": "exact", "expected": {"answer": "3", "normalize": true}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只回答最终数字：一个队列从左到右是 A,B,C,D,E。依次执行：把第 2 个移到末尾；删除第 3 个；在最前面插入 X；把最后两个反转。最终队列中 C 的位置是第几位？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "0defd3c3114d287777b39b65961dfa6fd7469da02e6c49a8c170b4f1be17f971", "started_at": "2026-06-16T11:08:04.182023+00:00", "latency_ms": 8695, "output": "3", "usage": {"prompt_tokens": 93, "completion_tokens": 234, "total_tokens": 327, "cost": 0.00102435, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00102435, "upstream_inference_prompt_cost": 8.835e-05, "upstream_inference_completions_cost": 0.000936}, "completion_tokens_details": {"reasoning_tokens": 232, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608086-ppzosgoXjpjBt6bv5zJR", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"expected": 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"video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0002707, "upstream_inference_prompt_cost": 6.27e-05, "upstream_inference_completions_cost": 0.000208}, "completion_tokens_details": {"reasoning_tokens": 45, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608095-uwJI6Abrjk6WZ1OIBJEx", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"expected": "120", "actual": "120"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-005", "suite": "rag_long_context", "case_version": "0.2.0", "tags": ["rag", "mode-comparison"], "scorer": "text_rules", "expected": {"required": ["ability mode", "efficiency mode", "真实能力", "低预算"], "forbidden": ["只看一个模式"], "max_chars": 180}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": 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"text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-reasoning-008", "suite": "reasoning", "case_version": "0.3.0", "tags": ["state-tracking", "branching"], "scorer": "exact", "expected": {"answer": "15", "normalize": true}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只回答最终数字：变量初始为 x=2, y=5, z=1。若 x list[str]，解析一行简化 CSV：逗号分隔；字段可以用双引号包裹；引号内逗号保留；引号内两个连续双引号表示一个双引号；空字段保留；空格是普通字符，不要自动 trim。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "81b6be132a0538b92491e39887550c116b7f09684b97f8dd1ad7df5426e97adb", "started_at": "2026-06-16T11:10:07.967676+00:00", "latency_ms": 45843, "output": "```python\ndef solve(line: str) -> list[str]:\n res: list[str] = []\n cur: list[str] = []\n in_quote = False\n i = 0\n n = len(line)\n\n while i < n:\n if in_quote:\n if line[i] == '\"':\n if i + 1 < n and line[i + 1] == '\"':\n cur.append('\"')\n i += 2\n else:\n in_quote = False\n i += 1\n else:\n cur.append(line[i])\n i += 1\n else:\n if line[i] == '\"':\n in_quote = True\n i += 1\n elif line[i] == ',':\n res.append(''.join(cur))\n cur = []\n i += 1\n else:\n cur.append(line[i])\n i += 1\n\n res.append(''.join(cur))\n return res\n```", "usage": {"prompt_tokens": 104, "completion_tokens": 2815, "total_tokens": 2919, "cost": 0.0113588, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0113588, "upstream_inference_prompt_cost": 9.88e-05, "upstream_inference_completions_cost": 0.01126}, "completion_tokens_details": {"reasoning_tokens": 2836, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608210-yE8UpZl8xSnf3pSnW308", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-016", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "intervals", "sorting"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve([(5,7),(1,2),(3,4),(10,10)]) == [(1,7),(10,10)]", "assert solution.solve([(1,1),(3,3)]) == [(1,1),(3,3)]", "assert solution.solve([]) == []"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(intervals: list[tuple[int, int]]) -> list[tuple[int, int]]。intervals 是整数闭区间，先按起点排序；重叠或端点相邻的区间要合并，例如 [1,2] 和 [3,4] 合并为 [1,4]。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "6dc22c1e6ae004a46c47dc11d5cc9ed5d57f09ec77549ff0ada57b459929d814", "started_at": "2026-06-16T11:10:53.871095+00:00", "latency_ms": 5227, "output": "```python\ndef solve(intervals: list[tuple[int, int]]) -> list[tuple[int, int]]:\n if not intervals:\n return []\n intervals = sorted(intervals, key=lambda x: x[0])\n merged = [intervals[0]]\n for s, e in intervals[1:]:\n last_s, last_e = merged[-1]\n if s <= last_e + 1:\n merged[-1] = (last_s, max(last_e, e))\n else:\n merged.append((s, e))\n return merged\n```", "usage": {"prompt_tokens": 110, "completion_tokens": 237, "total_tokens": 347, "cost": 0.0010525, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0010525, "upstream_inference_prompt_cost": 0.0001045, "upstream_inference_completions_cost": 0.000948}, "completion_tokens_details": {"reasoning_tokens": 122, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608256-3EGdPEOV2R9oW1VvTkww", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-017", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "rate-limit", "state"], "scorer": "code_python_tests", "expected": {"tests": ["events=[('a',1),('a',2),('a',3),('a',4),('a',8)]\nassert solution.solve(events, 5, 2) == [True, True, False, False, True]", "assert solution.solve([('x',10),('x',11),('x',16)], 5, 1) == [True, False, True]"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(events: list[tuple[str, int]], window: int, limit: int) -> list[bool]，模拟按用户限流。events 按时间非降序排列。某用户在当前事件时间 ts 的窗口 (ts-window, ts] 内，已放行事件数少于 limit 才放行；被拒绝的事件不计入窗口。