172 lines
199 KiB
JSON
172 lines
199 KiB
JSON
{"text": "Write a Python function `merge_intervals(intervals)` where intervals is\na list of [start, end] lists. Merge all overlapping intervals and return\na new list of [start, end] lists sorted by start. Intervals that merely\ntouch (one ends exactly where the next begins) must be merged. Input may\nbe unsorted and may contain intervals fully nested inside others.\nReply with ONLY the function definition — no explanation, no fences.\n", "category": "coding_general", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nWrite a Python function `merge_intervals(intervals)` where intervals is\na list of [start, end] lists. Merge all overlapping intervals and return\na new list of [start, end] lists sorted by start. Intervals that merely\ntouch (one ends exactly where the next begins) must be merged. Input may\nbe unsorted and may contain intervals fully nested inside others.\nReply with ONLY the function definition — no explanation, no fences.\n", "category": "coding_general", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nWrite a Python function `merge_intervals(intervals)` where intervals is\na list of [start, end] lists. Merge all overlapping intervals and return\na new list of [start, end] lists sorted by start. Intervals that merely\ntouch (one ends exactly where the next begins) must be merged. Input may\nbe unsorted and may contain intervals fully nested inside others.\nReply with ONLY the function definition — no explanation, no fences.\n", "category": "coding_general", "noise_level": "long"}
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{"text": "Write a Python function `parse_semver(version)` that parses a semantic\nversion string into a dict with keys: major, minor, patch (ints), and\nprerelease, build (strings, or None when absent). Valid examples:\n\"1.2.3\", \"1.2.3-alpha.1\", \"1.2.3+build.5\", \"1.2.3-rc.1+exp.sha.5114f85\".\nRaise ValueError if the string is not a valid semantic version, for\nexample \"1.2\" or \"1.2.x\".\nReply with ONLY the function definition — no explanation, no fences.\n", "category": "coding_general", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nWrite a Python function `parse_semver(version)` that parses a semantic\nversion string into a dict with keys: major, minor, patch (ints), and\nprerelease, build (strings, or None when absent). Valid examples:\n\"1.2.3\", \"1.2.3-alpha.1\", \"1.2.3+build.5\", \"1.2.3-rc.1+exp.sha.5114f85\".\nRaise ValueError if the string is not a valid semantic version, for\nexample \"1.2\" or \"1.2.x\".\nReply with ONLY the function definition — no explanation, no fences.\n", "category": "coding_general", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nWrite a Python function `parse_semver(version)` that parses a semantic\nversion string into a dict with keys: major, minor, patch (ints), and\nprerelease, build (strings, or None when absent). Valid examples:\n\"1.2.3\", \"1.2.3-alpha.1\", \"1.2.3+build.5\", \"1.2.3-rc.1+exp.sha.5114f85\".\nRaise ValueError if the string is not a valid semantic version, for\nexample \"1.2\" or \"1.2.x\".\nReply with ONLY the function definition — no explanation, no fences.\n", "category": "coding_general", "noise_level": "long"}
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{"text": "Write a Python function `word_wrap(text, width)` returning a list of\nlines. Split on whitespace and pack as many words per line as fit within\n`width` characters, joining words with a single space. Never split a\nword: a word longer than `width` gets its own line. Runs of whitespace\ncollapse. Empty or whitespace-only text returns an empty list.\nReply with ONLY the function definition — no explanation, no fences.\n", "category": "coding_general", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nWrite a Python function `word_wrap(text, width)` returning a list of\nlines. Split on whitespace and pack as many words per line as fit within\n`width` characters, joining words with a single space. Never split a\nword: a word longer than `width` gets its own line. Runs of whitespace\ncollapse. Empty or whitespace-only text returns an empty list.\nReply with ONLY the function definition — no explanation, no fences.\n", "category": "coding_general", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nWrite a Python function `word_wrap(text, width)` returning a list of\nlines. Split on whitespace and pack as many words per line as fit within\n`width` characters, joining words with a single space. Never split a\nword: a word longer than `width` gets its own line. Runs of whitespace\ncollapse. Empty or whitespace-only text returns an empty list.\nReply with ONLY the function definition — no explanation, no fences.\n", "category": "coding_general", "noise_level": "long"}
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{"text": "What does this function return when called as shown? Reply with ONLY\nthe literal Python value — strings in quotes (for example: 42, [1, 2],\n'text', None), no explanation, no fences.\n\ndef f(t):\n for c in t:\n if not c.isnumeric():\n return False\n return True\n\nf('#284376598')\n", "category": "coding_general", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nWhat does this function return when called as shown? Reply with ONLY\nthe literal Python value — strings in quotes (for example: 42, [1, 2],\n'text', None), no explanation, no fences.\n\ndef f(t):\n for c in t:\n if not c.isnumeric():\n return False\n return True\n\nf('#284376598')\n", "category": "coding_general", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nWhat does this function return when called as shown? Reply with ONLY\nthe literal Python value — strings in quotes (for example: 42, [1, 2],\n'text', None), no explanation, no fences.\n\ndef f(t):\n for c in t:\n if not c.isnumeric():\n return False\n return True\n\nf('#284376598')\n", "category": "coding_general", "noise_level": "long"}
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{"text": "What does this function return when called as shown? Reply with ONLY\nthe literal Python value — strings in quotes (for example: 42, [1, 2],\n'text', None), no explanation, no fences.\n\ndef f(nums):\n output = []\n for n in nums:\n output.append((nums.count(n), n))\n output.sort(reverse=True)\n return output\n\nf([1, 1, 3, 1, 3, 1])\n", "category": "coding_general", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nWhat does this function return when called as shown? Reply with ONLY\nthe literal Python value — strings in quotes (for example: 42, [1, 2],\n'text', None), no explanation, no fences.\n\ndef f(nums):\n output = []\n for n in nums:\n output.append((nums.count(n), n))\n output.sort(reverse=True)\n return output\n\nf([1, 1, 3, 1, 3, 1])\n", "category": "coding_general", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nWhat does this function return when called as shown? Reply with ONLY\nthe literal Python value — strings in quotes (for example: 42, [1, 2],\n'text', None), no explanation, no fences.\n\ndef f(nums):\n output = []\n for n in nums:\n output.append((nums.count(n), n))\n output.sort(reverse=True)\n return output\n\nf([1, 1, 3, 1, 3, 1])\n", "category": "coding_general", "noise_level": "long"}
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{"text": "What does this function return when called as shown? Reply with ONLY\nthe literal Python value — strings in quotes (for example: 42, [1, 2],\n'text', None), no explanation, no fences.\n\ndef f(a, b, c):\n result = {}\n for d in a, b, c:\n result.update(dict.fromkeys(d))\n return result\n\nf((1, ), (1, ), (1, 2))\n", "category": "coding_general", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nWhat does this function return when called as shown? Reply with ONLY\nthe literal Python value — strings in quotes (for example: 42, [1, 2],\n'text', None), no explanation, no fences.\n\ndef f(a, b, c):\n result = {}\n for d in a, b, c:\n result.update(dict.fromkeys(d))\n return result\n\nf((1, ), (1, ), (1, 2))\n", "category": "coding_general", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nWhat does this function return when called as shown? Reply with ONLY\nthe literal Python value — strings in quotes (for example: 42, [1, 2],\n'text', None), no explanation, no fences.\n\ndef f(a, b, c):\n result = {}\n for d in a, b, c:\n result.update(dict.fromkeys(d))\n return result\n\nf((1, ), (1, ), (1, 2))\n", "category": "coding_general", "noise_level": "long"}
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{"text": "What does this function return when called as shown? Reply with ONLY\nthe literal Python value — strings in quotes (for example: 42, [1, 2],\n'text', None), no explanation, no fences.\n\ndef f(text):\n new_text = list(text)\n for i in '+':\n if i in new_text:\n new_text.remove(i)\n return ''.join(new_text)\n\nf('hbtofdeiequ')\n", "category": "coding_general", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nWhat does this function return when called as shown? Reply with ONLY\nthe literal Python value — strings in quotes (for example: 42, [1, 2],\n'text', None), no explanation, no fences.\n\ndef f(text):\n new_text = list(text)\n for i in '+':\n if i in new_text:\n new_text.remove(i)\n return ''.join(new_text)\n\nf('hbtofdeiequ')\n", "category": "coding_general", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nWhat does this function return when called as shown? Reply with ONLY\nthe literal Python value — strings in quotes (for example: 42, [1, 2],\n'text', None), no explanation, no fences.\n\ndef f(text):\n new_text = list(text)\n for i in '+':\n if i in new_text:\n new_text.remove(i)\n return ''.join(new_text)\n\nf('hbtofdeiequ')\n", "category": "coding_general", "noise_level": "long"}
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{"text": "What does this function return when called as shown? Reply with ONLY\nthe literal Python value — strings in quotes (for example: 42, [1, 2],\n'text', None), no explanation, no fences.\n\ndef f(text, lower, upper):\n count = 0\n new_text = list()\n for char in text:\n char = lower if char.isdecimal() else upper\n if char in ['p', 'C']:\n count += 1\n new_text.append(char)\n return count, ''.join(new_text)\n\nf('DSUWeqExTQdCMGpqur', 'a', 'x')\n", "category": "coding_general", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nWhat does this function return when called as shown? Reply with ONLY\nthe literal Python value — strings in quotes (for example: 42, [1, 2],\n'text', None), no explanation, no fences.\n\ndef f(text, lower, upper):\n count = 0\n new_text = list()\n for char in text:\n char = lower if char.isdecimal() else upper\n if char in ['p', 'C']:\n count += 1\n new_text.append(char)\n return count, ''.join(new_text)\n\nf('DSUWeqExTQdCMGpqur', 'a', 'x')\n", "category": "coding_general", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nWhat does this function return when called as shown? Reply with ONLY\nthe literal Python value — strings in quotes (for example: 42, [1, 2],\n'text', None), no explanation, no fences.\n\ndef f(text, lower, upper):\n count = 0\n new_text = list()\n for char in text:\n char = lower if char.isdecimal() else upper\n if char in ['p', 'C']:\n count += 1\n new_text.append(char)\n return count, ''.join(new_text)\n\nf('DSUWeqExTQdCMGpqur', 'a', 'x')\n", "category": "coding_general", "noise_level": "long"}
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{"text": "What does this function return when called as shown? Reply with ONLY\nthe literal Python value — strings in quotes (for example: 42, [1, 2],\n'text', None), no explanation, no fences.\n\ndef f(dic):\n for k,v in sorted(dic.items(), key=lambda x: len(str(x)))[:-1]:\n dic.pop(k)\n return list(dic.items())\n\nf({'11': 52, '65': 34, 'a': 12, '4': 52, '74': 31})\n", "category": "coding_general", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nWhat does this function return when called as shown? Reply with ONLY\nthe literal Python value — strings in quotes (for example: 42, [1, 2],\n'text', None), no explanation, no fences.\n\ndef f(dic):\n for k,v in sorted(dic.items(), key=lambda x: len(str(x)))[:-1]:\n dic.pop(k)\n return list(dic.items())\n\nf({'11': 52, '65': 34, 'a': 12, '4': 52, '74': 31})\n", "category": "coding_general", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nWhat does this function return when called as shown? Reply with ONLY\nthe literal Python value — strings in quotes (for example: 42, [1, 2],\n'text', None), no explanation, no fences.\n\ndef f(dic):\n for k,v in sorted(dic.items(), key=lambda x: len(str(x)))[:-1]:\n dic.pop(k)\n return list(dic.items())\n\nf({'11': 52, '65': 34, 'a': 12, '4': 52, '74': 31})\n", "category": "coding_general", "noise_level": "long"}
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{"text": "Refactor this function to remove the repetition. Behaviour must be\npreserved EXACTLY, including for values that are present but falsy.\nReply with ONLY the rewritten function — no explanation, no fences.\n\ndef apply_settings(overrides):\n result = {}\n if \"retries\" in overrides:\n result[\"retries\"] = overrides[\"retries\"]\n else:\n result[\"retries\"] = 3\n if \"timeout\" in overrides:\n result[\"timeout\"] = overrides[\"timeout\"]\n else:\n result[\"timeout\"] = 30\n if \"verbose\" in overrides:\n result[\"verbose\"] = overrides[\"verbose\"]\n else:\n result[\"verbose\"] = False\n return result\n", "category": "coding_refactor", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nRefactor this function to remove the repetition. Behaviour must be\npreserved EXACTLY, including for values that are present but falsy.\nReply with ONLY the rewritten function — no explanation, no fences.\n\ndef apply_settings(overrides):\n result = {}\n if \"retries\" in overrides:\n result[\"retries\"] = overrides[\"retries\"]\n else:\n result[\"retries\"] = 3\n if \"timeout\" in overrides:\n result[\"timeout\"] = overrides[\"timeout\"]\n else:\n result[\"timeout\"] = 30\n if \"verbose\" in overrides:\n result[\"verbose\"] = overrides[\"verbose\"]\n else:\n result[\"verbose\"] = False\n return result\n", "category": "coding_refactor", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nRefactor this function to remove the repetition. Behaviour must be\npreserved EXACTLY, including for values that are present but falsy.\nReply with ONLY the rewritten function — no explanation, no fences.\n\ndef apply_settings(overrides):\n result = {}\n if \"retries\" in overrides:\n result[\"retries\"] = overrides[\"retries\"]\n else:\n result[\"retries\"] = 3\n if \"timeout\" in overrides:\n result[\"timeout\"] = overrides[\"timeout\"]\n else:\n result[\"timeout\"] = 30\n if \"verbose\" in overrides:\n result[\"verbose\"] = overrides[\"verbose\"]\n else:\n result[\"verbose\"] = False\n return result\n", "category": "coding_refactor", "noise_level": "long"}
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{"text": "Refactor this to remove the nested loops and the flag variable.\nBehaviour must be preserved exactly, including which item wins when\nseveral match. Reply with ONLY the rewritten function — no explanation,\nno fences.\n\ndef first_match(items, predicates):\n found = None\n done = False\n for item in items:\n if done:\n break\n for p in predicates:\n if p(item):\n found = item\n done = True\n break\n return found\n", "category": "coding_refactor", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nRefactor this to remove the nested loops and the flag variable.\nBehaviour must be preserved exactly, including which item wins when\nseveral match. Reply with ONLY the rewritten function — no explanation,\nno fences.\n\ndef first_match(items, predicates):\n found = None\n done = False\n for item in items:\n if done:\n break\n for p in predicates:\n if p(item):\n found = item\n done = True\n break\n return found\n", "category": "coding_refactor", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nRefactor this to remove the nested loops and the flag variable.\nBehaviour must be preserved exactly, including which item wins when\nseveral match. Reply with ONLY the rewritten function — no explanation,\nno fences.\n\ndef first_match(items, predicates):\n found = None\n done = False\n for item in items:\n if done:\n break\n for p in predicates:\n if p(item):\n found = item\n done = True\n break\n return found\n", "category": "coding_refactor", "noise_level": "long"}
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{"text": "Refactor this if/elif chain into a table-driven lookup. Behaviour must be\npreserved exactly for every input, including inputs that match no case.\nReply with ONLY the rewritten code — no explanation, no fences.\n\ndef describe(code):\n if code == 200:\n return \"ok\"\n elif code == 201:\n return \"created\"\n elif code == 404:\n return \"not found\"\n elif code == 500:\n return \"server error\"\n else:\n return \"unknown\"\n", "category": "coding_refactor", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nRefactor this if/elif chain into a table-driven lookup. Behaviour must be\npreserved exactly for every input, including inputs that match no case.\nReply with ONLY the rewritten code — no explanation, no fences.\n\ndef describe(code):\n if code == 200:\n return \"ok\"\n elif code == 201:\n return \"created\"\n elif code == 404:\n return \"not found\"\n elif code == 500:\n return \"server error\"\n else:\n return \"unknown\"\n", "category": "coding_refactor", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nRefactor this if/elif chain into a table-driven lookup. Behaviour must be\npreserved exactly for every input, including inputs that match no case.\nReply with ONLY the rewritten code — no explanation, no fences.\n\ndef describe(code):\n if code == 200:\n return \"ok\"\n elif code == 201:\n return \"created\"\n elif code == 404:\n return \"not found\"\n elif code == 500:\n return \"server error\"\n else:\n return \"unknown\"\n", "category": "coding_refactor", "noise_level": "long"}