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "1539217453d6af4bac3c7abfbd8df43ed131cd647e58a0ad2a5a670794a91f80", "started_at": "2026-06-16T11:10:59.154814+00:00", "latency_ms": 15517, "output": "```python\nfrom collections import deque\n\ndef solve(events: list[tuple[str, int]], window: int, limit: int) -> list[bool]:\n user_windows: dict[str, deque[int]] = {}\n res: list[bool] = []\n for user, ts in events:\n q = user_windows.setdefault(user, deque())\n while q and q[0] <= ts - window:\n q.popleft()\n if len(q) < limit:\n q.append(ts)\n res.append(True)\n else:\n res.append(False)\n return res\n```", "usage": {"prompt_tokens": 118, "completion_tokens": 354, "total_tokens": 472, "cost": 0.0015281, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0015281, "upstream_inference_prompt_cost": 0.0001121, "upstream_inference_completions_cost": 0.001416}, "completion_tokens_details": {"reasoning_tokens": 271, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608261-W3oN1pxcnmoVLiumkbtu", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-018", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "path", "stack"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve('/a//b/./c/../') == '/a/b'", "assert solution.solve('/../../x') == '/x'", "assert solution.solve('/') == '/'"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(path: str) -> str，规范化绝对 Unix 路径：处理重复斜杠、.、..；.. 在根目录时仍留在根目录；返回结果必须以 / 开头且除根目录外不能以 / 结尾。不要使用 os.path。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "92e706f1062d7652c2f14c514c44602c6708e65d87771889d3aff7450e33e85d", "started_at": "2026-06-16T11:11:14.730890+00:00", "latency_ms": 13465, "output": "```python\ndef solve(path: str) -> str:\n stack = []\n for part in path.split('/'):\n if part == '' or part == '.':\n continue\n if part == '..':\n if stack:\n stack.pop()\n else:\n stack.append(part)\n return '/' + '/'.join(stack)\n```", "usage": {"prompt_tokens": 100, "completion_tokens": 629, "total_tokens": 729, "cost": 0.002611, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.002611, "upstream_inference_prompt_cost": 9.5e-05, "upstream_inference_completions_cost": 0.002516}, "completion_tokens_details": {"reasoning_tokens": 581, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608276-DBhXkTD1ZraF8T7EwMBh", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-019", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "grouping", "stable-order"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve(['eat','tea','tan','ate','nat','bat']) == [['eat','tea','ate'], ['tan','nat'], ['bat']]", "assert solution.solve(['b','B','bb']) == [['b'], ['B'], ['bb']]"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(words: list[str]) -> list[list[str]]，按变位词分组。大小写敏感；组内保持输入顺序；组的顺序按该组第一个单词在输入中出现的位置。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "0a957bf71a0be6fa198a854347b2fe5d2c5d5f9b9a8bd5041dac9cdb46ae06ce", "started_at": "2026-06-16T11:11:28.238435+00:00", "latency_ms": 2538, "output": "```python\nfrom collections import defaultdict\n\ndef solve(words: list[str]) -> list[list[str]]:\n groups = defaultdict(list)\n for word in words:\n key = tuple(sorted(word))\n groups[key].append(word)\n return list(groups.values())\n```", "usage": {"prompt_tokens": 87, "completion_tokens": 244, "total_tokens": 331, "cost": 0.00105865, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00105865, "upstream_inference_prompt_cost": 8.265e-05, "upstream_inference_completions_cost": 0.000976}, "completion_tokens_details": {"reasoning_tokens": 189, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608290-Z7eaBB4CSFyN55UKygPW", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-020", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "parser", "front-matter"], "scorer": "code_python_tests", "expected": {"tests": ["text='---\\ntitle: Test\\ntags: [ai, bench, v0]\\ndraft: false\\n---\\nbody'\nassert solution.solve(text) == {'title':'Test','tags':['ai','bench','v0'],'draft':'false'}", "assert solution.solve('hello\\n---\\na: b') == {}", "assert solution.solve('---\\na: 1') == {}"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(text: str) -> dict，解析 Markdown front matter。只有第一行正好是 --- 时才解析，直到下一行 --- 结束；每行 key: value，key 和 value 两侧 trim；形如 [a, b] 的 value 返回字符串列表；其他 value 返回字符串。没有完整 front matter 返回 {}。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "4111f2228a7b621a743019a4cad1b5638c8a120765153c2d35f8db2aa136f79c", "started_at": "2026-06-16T11:11:30.814735+00:00", "latency_ms": 15221, "output": "```python\ndef solve(text: str) -> dict:\n lines = text.splitlines()\n if not lines or lines[0] != '---':\n return {}\n result = {}\n for i in range(1, len(lines)):\n line = lines[i]\n if line == '---':\n return result\n if ':' not in line:\n continue\n key, _, value = line.partition(':')\n key = key.strip()\n value = value.strip()\n if value.startswith('[') and value.endswith(']'):\n result[key] = [x.strip() for x in value[1:-1].split(',') if x.strip() != '']\n else:\n result[key] = value\n return {}\n```", "usage": {"prompt_tokens": 118, "completion_tokens": 926, "total_tokens": 1044, "cost": 0.0038161, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0038161, "upstream_inference_prompt_cost": 0.0001121, "upstream_inference_completions_cost": 0.003704}, "completion_tokens_details": {"reasoning_tokens": 872, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608293-n60Wt0LDZEM0vxJp6ACh", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-021", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "frequency", "stable-order"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve(['b','a','b','c','a','b'], 2) == ['b','a']", "assert solution.solve(['x','y','z','y','z','x'], 2) == ['x','y']", "assert solution.solve(['a'], 5) == ['a']"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(items: list[str], k: int) -> list[str]，返回出现次数最高的前 k 个元素；次数相同按第一次出现的先后排序；k 大于不同元素数量时返回全部。