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{"text": "Refactor this BowlingGame to remove the duplication and nested\nconditions. Behaviour must be preserved EXACTLY, including scoring,\nbonuses, and error cases. Reply with ONLY the rewritten class — no\nexplanation, no fences.\n\nclass BowlingGame:\n def __init__(self):\n self._frames = []\n self._current = 0\n self._bonus = []\n\n def roll(self, pins):\n if not (0 <= pins <= 10):\n raise ValueError('invalid pins')\n if self._current < 10:\n if len(self._frames) == self._current:\n self._frames.append([pins])\n else:\n self._frames[self._current].append(pins)\n current = self._frames[self._current]\n if sum(current) > 10:\n raise ValueError(\"a frame's rolls cannot exceed 10\")\n strike = (len(current) == 1 and current[0] == 10)\n if strike or len(current) == 2:\n self._current += 1\n else:\n last = self._frames[-1]\n last_total = sum(last)\n strike10 = len(last) == 1 and last[0] == 10\n spare10 = len(last) == 2 and last_total == 10\n if strike10:\n if len(self._bonus) >= 2:\n raise IndexError(\n 'wrong number of fill balls when the tenth frame is a strike')\n self._bonus.append(pins)\n if len(self._bonus) == 2 and self._bonus[0] != 10 and sum(self._bonus) > 10:\n raise ValueError('invalid fill balls')\n if len(self._bonus) > 2:\n raise IndexError(\n 'wrong number of fill balls when the tenth frame is a strike')\n elif spare10:\n if len(self._bonus) >= 1:\n raise IndexError(\n 'wrong number of fill balls when the tenth frame is a spare')\n self._bonus.append(pins)\n else:\n raise IndexError('cannot throw bonus with an open tenth frame')\n\n def score(self):\n if self._current < 10:\n raise IndexError('frame less than 10')\n last = self._frames[-1]\n if len(last) == 2 and sum(last) == 10 and len(self._bonus) != 1:\n raise IndexError('one bonus must be rolled when the tenth frame is spare')\n if len(last) == 1 and last[0] == 10 and len(self._bonus) != 2:\n raise IndexError('two bonuses must be rolled when the tenth frame is strike')\n total = 0\n for i in range(10):\n frame = self._frames[i]\n frame_sum = sum(frame)\n strike = (len(frame) == 1 and frame[0] == 10)\n spare = (len(frame) == 2 and frame_sum == 10)\n if strike or spare:\n nxt = []\n for j in range(i + 1, 10):\n nxt.extend(self._frames[j])\n nxt.extend(self._bonus)\n if strike:\n frame_sum += sum(nxt[:2])\n else:\n frame_sum += sum(nxt[:1])\n total += frame_sum\n return total\n", "category": "coding_refactor", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nRefactor this BowlingGame to remove the duplication and nested\nconditions. Behaviour must be preserved EXACTLY, including scoring,\nbonuses, and error cases. Reply with ONLY the rewritten class — no\nexplanation, no fences.\n\nclass BowlingGame:\n def __init__(self):\n self._frames = []\n self._current = 0\n self._bonus = []\n\n def roll(self, pins):\n if not (0 <= pins <= 10):\n raise ValueError('invalid pins')\n if self._current < 10:\n if len(self._frames) == self._current:\n self._frames.append([pins])\n else:\n self._frames[self._current].append(pins)\n current = self._frames[self._current]\n if sum(current) > 10:\n raise ValueError(\"a frame's rolls cannot exceed 10\")\n strike = (len(current) == 1 and current[0] == 10)\n if strike or len(current) == 2:\n self._current += 1\n else:\n last = self._frames[-1]\n last_total = sum(last)\n strike10 = len(last) == 1 and last[0] == 10\n spare10 = len(last) == 2 and last_total == 10\n if strike10:\n if len(self._bonus) >= 2:\n raise IndexError(\n 'wrong number of fill balls when the tenth frame is a strike')\n self._bonus.append(pins)\n if len(self._bonus) == 2 and self._bonus[0] != 10 and sum(self._bonus) > 10:\n raise ValueError('invalid fill balls')\n if len(self._bonus) > 2:\n raise IndexError(\n 'wrong number of fill balls when the tenth frame is a strike')\n elif spare10:\n if len(self._bonus) >= 1:\n raise IndexError(\n 'wrong number of fill balls when the tenth frame is a spare')\n self._bonus.append(pins)\n else:\n raise IndexError('cannot throw bonus with an open tenth frame')\n\n def score(self):\n if self._current < 10:\n raise IndexError('frame less than 10')\n last = self._frames[-1]\n if len(last) == 2 and sum(last) == 10 and len(self._bonus) != 1:\n raise IndexError('one bonus must be rolled when the tenth frame is spare')\n if len(last) == 1 and last[0] == 10 and len(self._bonus) != 2:\n raise IndexError('two bonuses must be rolled when the tenth frame is strike')\n total = 0\n for i in range(10):\n frame = self._frames[i]\n frame_sum = sum(frame)\n strike = (len(frame) == 1 and frame[0] == 10)\n spare = (len(frame) == 2 and frame_sum == 10)\n if strike or spare:\n nxt = []\n for j in range(i + 1, 10):\n nxt.extend(self._frames[j])\n nxt.extend(self._bonus)\n if strike:\n frame_sum += sum(nxt[:2])\n else:\n frame_sum += sum(nxt[:1])\n total += frame_sum\n return total\n", "category": "coding_refactor", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nRefactor this BowlingGame to remove the duplication and nested\nconditions. Behaviour must be preserved EXACTLY, including scoring,\nbonuses, and error cases. Reply with ONLY the rewritten class — no\nexplanation, no fences.\n\nclass BowlingGame:\n def __init__(self):\n self._frames = []\n self._current = 0\n self._bonus = []\n\n def roll(self, pins):\n if not (0 <= pins <= 10):\n raise ValueError('invalid pins')\n if self._current < 10:\n if len(self._frames) == self._current:\n self._frames.append([pins])\n else:\n self._frames[self._current].append(pins)\n current = self._frames[self._current]\n if sum(current) > 10:\n raise ValueError(\"a frame's rolls cannot exceed 10\")\n strike = (len(current) == 1 and current[0] == 10)\n if strike or len(current) == 2:\n self._current += 1\n else:\n last = self._frames[-1]\n last_total = sum(last)\n strike10 = len(last) == 1 and last[0] == 10\n spare10 = len(last) == 2 and last_total == 10\n if strike10:\n if len(self._bonus) >= 2:\n raise IndexError(\n 'wrong number of fill balls when the tenth frame is a strike')\n self._bonus.append(pins)\n if len(self._bonus) == 2 and self._bonus[0] != 10 and sum(self._bonus) > 10:\n raise ValueError('invalid fill balls')\n if len(self._bonus) > 2:\n raise IndexError(\n 'wrong number of fill balls when the tenth frame is a strike')\n elif spare10:\n if len(self._bonus) >= 1:\n raise IndexError(\n 'wrong number of fill balls when the tenth frame is a spare')\n self._bonus.append(pins)\n else:\n raise IndexError('cannot throw bonus with an open tenth frame')\n\n def score(self):\n if self._current < 10:\n raise IndexError('frame less than 10')\n last = self._frames[-1]\n if len(last) == 2 and sum(last) == 10 and len(self._bonus) != 1:\n raise IndexError('one bonus must be rolled when the tenth frame is spare')\n if len(last) == 1 and last[0] == 10 and len(self._bonus) != 2:\n raise IndexError('two bonuses must be rolled when the tenth frame is strike')\n total = 0\n for i in range(10):\n frame = self._frames[i]\n frame_sum = sum(frame)\n strike = (len(frame) == 1 and frame[0] == 10)\n spare = (len(frame) == 2 and frame_sum == 10)\n if strike or spare:\n nxt = []\n for j in range(i + 1, 10):\n nxt.extend(self._frames[j])\n nxt.extend(self._bonus)\n if strike:\n frame_sum += sum(nxt[:2])\n else:\n frame_sum += sum(nxt[:1])\n total += frame_sum\n return total\n", "category": "coding_refactor", "noise_level": "long"}
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{"text": "This BowlingGame is wrong on one subtle tenth-frame case. Fix ONLY the\nbug; do not change anything else. Reply with ONLY the corrected class —\nno explanation, no fences.\n\nclass BowlingGame:\n def __init__(self):\n self.current_frame_idx = 0\n self.bonus_throws = []\n self.frames = [Frame(idx) for idx in range(10)]\n\n @property\n def current_frame(self):\n return self.frames[self.current_frame_idx]\n\n def next_throws(self, frame_idx):\n throws = []\n for idx in range(frame_idx + 1, 10):\n throws.extend(self.frames[idx].throws)\n throws.extend(self.bonus_throws)\n return throws\n\n def roll_bonus(self, pins):\n tenth_frame = self.frames[-1]\n if tenth_frame.is_open():\n raise IndexError('cannot throw bonus with an open tenth frame')\n self.bonus_throws.append(pins)\n if tenth_frame.is_strike() and len(self.bonus_throws) > 2:\n raise IndexError(\n 'wrong number of fill balls when the tenth frame is a strike')\n elif tenth_frame.is_spare() and len(self.bonus_throws) > 1:\n raise IndexError(\n 'wrong number of fill balls when the tenth frame is a spare')\n\n def roll(self, pins):\n if not 0 <= pins <= 10:\n raise ValueError('invalid pins')\n elif self.current_frame_idx == 10:\n self.roll_bonus(pins)\n else:\n self.current_frame.throw(pins)\n if self.current_frame.is_closed():\n self.current_frame_idx += 1\n\n def score(self):\n if self.current_frame_idx < 10:\n raise IndexError('frame less than 10')\n if self.frames[-1].is_spare() and len(self.bonus_throws) != 1:\n raise IndexError(\n 'one bonus must be rolled when the tenth frame is spare')\n if self.frames[-1].is_strike() and len(self.bonus_throws) != 2:\n raise IndexError(\n 'two bonuses must be rolled when the tenth frame is strike')\n return sum(frame.score(self.next_throws(frame.idx))\n for frame in self.frames)\n\n\nclass Frame:\n def __init__(self, idx):\n self.idx = idx\n self.throws = []\n\n @property\n def total_pins(self):\n return sum(self.throws)\n\n def is_strike(self):\n return self.total_pins == 10 and len(self.throws) == 1\n\n def is_spare(self):\n return self.total_pins == 10 and len(self.throws) == 2\n\n def is_open(self):\n return self.total_pins < 10 and len(self.throws) == 2\n\n def is_closed(self):\n return self.total_pins == 10 or len(self.throws) == 2\n\n def throw(self, pins):\n if self.total_pins + pins > 10:\n raise ValueError(\"a frame's rolls cannot exceed 10\")\n self.throws.append(pins)\n\n def score(self, next_throws):\n result = self.total_pins\n if self.is_strike():\n result += sum(next_throws[:2])\n elif self.is_spare():\n result += sum(next_throws[:1])\n return result\n", "category": "debugging", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nThis BowlingGame is wrong on one subtle tenth-frame case. Fix ONLY the\nbug; do not change anything else. Reply with ONLY the corrected class —\nno explanation, no fences.\n\nclass BowlingGame:\n def __init__(self):\n self.current_frame_idx = 0\n self.bonus_throws = []\n self.frames = [Frame(idx) for idx in range(10)]\n\n @property\n def current_frame(self):\n return self.frames[self.current_frame_idx]\n\n def next_throws(self, frame_idx):\n throws = []\n for idx in range(frame_idx + 1, 10):\n throws.extend(self.frames[idx].throws)\n throws.extend(self.bonus_throws)\n return throws\n\n def roll_bonus(self, pins):\n tenth_frame = self.frames[-1]\n if tenth_frame.is_open():\n raise IndexError('cannot throw bonus with an open tenth frame')\n self.bonus_throws.append(pins)\n if tenth_frame.is_strike() and len(self.bonus_throws) > 2:\n raise IndexError(\n 'wrong number of fill balls when the tenth frame is a strike')\n elif tenth_frame.is_spare() and len(self.bonus_throws) > 1:\n raise IndexError(\n 'wrong number of fill balls when the tenth frame is a spare')\n\n def roll(self, pins):\n if not 0 <= pins <= 10:\n raise ValueError('invalid pins')\n elif self.current_frame_idx == 10:\n self.roll_bonus(pins)\n else:\n self.current_frame.throw(pins)\n if self.current_frame.is_closed():\n self.current_frame_idx += 1\n\n def score(self):\n if self.current_frame_idx < 10:\n raise IndexError('frame less than 10')\n if self.frames[-1].is_spare() and len(self.bonus_throws) != 1:\n raise IndexError(\n 'one bonus must be rolled when the tenth frame is spare')\n if self.frames[-1].is_strike() and len(self.bonus_throws) != 2:\n raise IndexError(\n 'two bonuses must be rolled when the tenth frame is strike')\n return sum(frame.score(self.next_throws(frame.idx))\n for frame in self.frames)\n\n\nclass Frame:\n def __init__(self, idx):\n self.idx = idx\n self.throws = []\n\n @property\n def total_pins(self):\n return sum(self.throws)\n\n def is_strike(self):\n return self.total_pins == 10 and len(self.throws) == 1\n\n def is_spare(self):\n return self.total_pins == 10 and len(self.throws) == 2\n\n def is_open(self):\n return self.total_pins < 10 and len(self.throws) == 2\n\n def is_closed(self):\n return self.total_pins == 10 or len(self.throws) == 2\n\n def throw(self, pins):\n if self.total_pins + pins > 10:\n raise ValueError(\"a frame's rolls cannot exceed 10\")\n self.throws.append(pins)\n\n def score(self, next_throws):\n result = self.total_pins\n if self.is_strike():\n result += sum(next_throws[:2])\n elif self.is_spare():\n result += sum(next_throws[:1])\n return result\n", "category": "debugging", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nThis BowlingGame is wrong on one subtle tenth-frame case. Fix ONLY the\nbug; do not change anything else. Reply with ONLY the corrected class —\nno explanation, no fences.\n\nclass BowlingGame:\n def __init__(self):\n self.current_frame_idx = 0\n self.bonus_throws = []\n self.frames = [Frame(idx) for idx in range(10)]\n\n @property\n def current_frame(self):\n return self.frames[self.current_frame_idx]\n\n def next_throws(self, frame_idx):\n throws = []\n for idx in range(frame_idx + 1, 10):\n throws.extend(self.frames[idx].throws)\n throws.extend(self.bonus_throws)\n return throws\n\n def roll_bonus(self, pins):\n tenth_frame = self.frames[-1]\n if tenth_frame.is_open():\n raise IndexError('cannot throw bonus with an open tenth frame')\n self.bonus_throws.append(pins)\n if tenth_frame.is_strike() and len(self.bonus_throws) > 2:\n raise IndexError(\n 'wrong number of fill balls when the tenth frame is a strike')\n elif tenth_frame.is_spare() and len(self.bonus_throws) > 1:\n raise IndexError(\n 'wrong number of fill balls when the tenth frame is a spare')\n\n def roll(self, pins):\n if not 0 <= pins <= 10:\n raise ValueError('invalid pins')\n elif self.current_frame_idx == 10:\n self.roll_bonus(pins)\n else:\n self.current_frame.throw(pins)\n if self.current_frame.is_closed():\n self.current_frame_idx += 1\n\n def score(self):\n if self.current_frame_idx < 10:\n raise IndexError('frame less than 10')\n if self.frames[-1].is_spare() and len(self.bonus_throws) != 1:\n raise IndexError(\n 'one bonus must be rolled when the tenth frame is spare')\n if self.frames[-1].is_strike() and len(self.bonus_throws) != 2:\n raise IndexError(\n 'two bonuses must be rolled when the tenth frame is strike')\n return sum(frame.score(self.next_throws(frame.idx))\n for frame in self.frames)\n\n\nclass Frame:\n def __init__(self, idx):\n self.idx = idx\n self.throws = []\n\n @property\n def total_pins(self):\n return sum(self.throws)\n\n def is_strike(self):\n return self.total_pins == 10 and len(self.throws) == 1\n\n def is_spare(self):\n return self.total_pins == 10 and len(self.throws) == 2\n\n def is_open(self):\n return self.total_pins < 10 and len(self.throws) == 2\n\n def is_closed(self):\n return self.total_pins == 10 or len(self.throws) == 2\n\n def throw(self, pins):\n if self.total_pins + pins > 10:\n raise ValueError(\"a frame's rolls cannot exceed 10\")\n self.throws.append(pins)\n\n def score(self, next_throws):\n result = self.total_pins\n if self.is_strike():\n result += sum(next_throws[:2])\n elif self.is_spare():\n result += sum(next_throws[:1])\n return result\n", "category": "debugging", "noise_level": "long"}
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{"text": "Refactor this can_chain to remove the duplicated chain-building\nconditions and the flag variable. Behaviour must be preserved EXACTLY:\nfor a set of dominoes that can form a valid chain it returns a valid\nchain (ANY valid chain — not a fixed one), and None when no chain is\npossible. Reply with ONLY the rewritten function — no explanation, no\nfences.\n\nfrom itertools import permutations\n\n\ndef can_chain(dominoes):\n if not any(dominoes):\n return []\n for perm in permutations(dominoes):\n chain = [perm[0]]\n complete = True\n for domino in perm[1:]:\n prev = chain[-1]\n if len(chain) == 1 and prev[0] == domino[0]:\n chain = [(prev[1], prev[0]), domino]\n elif len(chain) == 1 and prev[0] == domino[1]:\n chain = [(prev[1], prev[0]), (domino[1], domino[0])]\n elif prev[1] == domino[0]:\n chain = chain + [domino]\n elif prev[1] == domino[1]:\n chain = chain + [(domino[1], domino[0])]\n else:\n complete = False\n break\n if complete and chain[0][0] == chain[-1][1]:\n return chain\n return None\n", "category": "coding_refactor", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nRefactor this can_chain to remove the duplicated chain-building\nconditions and the flag variable. Behaviour must be preserved EXACTLY:\nfor a set of dominoes that can form a valid chain it returns a valid\nchain (ANY valid chain — not a fixed one), and None when no chain is\npossible. Reply with ONLY the rewritten function — no explanation, no\nfences.\n\nfrom itertools import permutations\n\n\ndef can_chain(dominoes):\n if not any(dominoes):\n return []\n for perm in permutations(dominoes):\n chain = [perm[0]]\n complete = True\n for domino in perm[1:]:\n prev = chain[-1]\n if len(chain) == 1 and prev[0] == domino[0]:\n chain = [(prev[1], prev[0]), domino]\n elif len(chain) == 1 and prev[0] == domino[1]:\n chain = [(prev[1], prev[0]), (domino[1], domino[0])]\n elif prev[1] == domino[0]:\n chain = chain + [domino]\n elif prev[1] == domino[1]:\n chain = chain + [(domino[1], domino[0])]\n else:\n complete = False\n break\n if complete and chain[0][0] == chain[-1][1]:\n return chain\n return None\n", "category": "coding_refactor", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nRefactor this can_chain to remove the duplicated chain-building\nconditions and the flag variable. Behaviour must be preserved EXACTLY:\nfor a set of dominoes that can form a valid chain it returns a valid\nchain (ANY valid chain — not a fixed one), and None when no chain is\npossible. Reply with ONLY the rewritten function — no explanation, no\nfences.\n\nfrom itertools import permutations\n\n\ndef can_chain(dominoes):\n if not any(dominoes):\n return []\n for perm in permutations(dominoes):\n chain = [perm[0]]\n complete = True\n for domino in perm[1:]:\n prev = chain[-1]\n if len(chain) == 1 and prev[0] == domino[0]:\n chain = [(prev[1], prev[0]), domino]\n elif len(chain) == 1 and prev[0] == domino[1]:\n chain = [(prev[1], prev[0]), (domino[1], domino[0])]\n elif prev[1] == domino[0]:\n chain = chain + [domino]\n elif prev[1] == domino[1]:\n chain = chain + [(domino[1], domino[0])]\n else:\n complete = False\n break\n if complete and chain[0][0] == chain[-1][1]:\n return chain\n return None\n", "category": "coding_refactor", "noise_level": "long"}