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "e73dccf0e991c296063c917fbe5a6b5f99f50fb3baed6d0820cfc35df858c663", "started_at": "2026-06-16T11:11:46.079017+00:00", "latency_ms": 4175, "output": " ```python\nfrom collections import Counter\n\ndef solve(items: list[str], k: int) -> list[str]:\n return [x for x, _ in Counter(items).most_common(k)]\n```", "usage": {"prompt_tokens": 89, "completion_tokens": 284, "total_tokens": 373, "cost": 0.00106075, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00106075, "upstream_inference_prompt_cost": 6.675e-05, "upstream_inference_completions_cost": 0.000994}, "completion_tokens_details": {"reasoning_tokens": 284, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608308-JMxZQa4tCSSCdkMoG8LT", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-022", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "nested-dict", "copy"], "scorer": "code_python_tests", "expected": {"tests": ["base={'db':{'host':'old','port':5432},'feature':{'x':1}}\noverrides={'db.host':'new','feature.x':None,'api.timeout':30}\nres=solution.solve(base, overrides)\nassert res == {'db':{'host':'new','port':5432},'feature':{},'api':{'timeout':30}}\nassert base == {'db':{'host':'old','port':5432},'feature':{'x':1}}", "assert solution.solve({'a':1}, {'a.b':2}) == {'a': {'b': 2}}"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(config: dict, overrides: dict[str, object]) -> dict。overrides 的 key 是点号路径；值为 None 表示删除该路径的叶子 key；其他值写入路径，必要时创建中间 dict；不能修改输入 config。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "e21e5bbf42159ba49144d39d17824dcf011df026efab7a9bfb6179aed2bb558a", "started_at": "2026-06-16T11:11:50.302690+00:00", "latency_ms": 8401, "output": " ```python\nimport copy\nfrom typing import Any, Dict\n\ndef solve(config: Dict[str, Any], overrides: Dict[str, Any]) -> Dict[str, Any]:\n result = copy.deepcopy(config)\n\n for path, value in overrides.items():\n parts = path.split(\".\")\n if not parts:\n continue\n\n current = result\n for part in parts[:-1]:\n if part not in current or not isinstance(current[part], dict):\n current[part] = {}\n current = current[part]\n\n leaf = parts[-1]\n if value is None:\n if isinstance(current, dict) and leaf in current:\n del current[leaf]\n else:\n current[leaf] = value\n\n return result\n```", "usage": {"prompt_tokens": 99, "completion_tokens": 385, "total_tokens": 484, "cost": 0.00142175, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00142175, "upstream_inference_prompt_cost": 7.425e-05, "upstream_inference_completions_cost": 0.0013475}, "completion_tokens_details": {"reasoning_tokens": 228, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608312-lyghe1GUsFiJXXwjFUI0", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-023", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "url", "parser"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve('a=1&b=two+words&a=3') == {'a':['1','3'], 'b':['two words']} ", "assert solution.solve('empty=&flag&x=a%2Bb') == {'empty':[''], 'flag':[''], 'x':['a+b']} ", "assert solution.solve('') == {}"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(query: str) -> dict[str, list[str]]，解析 URL query string。& 分隔参数；没有 = 的参数值为空字符串；+ 表示空格；%XX 需要按 UTF-8 百分号解码；同名 key 保留所有值的列表。可以使用标准库。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "cfe8be23444d346039a0740ab1568f54ed98bd44e5d63909779673da2207f393", "started_at": "2026-06-16T11:11:58.759994+00:00", "latency_ms": 9939, "output": " ```python\nfrom urllib.parse import unquote_plus\n\ndef solve(query: str) -> dict[str, list[str]]:\n result: dict[str, list[str]] = {}\n if not query:\n return result\n for part in query.split(\"&\"):\n if \"=\" in part:\n key, value = part.split(\"=\", 1)\n else:\n key, value = part, \"\"\n key = unquote_plus(key, encoding=\"utf-8\")\n value = unquote_plus(value, encoding=\"utf-8\")\n result.setdefault(key, []).append(value)\n return result\n```", "usage": {"prompt_tokens": 108, "completion_tokens": 555, "total_tokens": 663, "cost": 0.0023226, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0023226, "upstream_inference_prompt_cost": 0.0001026, "upstream_inference_completions_cost": 0.00222}, "completion_tokens_details": {"reasoning_tokens": 457, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608320-1DBM9Np7Ca76XozM9EhN", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-024", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "parser", "stack"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve('

x

') is True", "assert solution.solve('') is False", "assert solution.solve('text') is True"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(html: str) -> bool，校验简化 HTML 标签是否配对。标签形如 、、
，标签名只含小写字母；自闭合标签不入栈；普通文本忽略。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "088a9867c7f154cf1ee172830e13e8e49c53a8e572707d776f0cdea59f3555cb", "started_at": "2026-06-16T11:12:08.741589+00:00", "latency_ms": 5408, "output": "```python\nimport re\n\ndef solve(html: str) -> bool:\n stack = []\n for m in re.finditer(r'<(/?)([a-z]+)(/?)>', html):\n slash_open, name, slash_close = m.groups()\n if slash_close:\n continue\n if slash_open:\n if not stack or stack[-1] != name:\n return False\n stack.pop()\n else:\n stack.append(name)\n return not stack\n```", "usage": {"prompt_tokens": 95, "completion_tokens": 349, "total_tokens": 444, "cost": 0.00148625, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00148625, "upstream_inference_prompt_cost": 9.025e-05, "upstream_inference_completions_cost": 0.001396}, "completion_tokens_details": {"reasoning_tokens": 256, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608330-Q54RRazHi8DAaRJD7ItG", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-025", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "bfs", "grid"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve(['S..','##.','..E']) == 4", "assert solution.solve(['S#','##','E.']) == -1", "assert solution.solve(['SE']) == 1"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(grid: list[str]) -> int。grid 中 S 是起点，E 是终点，# 是墙，. 可走。每步上下左右移动一格，返回从 S 到 E 的最短步数；不可达返回 -1。