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{"text": "This can_chain returns a bogus \"chain\" for inputs that cannot be\nchained — it returns a list instead of None when no valid chain exists.\nFix ONLY the one subtle bug; do not change anything else, and do not\nchange the can_chain signature. Reply with ONLY the corrected function\n— no explanation, no fences.\n\nfrom itertools import permutations\nfrom functools import reduce\n\n\ndef swap(item_1, item_2):\n return (item_2, item_1)\n\n\ndef build_chain(chain, domino):\n if chain is not None:\n last = chain[-1]\n if len(chain) == 1 and last[0] == domino[0]:\n return [swap(*last), domino]\n elif len(chain) == 1 and last[0] == domino[1]:\n return [swap(*last), swap(*domino)]\n elif last[1] == domino[0]:\n return chain + [domino]\n elif last[1] == domino[1]:\n return chain + [swap(*domino)]\n return None\n\n\ndef can_chain(dominoes):\n if not any(dominoes):\n return []\n for perm in permutations(dominoes):\n chain = reduce(build_chain, perm[1:], [perm[0]])\n # BUG: the circular-closure check (chain[0][0] == chain[-1][1])\n # is missing, so a line that merely matches end-to-start is\n # returned even when it does not close into a loop.\n if chain is not None:\n return chain\n return None\n", "category": "debugging", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nThis can_chain returns a bogus \"chain\" for inputs that cannot be\nchained — it returns a list instead of None when no valid chain exists.\nFix ONLY the one subtle bug; do not change anything else, and do not\nchange the can_chain signature. Reply with ONLY the corrected function\n— no explanation, no fences.\n\nfrom itertools import permutations\nfrom functools import reduce\n\n\ndef swap(item_1, item_2):\n return (item_2, item_1)\n\n\ndef build_chain(chain, domino):\n if chain is not None:\n last = chain[-1]\n if len(chain) == 1 and last[0] == domino[0]:\n return [swap(*last), domino]\n elif len(chain) == 1 and last[0] == domino[1]:\n return [swap(*last), swap(*domino)]\n elif last[1] == domino[0]:\n return chain + [domino]\n elif last[1] == domino[1]:\n return chain + [swap(*domino)]\n return None\n\n\ndef can_chain(dominoes):\n if not any(dominoes):\n return []\n for perm in permutations(dominoes):\n chain = reduce(build_chain, perm[1:], [perm[0]])\n # BUG: the circular-closure check (chain[0][0] == chain[-1][1])\n # is missing, so a line that merely matches end-to-start is\n # returned even when it does not close into a loop.\n if chain is not None:\n return chain\n return None\n", "category": "debugging", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nThis can_chain returns a bogus \"chain\" for inputs that cannot be\nchained — it returns a list instead of None when no valid chain exists.\nFix ONLY the one subtle bug; do not change anything else, and do not\nchange the can_chain signature. Reply with ONLY the corrected function\n— no explanation, no fences.\n\nfrom itertools import permutations\nfrom functools import reduce\n\n\ndef swap(item_1, item_2):\n return (item_2, item_1)\n\n\ndef build_chain(chain, domino):\n if chain is not None:\n last = chain[-1]\n if len(chain) == 1 and last[0] == domino[0]:\n return [swap(*last), domino]\n elif len(chain) == 1 and last[0] == domino[1]:\n return [swap(*last), swap(*domino)]\n elif last[1] == domino[0]:\n return chain + [domino]\n elif last[1] == domino[1]:\n return chain + [swap(*domino)]\n return None\n\n\ndef can_chain(dominoes):\n if not any(dominoes):\n return []\n for perm in permutations(dominoes):\n chain = reduce(build_chain, perm[1:], [perm[0]])\n # BUG: the circular-closure check (chain[0][0] == chain[-1][1])\n # is missing, so a line that merely matches end-to-start is\n # returned even when it does not close into a loop.\n if chain is not None:\n return chain\n return None\n", "category": "debugging", "noise_level": "long"}
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{"text": "Refactor this affine cipher to remove the duplicated cipher math. The\nsame letter-to-index transform and the coprime guard appear inline in\nboth encode and decode; behavioural duplicates like these are where bugs\nhide. Consolidate them. Behaviour must be preserved EXACTLY, including\nthe ValueError raised when `a` is not coprime with the alphabet size and\nthe 5-character block grouping in encode. Keep the module functions\n`encode(plain, a, b)` and `decode(ciphered, a, b)`. Reply with ONLY the\nrewritten module — no explanation, no fences.\n\nBLOCK_SIZE = 5\nALPHABET = 26\n\n\ndef mod_inverse(a_key, alphabet):\n a_key = a_key % alphabet\n for idx in range(1, alphabet):\n if (a_key * idx) % alphabet == 1:\n return idx\n return 1\n\n\ndef encode(plain, a, b):\n inverse = mod_inverse(a, ALPHABET)\n if inverse == 1:\n raise ValueError('a and m must be coprime.')\n chars = []\n for character in plain:\n if character.isalnum():\n origin = ord(character.lower()) - 97\n if origin < 0:\n chars.append(character)\n continue\n new = (a * origin + b) % ALPHABET\n chars.append(chr(new + 97))\n cipher = ''.join(chars)\n return ' '.join([cipher[idx:idx + BLOCK_SIZE]\n for idx in range(0, len(cipher), BLOCK_SIZE)])\n\n\ndef decode(ciphered, a, b):\n inverse = mod_inverse(a, ALPHABET)\n if inverse == 1:\n raise ValueError('a and m must be coprime.')\n chars = []\n for character in ciphered:\n if character.isalnum():\n origin = ord(character.lower()) - 97\n if origin < 0:\n chars.append(character)\n continue\n new = (inverse * (origin - b)) % ALPHABET\n chars.append(chr(new + 97))\n return ''.join(chars)\n", "category": "coding_refactor", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nRefactor this affine cipher to remove the duplicated cipher math. The\nsame letter-to-index transform and the coprime guard appear inline in\nboth encode and decode; behavioural duplicates like these are where bugs\nhide. Consolidate them. Behaviour must be preserved EXACTLY, including\nthe ValueError raised when `a` is not coprime with the alphabet size and\nthe 5-character block grouping in encode. Keep the module functions\n`encode(plain, a, b)` and `decode(ciphered, a, b)`. Reply with ONLY the\nrewritten module — no explanation, no fences.\n\nBLOCK_SIZE = 5\nALPHABET = 26\n\n\ndef mod_inverse(a_key, alphabet):\n a_key = a_key % alphabet\n for idx in range(1, alphabet):\n if (a_key * idx) % alphabet == 1:\n return idx\n return 1\n\n\ndef encode(plain, a, b):\n inverse = mod_inverse(a, ALPHABET)\n if inverse == 1:\n raise ValueError('a and m must be coprime.')\n chars = []\n for character in plain:\n if character.isalnum():\n origin = ord(character.lower()) - 97\n if origin < 0:\n chars.append(character)\n continue\n new = (a * origin + b) % ALPHABET\n chars.append(chr(new + 97))\n cipher = ''.join(chars)\n return ' '.join([cipher[idx:idx + BLOCK_SIZE]\n for idx in range(0, len(cipher), BLOCK_SIZE)])\n\n\ndef decode(ciphered, a, b):\n inverse = mod_inverse(a, ALPHABET)\n if inverse == 1:\n raise ValueError('a and m must be coprime.')\n chars = []\n for character in ciphered:\n if character.isalnum():\n origin = ord(character.lower()) - 97\n if origin < 0:\n chars.append(character)\n continue\n new = (inverse * (origin - b)) % ALPHABET\n chars.append(chr(new + 97))\n return ''.join(chars)\n", "category": "coding_refactor", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nRefactor this affine cipher to remove the duplicated cipher math. The\nsame letter-to-index transform and the coprime guard appear inline in\nboth encode and decode; behavioural duplicates like these are where bugs\nhide. Consolidate them. Behaviour must be preserved EXACTLY, including\nthe ValueError raised when `a` is not coprime with the alphabet size and\nthe 5-character block grouping in encode. Keep the module functions\n`encode(plain, a, b)` and `decode(ciphered, a, b)`. Reply with ONLY the\nrewritten module — no explanation, no fences.\n\nBLOCK_SIZE = 5\nALPHABET = 26\n\n\ndef mod_inverse(a_key, alphabet):\n a_key = a_key % alphabet\n for idx in range(1, alphabet):\n if (a_key * idx) % alphabet == 1:\n return idx\n return 1\n\n\ndef encode(plain, a, b):\n inverse = mod_inverse(a, ALPHABET)\n if inverse == 1:\n raise ValueError('a and m must be coprime.')\n chars = []\n for character in plain:\n if character.isalnum():\n origin = ord(character.lower()) - 97\n if origin < 0:\n chars.append(character)\n continue\n new = (a * origin + b) % ALPHABET\n chars.append(chr(new + 97))\n cipher = ''.join(chars)\n return ' '.join([cipher[idx:idx + BLOCK_SIZE]\n for idx in range(0, len(cipher), BLOCK_SIZE)])\n\n\ndef decode(ciphered, a, b):\n inverse = mod_inverse(a, ALPHABET)\n if inverse == 1:\n raise ValueError('a and m must be coprime.')\n chars = []\n for character in ciphered:\n if character.isalnum():\n origin = ord(character.lower()) - 97\n if origin < 0:\n chars.append(character)\n continue\n new = (inverse * (origin - b)) % ALPHABET\n chars.append(chr(new + 97))\n return ''.join(chars)\n", "category": "coding_refactor", "noise_level": "long"}