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "8c6dc47fe32c2eef1e05bed2e6bd50520bb606e6965fe6c18e354a50a1e65085", "started_at": "2026-06-16T11:12:14.199757+00:00", "latency_ms": 30625, "output": "```python\nfrom collections import deque\n\ndef solve(grid: list[str]) -> int:\n if not grid:\n return -1\n n = len(grid)\n m = len(grid[0])\n sr = sc = er = ec = -1\n for i in range(n):\n for j, ch in enumerate(grid[i]):\n if ch == 'S':\n sr, sc = i, j\n elif ch == 'E':\n er, ec = i, j\n if sr == -1 or er == -1:\n return -1\n q = deque([(sr, sc, 0)])\n visited = {(sr, sc)}\n dirs = [(1, 0), (-1, 0), (0, 1), (0, -1)]\n while q:\n r, c, d = q.popleft()\n if r == er and c == ec:\n return d\n for dr, dc in dirs:\n nr, nc = r + dr, c + dc\n if 0 <= nr < n and 0 <= nc < m and (nr, nc) not in visited and grid[nr][nc] != '#':\n visited.add((nr, nc))\n q.append((nr, nc, d + 1))\n return -1\n```", "usage": {"prompt_tokens": 103, "completion_tokens": 726, "total_tokens": 829, "cost": 0.00300185, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00300185, "upstream_inference_prompt_cost": 9.785e-05, "upstream_inference_completions_cost": 0.002904}, "completion_tokens_details": {"reasoning_tokens": 446, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608336-GcWqzTSmlOUbh4beyM5K", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-026", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "sliding-window", "median"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve([1,3,-1,-3,5,3,6,7], 3) == [1, -1, -1, 3, 5, 6]", "assert solution.solve([1,2,3,4], 2) == [1.5, 2.5, 3.5]"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(nums: list[int], k: int) -> list[float]，返回每个长度为 k 的滑动窗口中位数。k 为奇数时返回中间值；k 为偶数时返回两个中间值平均数。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "53547e8e9f25c840b8a6248c7be329b1779ddc5a47484208f5c434403bd8228c", "started_at": "2026-06-16T11:12:45.042939+00:00", "latency_ms": 5236, "output": "```python\nimport bisect\n\ndef solve(nums: list[int], k: int) -> list[float]:\n if k <= 0 or k > len(nums):\n return []\n sl = []\n res = []\n for i, v in enumerate(nums):\n bisect.insort(sl, v)\n if i >= k:\n out = nums[i - k]\n idx = bisect.bisect_left(sl, out)\n sl.pop(idx)\n if i >= k - 1:\n if k % 2 == 1:\n res.append(float(sl[k // 2]))\n else:\n res.append((sl[k // 2 - 1] + sl[k // 2]) / 2.0)\n return res\n```", "usage": {"prompt_tokens": 93, "completion_tokens": 346, "total_tokens": 439, "cost": 0.00147235, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00147235, "upstream_inference_prompt_cost": 8.835e-05, "upstream_inference_completions_cost": 0.001384}, "completion_tokens_details": {"reasoning_tokens": 197, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608367-Zeu04YfGkalxenCgG1KX", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-027", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "sorting", "semver"], "scorer": "code_python_tests", "expected": {"tests": ["assert solution.solve(['1.0.0','1.0.0-alpha','1.0.1','1.0.0-beta','0.9.9']) == ['0.9.9','1.0.0-alpha','1.0.0-beta','1.0.0','1.0.1']", "assert solution.solve(['1.0.10','1.0.2']) == ['1.0.2','1.0.10']"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(versions: list[str]) -> list[str]，按简化语义版本排序。版本为 major.minor.patch 或 major.minor.patch-label；major/minor/patch 按数字比较；同一数字版本下，带 label 的预发布版本低于正式版本；label 按字典序比较。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "f9b7324425840beb574b30433a6e004d34a834ef548c9cfa579b9b9b6950377d", "started_at": "2026-06-16T11:12:50.324006+00:00", "latency_ms": 17279, "output": " ```python\ndef solve(versions: list[str]) -> list[str]:\n def key(v: str):\n num, _, label = v.partition('-')\n major, minor, patch = num.split('.')\n return (int(major), int(minor), int(patch), 0 if label else 1, label)\n return sorted(versions, key=key)\n```", "usage": {"prompt_tokens": 109, "completion_tokens": 414, "total_tokens": 523, "cost": 0.00153075, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00153075, "upstream_inference_prompt_cost": 8.175e-05, "upstream_inference_completions_cost": 0.001449}, "completion_tokens_details": {"reasoning_tokens": 335, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608372-iGq1HWgcvPcMp9twI99F", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-coding-028", "suite": "coding", "case_version": "0.3.0", "tags": ["python", "graph", "reverse-deps"], "scorer": "code_python_tests", "expected": {"tests": ["deps={'app':['lib','ui'],'ui':['core'],'lib':['core'],'core':[],'docs':[]}\nassert solution.solve(deps, ['core']) == ['app','core','lib','ui']", "assert solution.solve({'a':['x']}, ['x']) == ['a','x']", "assert solution.solve({'a':['b'], 'b':[]}, ['a']) == ['a']"], "timeout_seconds": 3}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只输出 Python 代码，不要解释。实现 solve(deps: dict[str, list[str]], changed: list[str]) -> list[str]。deps 表示 package -> 直接依赖。返回所有 changed 包，以及直接或间接依赖 changed 包的包，按字典序排序；只出现在依赖列表中的包也要能作为 changed 包返回。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "2a0e51751556bc0e35f2a2a2aa4ed86810eacfc274bb9c5f48e8990611a9a473", "started_at": "2026-06-16T11:13:07.646113+00:00", "latency_ms": 23442, "output": "```python\ndef solve(deps: dict[str, list[str]], changed: list[str]) -> list[str]:\n reverse = {}\n for pkg, dep_list in deps.items():\n for dep in dep_list:\n reverse.setdefault(dep, []).append(pkg)\n\n stack = list(changed)\n result = set(changed)\n\n while stack:\n cur = stack.pop()\n for parent in reverse.get(cur, []):\n if parent not in result:\n result.add(parent)\n stack.append(parent)\n\n return sorted(result)\n```", "usage": {"prompt_tokens": 107, "completion_tokens": 1163, "total_tokens": 1270, "cost": 0.00475365, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00475365, "upstream_inference_prompt_cost": 0.00010165, "upstream_inference_completions_cost": 0.004652}, "completion_tokens_details": {"reasoning_tokens": 1309, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608389-LGlequIN4A9hlBW0yaFw", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"returncode": 0, "stdout": "", "stderr": ""}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-008", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "conflict", "workflow"], "scorer": "text_rules", "expected": {"required": ["50", "审题"], "required_any": [["不跑", "不要立刻", "先不跑", "不应立刻", "不应该立刻", "不应立即", "不应该立即", "不应立刻跑", "不应该立刻跑", "不应立即跑", "不应该立即跑"]], "forbidden": [], "max_chars": 160}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只根据资料回答。\n\n资料 A：早期草案说 v0.3 只新增 20 道题。\n资料 B：2026-06-16 的确认方案是 v0.3-challenge100，在现有 50 题基础上新增 50 道题。\n资料 C：新增题应先生成审题 HTML，确认后再跑模型，不要立即消耗 API。\n\n问题：下一步应该新增多少题？是否应该立刻跑模型？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "c99da78812f6f4ab7745f793b9e3dc087033b0cce0591db49bf8642829324a81", "started_at": "2026-06-16T11:13:31.132588+00:00", "latency_ms": 3079, "output": " 根据资料 B，下一步应新增 **50 道题**（v0.3-challenge100，在现有 50 题基础上新增 50 题）。\n\n根据资料 C，**不应该立刻跑模型**。新增题应先生成审题 HTML，确认后再跑模型，避免立即消耗 API。", "usage": {"prompt_tokens": 129, "completion_tokens": 210, "total_tokens": 339, "cost": 0.00083175, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00083175, "upstream_inference_prompt_cost": 9.675e-05, "upstream_inference_completions_cost": 0.000735}, "completion_tokens_details": {"reasoning_tokens": 153, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608413-xcK6rRUe0xZ4qBDqk4wn", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 118, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-009", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "abstain"], "scorer": "text_rules", "expected": {"required": ["不能", "用户满意度"], "required_any": [["没有包含", "没有提供", "资料没有", "未包含"]], "forbidden": ["可以判断"], "max_chars": 120}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只根据资料回答，不要自行补充。\n\n资料：报告展示 pass_rate、avg_latency_ms、total_cost、reasoning_tokens、失败样例和逐题明细。资料没有包含用户满意度调查，也没有包含模型训练数据来源。\n\n问题：能否根据这份报告判断用户满意度？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "c072287ee5dbe1d477ab21e37485fb72f07cd11a57b57f199f071287443f404e", "started_at": "2026-06-16T11:13:34.221456+00:00", "latency_ms": 9231, "output": "不能。这份报告没有包含用户满意度调查或相关反馈数据，无法据此判断用户满意度。", "usage": {"prompt_tokens": 95, "completion_tokens": 113, "total_tokens": 208, "cost": 0.00054225, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00054225, "upstream_inference_prompt_cost": 9.025e-05, "upstream_inference_completions_cost": 0.000452}, "completion_tokens_details": {"reasoning_tokens": 92, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608416-kup4pEvriYcMM1IX4WnE", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 38, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-010", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "tradeoff"], "scorer": "text_rules", "expected": {"required": ["B", "延迟"], "required_any": [["没有超时", "无超时"]], "forbidden": ["选择 A", "选择 C"], "max_chars": 160}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只根据资料回答。\n\n资料：模型 A 通过 48/50，平均延迟 20 秒，成本 0.20 美元，没有超时失败。模型 B 通过 44/50，平均延迟 4 秒，成本 0.05 美元，没有超时失败。模型 C 通过 46/50，平均延迟 9 秒，成本 0.04 美元，但有 3 次 API 超时。\n\n问题：如果要选低延迟且稳定的生产摘要模型，资料更支持选择哪个？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "a17bb8c56d524481eedc45557a1394b5b65b034af6847928cca16e2c8c2428c9", "started_at": "2026-06-16T11:13:43.463487+00:00", "latency_ms": 6277, "output": " 资料更支持选择 **模型 B**。\n\n理由： \n- **低延迟**：模型 B 平均延迟仅 **4 秒**，远低于 A（20 秒）和 C（9 秒）。 \n- **稳定**：模型 B **没有超时失败**，而模型 C 有 3 次 API 超时；模型 A 虽也无超时，但延迟过高。 \n\n虽然模型 B 的通过率（44/50）略低于 A（48/50）和 C（46/50），但在“低延迟且稳定”这两个核心要求上，B 表现最佳。", "usage": {"prompt_tokens": 151, "completion_tokens": 452, "total_tokens": 603, "cost": 0.00169525, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00169525, "upstream_inference_prompt_cost": 0.00011325, "upstream_inference_completions_cost": 0.001582}, "completion_tokens_details": {"reasoning_tokens": 328, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608425-Y1SzGSiQiuvWmE17oSY8", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 209, "length_ok": false, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-011", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "scoring-policy"], "scorer": "text_rules", "expected": {"required": ["诊断"], "required_any": [["不扣分", "不会", "不会因长度", "不会因此被扣分", "不会直接导致扣分", "不会导致扣分", "不会导致失败或扣分"], ["length_scored", "长度"]], "forbidden": ["直接失败", "必须重跑"], "max_chars": 140}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只根据资料回答。\n\n资料：DracoBench 当前 scoring policy 中，text_rules 的 max_chars/min_chars 只作为诊断信息记录，length_scored 为 false。缺少 required、required_any 或出现 forbidden 才会导致失败。\n\n问题：如果答案超过 max_chars，但 required 都满足且没有 forbidden，会因为长度直接扣分吗？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "1ff7f897fc3d3121f25358f9a8df2a2df2970bc5762ff1218dd63c3f42d7d598", "started_at": "2026-06-16T11:13:49.756906+00:00", "latency_ms": 2791, "output": "不会。长度只作为诊断信息记录，length_scored 为 false，因此仅超过 max_chars 不会导致失败或扣分。", "usage": {"prompt_tokens": 113, "completion_tokens": 116, "total_tokens": 229, "cost": 0.00057135, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00057135, "upstream_inference_prompt_cost": 0.00010735, "upstream_inference_completions_cost": 0.000464}, "completion_tokens_details": {"reasoning_tokens": 107, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608432-Rxdc1FGTGc4fFroEkDmt", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 63, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-012", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "rescoring"], "scorer": "text_rules", "expected": {"required": ["46/50"], "forbidden": ["45/50 更合适", "原始结果为准"], "max_chars": 140}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只根据资料回答。\n\n资料 A：某模型原始结果为 45/50。\n资料 B：修正一个同义表达评分规则后，rescored 结果为 46/50。