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{"text": "This affine cipher fails to reject keys where `a` is not coprime with the\nalphabet size. It should raise ValueError('a and m must be coprime.')\nwhen `a` shares a factor with 26, but it lets those keys through. Fix\nONLY the one subtle bug in the coprime guard; do not change anything\nelse, and do not change the signatures of `encode(plain, a, b)` or\n`decode(ciphered, a, b)`. Reply with ONLY the corrected module — no\nexplanation, no fences.\n\nBLOCK_SIZE = 5\nALPHABET = 26\n\n\ndef mod_inverse(a_key, alphabet):\n a_key = a_key % alphabet\n for idx in range(1, alphabet):\n if (a_key * idx) % alphabet == 1:\n return idx\n return 1\n\n\ndef translate(text, a_key, b_key, mode):\n inverse = mod_inverse(a_key, ALPHABET)\n if inverse < 1:\n raise ValueError('a and m must be coprime.')\n chars = []\n for character in text:\n if character.isalnum():\n origin = ord(character.lower()) - 97\n if origin < 0:\n chars.append(character)\n continue\n if mode == 0:\n new = (a_key * origin + b_key) % ALPHABET\n elif mode == 1:\n new = (inverse * (origin - b_key)) % ALPHABET\n chars.append(chr(new + 97))\n return ''.join(chars)\n\n\ndef encode(plain, a, b):\n cipher = translate(plain, a, b, 0)\n return ' '.join([cipher[idx:idx + BLOCK_SIZE]\n for idx in range(0, len(cipher), BLOCK_SIZE)])\n\n\ndef decode(ciphered, a, b):\n return translate(ciphered, a, b, 1)\n", "category": "debugging", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nThis affine cipher fails to reject keys where `a` is not coprime with the\nalphabet size. It should raise ValueError('a and m must be coprime.')\nwhen `a` shares a factor with 26, but it lets those keys through. Fix\nONLY the one subtle bug in the coprime guard; do not change anything\nelse, and do not change the signatures of `encode(plain, a, b)` or\n`decode(ciphered, a, b)`. Reply with ONLY the corrected module — no\nexplanation, no fences.\n\nBLOCK_SIZE = 5\nALPHABET = 26\n\n\ndef mod_inverse(a_key, alphabet):\n a_key = a_key % alphabet\n for idx in range(1, alphabet):\n if (a_key * idx) % alphabet == 1:\n return idx\n return 1\n\n\ndef translate(text, a_key, b_key, mode):\n inverse = mod_inverse(a_key, ALPHABET)\n if inverse < 1:\n raise ValueError('a and m must be coprime.')\n chars = []\n for character in text:\n if character.isalnum():\n origin = ord(character.lower()) - 97\n if origin < 0:\n chars.append(character)\n continue\n if mode == 0:\n new = (a_key * origin + b_key) % ALPHABET\n elif mode == 1:\n new = (inverse * (origin - b_key)) % ALPHABET\n chars.append(chr(new + 97))\n return ''.join(chars)\n\n\ndef encode(plain, a, b):\n cipher = translate(plain, a, b, 0)\n return ' '.join([cipher[idx:idx + BLOCK_SIZE]\n for idx in range(0, len(cipher), BLOCK_SIZE)])\n\n\ndef decode(ciphered, a, b):\n return translate(ciphered, a, b, 1)\n", "category": "debugging", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nThis affine cipher fails to reject keys where `a` is not coprime with the\nalphabet size. It should raise ValueError('a and m must be coprime.')\nwhen `a` shares a factor with 26, but it lets those keys through. Fix\nONLY the one subtle bug in the coprime guard; do not change anything\nelse, and do not change the signatures of `encode(plain, a, b)` or\n`decode(ciphered, a, b)`. Reply with ONLY the corrected module — no\nexplanation, no fences.\n\nBLOCK_SIZE = 5\nALPHABET = 26\n\n\ndef mod_inverse(a_key, alphabet):\n a_key = a_key % alphabet\n for idx in range(1, alphabet):\n if (a_key * idx) % alphabet == 1:\n return idx\n return 1\n\n\ndef translate(text, a_key, b_key, mode):\n inverse = mod_inverse(a_key, ALPHABET)\n if inverse < 1:\n raise ValueError('a and m must be coprime.')\n chars = []\n for character in text:\n if character.isalnum():\n origin = ord(character.lower()) - 97\n if origin < 0:\n chars.append(character)\n continue\n if mode == 0:\n new = (a_key * origin + b_key) % ALPHABET\n elif mode == 1:\n new = (inverse * (origin - b_key)) % ALPHABET\n chars.append(chr(new + 97))\n return ''.join(chars)\n\n\ndef encode(plain, a, b):\n cipher = translate(plain, a, b, 0)\n return ' '.join([cipher[idx:idx + BLOCK_SIZE]\n for idx in range(0, len(cipher), BLOCK_SIZE)])\n\n\ndef decode(ciphered, a, b):\n return translate(ciphered, a, b, 1)\n", "category": "debugging", "noise_level": "long"}
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{"text": "This should return one multiplier function per factor, but every\nreturned function behaves the same. Fix it. Reply with ONLY the\ncorrected function — no explanation, no fences.\n\ndef make_multipliers(factors):\n out = []\n for f in factors:\n out.append(lambda x: x * f)\n return out\n", "category": "debugging", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nThis should return one multiplier function per factor, but every\nreturned function behaves the same. Fix it. Reply with ONLY the\ncorrected function — no explanation, no fences.\n\ndef make_multipliers(factors):\n out = []\n for f in factors:\n out.append(lambda x: x * f)\n return out\n", "category": "debugging", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nThis should return one multiplier function per factor, but every\nreturned function behaves the same. Fix it. Reply with ONLY the\ncorrected function — no explanation, no fences.\n\ndef make_multipliers(factors):\n out = []\n for f in factors:\n out.append(lambda x: x * f)\n return out\n", "category": "debugging", "noise_level": "long"}
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{"text": "This binary search should return the index of target in a sorted list,\nor -1 if absent. It is wrong for some inputs — one case loops forever.\nFix it. Reply with ONLY the corrected function — no explanation, no\nfences.\n\ndef bsearch(items, target):\n lo, hi = 0, len(items)\n while lo < hi:\n mid = (lo + hi) // 2\n if items[mid] == target:\n return mid\n elif items[mid] < target:\n lo = mid\n else:\n hi = mid\n return -1\n", "category": "debugging", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nThis binary search should return the index of target in a sorted list,\nor -1 if absent. It is wrong for some inputs — one case loops forever.\nFix it. Reply with ONLY the corrected function — no explanation, no\nfences.\n\ndef bsearch(items, target):\n lo, hi = 0, len(items)\n while lo < hi:\n mid = (lo + hi) // 2\n if items[mid] == target:\n return mid\n elif items[mid] < target:\n lo = mid\n else:\n hi = mid\n return -1\n", "category": "debugging", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nThis binary search should return the index of target in a sorted list,\nor -1 if absent. It is wrong for some inputs — one case loops forever.\nFix it. Reply with ONLY the corrected function — no explanation, no\nfences.\n\ndef bsearch(items, target):\n lo, hi = 0, len(items)\n while lo < hi:\n mid = (lo + hi) // 2\n if items[mid] == target:\n return mid\n elif items[mid] < target:\n lo = mid\n else:\n hi = mid\n return -1\n", "category": "debugging", "noise_level": "long"}
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{"text": "This should return the name inside each angle-bracket tag, in order, but\nit returns the wrong thing when there is more than one tag. Fix it.\nReply with ONLY the corrected function — no explanation, no fences.\n\nimport re\n\ndef extract_tags(text):\n return re.findall(r\"<(.+)>\", text)\n", "category": "debugging", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nThis should return the name inside each angle-bracket tag, in order, but\nit returns the wrong thing when there is more than one tag. Fix it.\nReply with ONLY the corrected function — no explanation, no fences.\n\nimport re\n\ndef extract_tags(text):\n return re.findall(r\"<(.+)>\", text)\n", "category": "debugging", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nThis should return the name inside each angle-bracket tag, in order, but\nit returns the wrong thing when there is more than one tag. Fix it.\nReply with ONLY the corrected function — no explanation, no fences.\n\nimport re\n\ndef extract_tags(text):\n return re.findall(r\"<(.+)>\", text)\n", "category": "debugging", "noise_level": "long"}
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{"text": "A price rises by 20%, then falls by 20% of its new value. The final\nprice is 96. What was the original price? Reply with ONLY the number.\n", "category": "reasoning_math", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nA price rises by 20%, then falls by 20% of its new value. The final\nprice is 96. What was the original price? Reply with ONLY the number.\n", "category": "reasoning_math", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nA price rises by 20%, then falls by 20% of its new value. The final\nprice is 96. What was the original price? Reply with ONLY the number.\n", "category": "reasoning_math", "noise_level": "long"}
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{"text": "Three machines take 3 minutes to make 3 widgets, each machine working\nindependently at the same constant rate. How many minutes do 100\nmachines take to make 100 widgets? Reply with ONLY the number.\n", "category": "reasoning_math", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nThree machines take 3 minutes to make 3 widgets, each machine working\nindependently at the same constant rate. How many minutes do 100\nmachines take to make 100 widgets? Reply with ONLY the number.\n", "category": "reasoning_math", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nThree machines take 3 minutes to make 3 widgets, each machine working\nindependently at the same constant rate. How many minutes do 100\nmachines take to make 100 widgets? Reply with ONLY the number.\n", "category": "reasoning_math", "noise_level": "long"}