\n资料 C：总览 index 使用 rescored JSONL 作为展示结果。\n\n问题：写文章引用总览结果时，应写 45/50 还是 46/50？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "274c0483d9fd5cae178e795e16add941178c14f5ae34a82f631655c000ff929a", "started_at": "2026-06-16T11:13:52.561011+00:00", "latency_ms": 2041, "output": " 应写 **46/50**。因为总览 index 使用 rescored JSONL 作为展示结果。", "usage": {"prompt_tokens": 114, "completion_tokens": 123, "total_tokens": 237, "cost": 0.000516, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.000516, "upstream_inference_prompt_cost": 8.55e-05, "upstream_inference_completions_cost": 0.0004305}, "completion_tokens_details": {"reasoning_tokens": 99, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608434-eCzwsrAAOuukukH1bwSU", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 49, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-013", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "reproducibility"], "scorer": "text_rules", "expected": {"required": ["model", "prompt_hash", "parameters", "scorer"], "forbidden": ["chain of thought", "训练数据"], "max_chars": 200}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只根据资料回答。\n\n资料：为了复现一次 benchmark，记录中包含 model、case_id、prompt_hash、parameters、scorer details、output、latency_ms 和 usage。记录不包含 chain of thought，也不包含训练数据。\n\n问题：复现评测主要应该依赖哪些记录字段？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "7455c8e21abbb53f7cb11c9db29ed66ad1dfcc7e60138f6dfccb7cbcacc958c3", "started_at": "2026-06-16T11:13:54.610820+00:00", "latency_ms": 3371, "output": "复现评测主要应依赖这些记录字段：**model、case_id、prompt_hash、parameters、scorer details、output、latency_ms、usage**。", "usage": {"prompt_tokens": 97, "completion_tokens": 136, "total_tokens": 233, "cost": 0.00063615, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00063615, "upstream_inference_prompt_cost": 9.215e-05, "upstream_inference_completions_cost": 0.000544}, "completion_tokens_details": {"reasoning_tokens": 125, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608436-f4V07150Fdwd46dpDqrP", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 96, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-014", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "mode"], "scorer": "text_rules", "expected": {"required": ["16384"], "forbidden": ["4096"], "max_chars": 100}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只根据资料回答。\n\n资料 A：早期 ability mode 使用 4096 max_tokens。\n资料 B：后来为了公平，ability mode 统一放宽到 16384 max_tokens。\n资料 C：当前总览页只展示 v0.2-challenge50 且 ability16384 的结果。\n\n问题：当前总览页对应的 token limit 是多少？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "1d5b45892f4d0509e7805976e9bb60b3893e68657b40fcfa934db89a27eccc7b", "started_at": "2026-06-16T11:13:57.994739+00:00", "latency_ms": 1636, "output": " 当前总览页对应的 token limit 是 **16384**。\n\n依据资料 C：当前总览页只展示 “ability16384” 的结果。", "usage": {"prompt_tokens": 111, "completion_tokens": 88, "total_tokens": 199, "cost": 0.00039125, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00039125, "upstream_inference_prompt_cost": 8.325e-05, "upstream_inference_completions_cost": 0.000308}, "completion_tokens_details": {"reasoning_tokens": 62, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608440-fniWO6eG59omdY6waHpc", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 70, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-015", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "failure-analysis", "scoring-policy"], "scorer": "text_rules", "expected": {"required": ["人工复查", "coding-004"], "required_any": [["rag-006", "规则", "评分规则", "同义表达"], ["不属于", "不是", "不需要"]], "max_chars": 180}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只根据资料回答。\n\n资料：coding-004 的失败是代码运行时 ValueError，根因是把字符串 key 强转 int。rag-006 的失败曾经是规则没有把 int 类型视作“整数”的同义表达，后来通过人工复查修正规则。\n\n问题：哪类失败更需要人工复查评分规则？回答时也说明 coding-004 是否属于这种情况。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "d4725ef21042620eab8231d5671ac8f778c2b71f85afb72d592c3da2278cc9c4", "started_at": "2026-06-16T11:13:59.643083+00:00", "latency_ms": 3530, "output": " 更需要人工复查评分规则的是 **因评分规则本身不完善导致的失败**（例如规则未覆盖同义表达、类型表述等语义等价情况）。\n\n`coding-004` **不属于**这种情况。它的失败是代码运行时的 `ValueError`，根因是代码实现中把字符串 key 强制转为 int，属于代码/实现错误，而不是评分规则的问题。", "usage": {"prompt_tokens": 113, "completion_tokens": 265, "total_tokens": 378, "cost": 0.00101225, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00101225, "upstream_inference_prompt_cost": 8.475e-05, "upstream_inference_completions_cost": 0.0009275}, "completion_tokens_details": {"reasoning_tokens": 232, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608441-UdJZdUN75HtIvQaDcDGr", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 158, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-016", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "abstain", "cost"], "scorer": "text_rules", "expected": {"required": ["不能", "利润率"], "required_any": [["不包含", "没有"]], "forbidden": ["可以判断"], "max_chars": 120}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只根据资料回答。\n\n资料：usage 字段包含 prompt_tokens、completion_tokens、reasoning_tokens 和 cost。报告没有供应商真实利润率，也没有供应商内部成本。\n\n问题：能否从 usage 字段判断供应商利润率？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "622c02bde50c8b232afe7bb574da76e2ed1e35d49a55a96f63b935dbbbb16175", "started_at": "2026-06-16T11:14:03.185977+00:00", "latency_ms": 2535, "output": " 不能。usage 字段只包含 token 数量和 cost，但资料中说明没有供应商的真实利润率和内部成本。利润率需要知道成本与收入/利润的关系，仅凭 usage 字段无法判断。", "usage": {"prompt_tokens": 83, "completion_tokens": 144, "total_tokens": 227, "cost": 0.00056625, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00056625, "upstream_inference_prompt_cost": 6.225e-05, "upstream_inference_completions_cost": 0.000504}, "completion_tokens_details": {"reasoning_tokens": 131, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608445-xtqMdPZ7vpQXC8fq1IIJ", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 88, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-017", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "index-scope"], "scorer": "text_rules", "expected": {"required": ["v0.2-challenge50", "ability16384"], "required_any": [["不应该", "不展示", "未展示", "不显示", "均不显示", "不应展示"], ["旧版本", "之前的版本"]], "max_chars": 160}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只根据资料回答。\n\n资料：当前 index 页只显示最后这版 50 道题的 v0.2-challenge50 结果，并且 token limit 都统一为 ability16384。之前的版本和 ability4096 结果不显示在 index 页。\n\n问题：index 页是否应该展示旧版本结果？当前展示范围是什么？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "84234aeba9875f705a8daae80d0f0a287d1cef74de57877dfe6fbd41e6d1e835", "started_at": "2026-06-16T11:14:05.731489+00:00", "latency_ms": 3428, "output": "根据资料：\n\n- **index 页不应该展示旧版本结果**。 \n- **当前展示范围**：只显示最后这版 50 道题的 **v0.2-challenge50** 结果，并且 token limit 统一为 **ability16384**。之前的版本和 ability4096 结果不显示。", "usage": {"prompt_tokens": 109, "completion_tokens": 185, "total_tokens": 294, "cost": 0.00084355, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00084355, "upstream_inference_prompt_cost": 0.00010355, "upstream_inference_completions_cost": 0.00074}, "completion_tokens_details": {"reasoning_tokens": 144, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608447-wwKg825key8KlQ5lFbJu", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 147, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-rag-018", "suite": "rag_long_context", "case_version": "0.3.0", "tags": ["rag", "failure-analysis", "truncation"], "scorer": "text_rules", "expected": {"required": ["输出"], "required_any": [["截断", "length", "token"]], "forbidden": [], "max_chars": 140}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "只根据资料回答。\n\n资料：某 coding 题中，模型响应的 finish_reason 为 length，output 为空，测试报错为 module has no attribute solve。报告认为这不是算法逻辑错误，而是输出被截断后没有形成可执行函数。\n\n问题：这次失败应如何归因？", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "f819b3ec516c1c77e6e0c1bbcece217d77fc5a4aaee6e7787be0b4cd5d97c9ff", "started_at": "2026-06-16T11:14:09.173273+00:00", "latency_ms": 3386, "output": " 应归因于**输出截断（length 限制）**，即模型生成被截断，未能输出完整的可执行 `solve` 函数，而不是算法逻辑错误。", "usage": {"prompt_tokens": 99, "completion_tokens": 155, "total_tokens": 254, "cost": 0.00061675, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00061675, "upstream_inference_prompt_cost": 7.425e-05, "upstream_inference_completions_cost": 0.0005425}, "completion_tokens_details": {"reasoning_tokens": 117, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608451-wEFpXwiW5A0fCwg0WkZl", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], "char_count": 65, "length_ok": true, "length_scored": false}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-015", "suite": "debugging", "case_version": "0.3.0", "tags": ["python", "closure", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*funcs\\.append\\(lambda\\s+i=i\\s*:\\s*i\\)\\s*`?", "flags": "is"}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "下面代码期望 funcs[0]()、funcs[1]()、funcs[2]() 分别返回 0、1、2，但实际都会返回 2。请指出根因，并给出最小修复。最后单独一行写 FIX: <修复后的 append 行>。\n\n```python\nfuncs = []\nfor i in range(3):\n funcs.append(lambda: i)\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "e90d1ddfafd6f041b7be435f823b34b7ad74ddf85bb4dbb228db8e1183cd8843", "started_at": "2026-06-16T11:14:12.572296+00:00", "latency_ms": 13328, "output": "根因：Python 的闭包按**变量名**捕获，而不是按值。循环结束后 `i` 的值为 2，所以所有 lambda 执行时读取到的都是同一个 `i` 的最终值。\n\n最小修复：利用默认参数在定义时求值的特性，把当前 `i` 绑定到 lambda 的参数默认值上。\n\nFIX: `funcs.append(lambda i=i: i)`", "usage": {"prompt_tokens": 117, "completion_tokens": 241, "total_tokens": 358, "cost": 0.00107515, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00107515, "upstream_inference_prompt_cost": 0.00011115, "upstream_inference_completions_cost": 0.000964}, "completion_tokens_details": {"reasoning_tokens": 155, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608454-JibbrRhD0gKiPUHXEgua", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*funcs\\.append\\(lambda\\s+i=i\\s*:\\s*i\\)\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-016", "suite": "debugging", "case_version": "0.3.0", "tags": ["python", "context-manager", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*return(?:\\s+False|\\s+None)?\\s*`?", "flags": "is"}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "下面 context manager 期望异常继续向外抛出，但实际异常被吞掉。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 return 行>。\n\n```python\nclass Span:\n def __enter__(self):\n return self\n def __exit__(self, exc_type, exc, tb):\n return True\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "e7cbf0d9b2df76954e4b3aacf7d21f0a22c40f64ccc2432b115896cdb5a3f123", "started_at": "2026-06-16T11:14:25.913416+00:00", "latency_ms": 3204, "output": " Bug：`__exit__` 返回 `True` 会告诉 Python 吞掉上下文内抛出的异常；要让它继续向外抛出，应返回 `False`（或 `None`）。\n\nFIX: return False", "usage": {"prompt_tokens": 112, "completion_tokens": 169, "total_tokens": 281, "cost": 0.00065662, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 32, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00065662, "upstream_inference_prompt_cost": 6.512e-05, "upstream_inference_completions_cost": 0.0005915}, "completion_tokens_details": {"reasoning_tokens": 122, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608468-CsnHbUJHjBHd6bjDMSlv", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*return(?:\\s+False|\\s+None)?\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-017", "suite": "debugging", "case_version": "0.3.0", "tags": ["python", "class-variable", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*self\\.items\\s*=\\s*\\[\\]\\s*`?", "flags": "is"}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "下面代码期望每个 Bag 实例都有独立列表，但不同实例会共享 items。请指出 bug，并给出最小修复。最后单独一行写 FIX: <新增到 __init__ 中的赋值行>。