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{"text": "How many 4-digit whole numbers have four distinct digits and do not\nbegin with 0? Reply with ONLY the number.\n", "category": "reasoning_math", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nHow many 4-digit whole numbers have four distinct digits and do not\nbegin with 0? Reply with ONLY the number.\n", "category": "reasoning_math", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nHow many 4-digit whole numbers have four distinct digits and do not\nbegin with 0? Reply with ONLY the number.\n", "category": "reasoning_math", "noise_level": "long"}
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{"text": "Convert 250 US dollars into Japanese yen.", "category": "tool_use_agentic", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nConvert 250 US dollars into Japanese yen.", "category": "tool_use_agentic", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nConvert 250 US dollars into Japanese yen.", "category": "tool_use_agentic", "noise_level": "long"}
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{"text": "It is 1:20pm and my meeting starts at 3pm. How many minutes away is it?\n", "category": "tool_use_agentic", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nIt is 1:20pm and my meeting starts at 3pm. How many minutes away is it?\n", "category": "tool_use_agentic", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nIt is 1:20pm and my meeting starts at 3pm. How many minutes away is it?\n", "category": "tool_use_agentic", "noise_level": "long"}
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{"text": "Write me a haiku about winter.", "category": "tool_use_agentic", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nWrite me a haiku about winter.", "category": "tool_use_agentic", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nWrite me a haiku about winter.", "category": "tool_use_agentic", "noise_level": "long"}
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{"text": "I'd appreciate if you could fetch the DNS resolution info for the domain mapped to IP 255.255.255.0 from VirusTotal. My key for this operation is 'sample_key4'.", "category": "tool_use_agentic", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nI'd appreciate if you could fetch the DNS resolution info for the domain mapped to IP 255.255.255.0 from VirusTotal. My key for this operation is 'sample_key4'.", "category": "tool_use_agentic", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nI'd appreciate if you could fetch the DNS resolution info for the domain mapped to IP 255.255.255.0 from VirusTotal. My key for this operation is 'sample_key4'.", "category": "tool_use_agentic", "noise_level": "long"}
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{"text": "What is diffrence between cpu and gpu?", "category": "tool_use_agentic", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nWhat is diffrence between cpu and gpu?", "category": "tool_use_agentic", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nWhat is diffrence between cpu and gpu?", "category": "tool_use_agentic", "noise_level": "long"}
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{"text": "Please help me get the votes associated with the IP of http://digdeep.io.", "category": "tool_use_agentic", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nPlease help me get the votes associated with the IP of http://digdeep.io.", "category": "tool_use_agentic", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nPlease help me get the votes associated with the IP of http://digdeep.io.", "category": "tool_use_agentic", "noise_level": "long"}
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{"text": "Using 'api_key_2', retrieve the IDs of graphs containing IP 145.34.45.56 on VirusTotal. Don't forget to set the cursor as 'cursor_b' and limit the results to 8.", "category": "tool_use_agentic", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nUsing 'api_key_2', retrieve the IDs of graphs containing IP 145.34.45.56 on VirusTotal. Don't forget to set the cursor as 'cursor_b' and limit the results to 8.", "category": "tool_use_agentic", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nUsing 'api_key_2', retrieve the IDs of graphs containing IP 145.34.45.56 on VirusTotal. Don't forget to set the cursor as 'cursor_b' and limit the results to 8.", "category": "tool_use_agentic", "noise_level": "long"}
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{"text": "How do I pull the domain info of twitter.com from VirusTotal? Using this API key: twt_key_abc.", "category": "tool_use_agentic", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nHow do I pull the domain info of twitter.com from VirusTotal? Using this API key: twt_key_abc.", "category": "tool_use_agentic", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nHow do I pull the domain info of twitter.com from VirusTotal? Using this API key: twt_key_abc.", "category": "tool_use_agentic", "noise_level": "long"}
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{"text": "Can you retrieve the details for the user with the ID 7890, who has black as their special request?", "category": "tool_use_agentic", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nCan you retrieve the details for the user with the ID 7890, who has black as their special request?", "category": "tool_use_agentic", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nCan you retrieve the details for the user with the ID 7890, who has black as their special request?", "category": "tool_use_agentic", "noise_level": "long"}
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{"text": "I want to see the star history of ShishirPatil/gorilla and gorilla-llm/gorilla-cli, with the timelines aligned, so that I can more clearly observe the rate of change from their initial releases.", "category": "tool_use_agentic", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nI want to see the star history of ShishirPatil/gorilla and gorilla-llm/gorilla-cli, with the timelines aligned, so that I can more clearly observe the rate of change from their initial releases.", "category": "tool_use_agentic", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nI want to see the star history of ShishirPatil/gorilla and gorilla-llm/gorilla-cli, with the timelines aligned, so that I can more clearly observe the rate of change from their initial releases.", "category": "tool_use_agentic", "noise_level": "long"}
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{"text": "What are the current weather conditions in Tel Aviv, and could you provide that in Fahrenheit, please?", "category": "tool_use_agentic", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nWhat are the current weather conditions in Tel Aviv, and could you provide that in Fahrenheit, please?", "category": "tool_use_agentic", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nWhat are the current weather conditions in Tel Aviv, and could you provide that in Fahrenheit, please?", "category": "tool_use_agentic", "noise_level": "long"}
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{"text": "Write a docstring for this function. Reply with ONLY the docstring text.\n\ndef retry(fn, attempts=3, backoff=2.0):\n delay = 1.0\n for i in range(attempts):\n try:\n return fn()\n except Exception:\n if i == attempts - 1:\n raise\n time.sleep(delay)\n delay *= backoff\n", "category": "docs_writing", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nWrite a docstring for this function. Reply with ONLY the docstring text.\n\ndef retry(fn, attempts=3, backoff=2.0):\n delay = 1.0\n for i in range(attempts):\n try:\n return fn()\n except Exception:\n if i == attempts - 1:\n raise\n time.sleep(delay)\n delay *= backoff\n", "category": "docs_writing", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nWrite a docstring for this function. Reply with ONLY the docstring text.\n\ndef retry(fn, attempts=3, backoff=2.0):\n delay = 1.0\n for i in range(attempts):\n try:\n return fn()\n except Exception:\n if i == attempts - 1:\n raise\n time.sleep(delay)\n delay *= backoff\n", "category": "docs_writing", "noise_level": "long"}
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{"text": "Write a docstring for this function. Reply with ONLY the docstring text.\n\ndef dedupe(items, key=None):\n seen = set()\n out = []\n for item in items:\n k = key(item) if key else item\n if k in seen:\n continue\n seen.add(k)\n out.append(item)\n return out\n", "category": "docs_writing", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nWrite a docstring for this function. Reply with ONLY the docstring text.\n\ndef dedupe(items, key=None):\n seen = set()\n out = []\n for item in items:\n k = key(item) if key else item\n if k in seen:\n continue\n seen.add(k)\n out.append(item)\n return out\n", "category": "docs_writing", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nWrite a docstring for this function. Reply with ONLY the docstring text.\n\ndef dedupe(items, key=None):\n seen = set()\n out = []\n for item in items:\n k = key(item) if key else item\n if k in seen:\n continue\n seen.add(k)\n out.append(item)\n return out\n", "category": "docs_writing", "noise_level": "long"}