\n\n```python\nclass Bag:\n items = []\n def add(self, x):\n self.items.append(x)\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "c2b320a4b54c57505deb9a6f14ebb63217e6c351a61dbfeed24131e848fe7553", "started_at": "2026-06-16T11:14:29.129201+00:00", "latency_ms": 6025, "output": "bug：`items = []` 是类属性，只创建一次，所有 `Bag` 实例共享同一个列表。`self.items.append` 因为没有给实例赋值，实际访问的是这个类属性。\n\n最小修复：在 `__init__` 中为每个实例创建独立列表。\n\n```python\nclass Bag:\n def __init__(self):\n self.items = []\n def add(self, x):\n self.items.append(x)\n```\n\nFIX: self.items = []", "usage": {"prompt_tokens": 106, "completion_tokens": 496, "total_tokens": 602, "cost": 0.0020847, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0020847, "upstream_inference_prompt_cost": 0.0001007, "upstream_inference_completions_cost": 0.001984}, "completion_tokens_details": {"reasoning_tokens": 396, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608471-QqMGX9AR7CsfaQp94gOT", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*self\\.items\\s*=\\s*\\[\\]\\s*`?"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-018", "suite": "debugging", "case_version": "0.3.0", "tags": ["python", "default-argument", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*def\\s+mark\\(ts=None\\)\\s*:", "flags": "is"}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "下面代码期望每次不传 ts 时使用当前时间，但默认时间只会在函数定义时计算一次。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的函数定义行>。\n\n```python\nfrom datetime import datetime\n\ndef mark(ts=datetime.utcnow()):\n return ts.isoformat()\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "96674f1c8091e56110c21b7b057178e05bd5225812543e3101e86fc6c5d2dba7", "started_at": "2026-06-16T11:14:35.165677+00:00", "latency_ms": 7233, "output": "bug：`datetime.utcnow()` 作为默认参数只在函数定义时求值一次，所以之后每次不传 `ts` 都会返回同一个时间。\n\n最小修复：把默认值改为 `None`，在函数内部再计算当前时间。\n\nFIX: `def mark(ts=None): return (datetime.utcnow() if ts is None else ts).isoformat()`", "usage": {"prompt_tokens": 105, "completion_tokens": 500, "total_tokens": 605, "cost": 0.00209975, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00209975, "upstream_inference_prompt_cost": 9.975e-05, "upstream_inference_completions_cost": 0.002}, "completion_tokens_details": {"reasoning_tokens": 537, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608477-uLjwS5j3A2UosUyhTXhy", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": "FIX:\\s*`?\\s*def\\s+mark\\(ts=None\\)\\s*:"}}, "error": null, "rescored_from": "/Users/dracohu/REPO/dracobench/runs/v0.3-challenge100-moonshotai-kimi-k2-7-code-ability16384.jsonl", "scoring_policy": "text_rules_length_diagnostic_only+v03_alias_relaxations_round2"} {"case_id": "challenge-debugging-019", "suite": "debugging", "case_version": "0.3.0", "tags": ["python", "method-call", "debugging"], "scorer": "regex", "expected": {"pattern": "FIX:\\s*`?\\s*return\\s+s\\.strip\\(\\)\\.lower\\(\\)\\s*`?", "flags": "is"}, "model": "moonshotai/kimi-k2.7-code", "provider": null, "prompt": "下面代码期望返回小写字符串，但实际返回的是方法对象。请指出 bug，并给出最小修复。最后单独一行写 FIX: <修复后的 return 行>。\n\n```python\ndef normalize(s):\n return s.strip().lower\n```", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "e9d483dafd7852b396cee6b27c6c25c888983460dba83c871f7f9a239dd601ef", "started_at": "2026-06-16T11:14:42.415137+00:00", "latency_ms": 1512, "output": "bug：`s.strip().lower` 后面缺少括号，返回的是 `lower` 方法对象本身，而不是调用后的结果。\n\n最小修复：在 `lower` 后加 `()` 以调用方法。\n\nFIX: `return s.strip().lower()`", "usage": {"prompt_tokens": 89, "completion_tokens": 180, "total_tokens": 269, "cost": 0.00080455, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00080455, "upstream_inference_prompt_cost": 8.455e-05, "upstream_inference_completions_cost": 0.00072}, "completion_tokens_details": {"reasoning_tokens": 125, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608484-BdWUH08n7nhyUTsRtI4d", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"pattern": 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"provider": null, "prompt": "只输出 JSON 对象，不要 Markdown。字段 version 必须是 \"v0.3\"；字段 ready 必须是 true；字段 cases 必须是正好两个对象组成的数组。cases 中每个对象只能包含 id、weight、active 三个字段；id 是字符串且匹配 case-1 或 case-2；weight 是整数；active 是布尔值。", "parameters": {"temperature": 0, "max_tokens": 16384, "seed": null}, "prompt_hash": "7aa2b7b97ec6a230b8e08a0949edc3f573a3979a488949456e1106dcbad11695", "started_at": "2026-06-16T11:14:43.940351+00:00", "latency_ms": 3124, "output": "{\"version\": \"v0.3\", \"ready\": true, \"cases\": [{\"id\": \"case-1\", \"weight\": 1, \"active\": true}, {\"id\": \"case-2\", \"weight\": 1, \"active\": true}]}", "usage": {"prompt_tokens": 114, "completion_tokens": 220, "total_tokens": 334, "cost": 0.0009883, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.0009883, "upstream_inference_prompt_cost": 0.0001083, "upstream_inference_completions_cost": 0.00088}, 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"parameters": {"temperature": 0.2, "max_tokens": 16384, "seed": null}, "prompt_hash": "2e406239f22e7454c39c9cc970d8388b92c83522c1edacf056286806f5933790", "started_at": "2026-06-16T11:14:47.074385+00:00", "latency_ms": 9045, "output": "为什么 v0.3 要扩到 100 题？因为推理题需要覆盖更多边界条件，才能全面检验模型能力。题量翻倍后，我们逐题进行人工复查，确保答案与标注准确可靠。样本更充分，结论也更稳健。", "usage": {"prompt_tokens": 81, "completion_tokens": 868, "total_tokens": 949, "cost": 0.00354895, "is_byok": false, "prompt_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0, "audio_tokens": 0, "video_tokens": 0}, "cost_details": {"upstream_inference_cost": 0.00354895, "upstream_inference_prompt_cost": 7.695e-05, "upstream_inference_completions_cost": 0.003472}, "completion_tokens_details": {"reasoning_tokens": 810, "image_tokens": 0, "audio_tokens": 0}}, "response_id": "gen-1781608489-Arko5ZGnB5QkAjolBINE", "finish_reason": "stop", "score": {"passed": true, "score": 1.0, "details": {"missing": [], "missing_any": [], "present_forbidden": [], 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