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{"text": "Summarize in at most two sentences:\n\nAt 02:14 UTC the checkout service began returning 502s. The on-call\nengineer found the connection pool exhausted. A deploy at 01:58 had\nlowered the pool size from 50 to 5 through a bad template variable. The\ndeploy was rolled back at 02:31 and errors stopped by 02:34. Roughly\n12,000 requests failed. No data was lost.\n", "category": "summarization", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nSummarize in at most two sentences:\n\nAt 02:14 UTC the checkout service began returning 502s. The on-call\nengineer found the connection pool exhausted. A deploy at 01:58 had\nlowered the pool size from 50 to 5 through a bad template variable. The\ndeploy was rolled back at 02:31 and errors stopped by 02:34. Roughly\n12,000 requests failed. No data was lost.\n", "category": "summarization", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nSummarize in at most two sentences:\n\nAt 02:14 UTC the checkout service began returning 502s. The on-call\nengineer found the connection pool exhausted. A deploy at 01:58 had\nlowered the pool size from 50 to 5 through a bad template variable. The\ndeploy was rolled back at 02:31 and errors stopped by 02:34. Roughly\n12,000 requests failed. No data was lost.\n", "category": "summarization", "noise_level": "long"}
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{"text": "Summarize the single most important point in one sentence:\n\nThe migration ran for six hours. Throughput averaged 4,200 rows per\nsecond, peaking at 6,100. The team used a rolling window of 5,000 rows\nper batch. Disk usage on the replica grew steadily. Partway through, a\nunique constraint on the accounts table silently rejected 812 rows,\nwhich were logged to a dead-letter file that nobody has yet processed.\nCPU stayed under 40% throughout.\n", "category": "summarization", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nSummarize the single most important point in one sentence:\n\nThe migration ran for six hours. Throughput averaged 4,200 rows per\nsecond, peaking at 6,100. The team used a rolling window of 5,000 rows\nper batch. Disk usage on the replica grew steadily. Partway through, a\nunique constraint on the accounts table silently rejected 812 rows,\nwhich were logged to a dead-letter file that nobody has yet processed.\nCPU stayed under 40% throughout.\n", "category": "summarization", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nSummarize the single most important point in one sentence:\n\nThe migration ran for six hours. Throughput averaged 4,200 rows per\nsecond, peaking at 6,100. The team used a rolling window of 5,000 rows\nper batch. Disk usage on the replica grew steadily. Partway through, a\nunique constraint on the accounts table silently rejected 812 rows,\nwhich were logged to a dead-letter file that nobody has yet processed.\nCPU stayed under 40% throughout.\n", "category": "summarization", "noise_level": "long"}
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{"text": "Translate into French. Reply with ONLY the translation.\n\n\"The connection pool was exhausted because a recent deploy reduced its\nsize. Roll back the deploy and the errors should stop within a few\nminutes.\"\n", "category": "translation", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nTranslate into French. Reply with ONLY the translation.\n\n\"The connection pool was exhausted because a recent deploy reduced its\nsize. Roll back the deploy and the errors should stop within a few\nminutes.\"\n", "category": "translation", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nTranslate into French. Reply with ONLY the translation.\n\n\"The connection pool was exhausted because a recent deploy reduced its\nsize. Roll back the deploy and the errors should stop within a few\nminutes.\"\n", "category": "translation", "noise_level": "long"}
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{"text": "Translate into Spanish, preserving the hedging and the informal tone.\nReply with ONLY the translation.\n\n\"I'm not totally sure this is the right call, but I'd lean towards\nshipping it and seeing what breaks — we can always roll it back.\"\n", "category": "translation", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nTranslate into Spanish, preserving the hedging and the informal tone.\nReply with ONLY the translation.\n\n\"I'm not totally sure this is the right call, but I'd lean towards\nshipping it and seeing what breaks — we can always roll it back.\"\n", "category": "translation", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nTranslate into Spanish, preserving the hedging and the informal tone.\nReply with ONLY the translation.\n\n\"I'm not totally sure this is the right call, but I'd lean towards\nshipping it and seeing what breaks — we can always roll it back.\"\n", "category": "translation", "noise_level": "long"}
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{"text": "Explain to a non-programmer, in under 100 words, why a program can be\ncorrect and still be too slow to use.\n", "category": "general_chat", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nExplain to a non-programmer, in under 100 words, why a program can be\ncorrect and still be too slow to use.\n", "category": "general_chat", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nExplain to a non-programmer, in under 100 words, why a program can be\ncorrect and still be too slow to use.\n", "category": "general_chat", "noise_level": "long"}
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{"text": "A colleague says \"we should rewrite the whole service in Rust, it'll be\nfaster.\" Reply in under 80 words, taking the suggestion seriously but\nidentifying what you would want to know first.\n", "category": "general_chat", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nA colleague says \"we should rewrite the whole service in Rust, it'll be\nfaster.\" Reply in under 80 words, taking the suggestion seriously but\nidentifying what you would want to know first.\n", "category": "general_chat", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nA colleague says \"we should rewrite the whole service in Rust, it'll be\nfaster.\" Reply in under 80 words, taking the suggestion seriously but\nidentifying what you would want to know first.\n", "category": "general_chat", "noise_level": "long"}
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{"text": "You are reviewing a refactor. BEFORE: def make_multipliers(factors):\n out = []\n for f in factors:\n out.append(lambda x: x * f)\n return out\nPROPOSED AFTER: def make_multipliers(factors):\n out = []\n for f in factors:\n out.append(lambda x, f=f: x * f)\n return out\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nYou are reviewing a refactor. BEFORE: def make_multipliers(factors):\n out = []\n for f in factors:\n out.append(lambda x: x * f)\n return out\nPROPOSED AFTER: def make_multipliers(factors):\n out = []\n for f in factors:\n out.append(lambda x, f=f: x * f)\n return out\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nYou are reviewing a refactor. BEFORE: def make_multipliers(factors):\n out = []\n for f in factors:\n out.append(lambda x: x * f)\n return out\nPROPOSED AFTER: def make_multipliers(factors):\n out = []\n for f in factors:\n out.append(lambda x, f=f: x * f)\n return out\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "long"}
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{"text": "You are reviewing a refactor. BEFORE: def make_multipliers(factors):\n out = []\n for f in factors:\n out.append(lambda x, f=f: x * f)\n return out\nPROPOSED AFTER: def make_multipliers(factors):\n out = []\n for f in factors:\n out.append(lambda x: x * f)\n return out\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nYou are reviewing a refactor. BEFORE: def make_multipliers(factors):\n out = []\n for f in factors:\n out.append(lambda x, f=f: x * f)\n return out\nPROPOSED AFTER: def make_multipliers(factors):\n out = []\n for f in factors:\n out.append(lambda x: x * f)\n return out\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nYou are reviewing a refactor. BEFORE: def make_multipliers(factors):\n out = []\n for f in factors:\n out.append(lambda x, f=f: x * f)\n return out\nPROPOSED AFTER: def make_multipliers(factors):\n out = []\n for f in factors:\n out.append(lambda x: x * f)\n return out\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "long"}
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{"text": "You are reviewing a refactor. BEFORE: def bsearch(items, target):\n lo, hi = 0, len(items)\n while lo < hi:\n mid = (lo + hi) // 2\n if items[mid] == target:\n return mid\n elif items[mid] < target:\n lo = mid\n else:\n hi = mid\n return -1\nPROPOSED AFTER: def bsearch(items, target):\n lo, hi = 0, len(items)\n while lo < hi:\n mid = (lo + hi) // 2\n if items[mid] == target:\n return mid\n elif items[mid] < target:\n lo = mid + 1\n else:\n hi = mid\n return -1\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nYou are reviewing a refactor. BEFORE: def bsearch(items, target):\n lo, hi = 0, len(items)\n while lo < hi:\n mid = (lo + hi) // 2\n if items[mid] == target:\n return mid\n elif items[mid] < target:\n lo = mid\n else:\n hi = mid\n return -1\nPROPOSED AFTER: def bsearch(items, target):\n lo, hi = 0, len(items)\n while lo < hi:\n mid = (lo + hi) // 2\n if items[mid] == target:\n return mid\n elif items[mid] < target:\n lo = mid + 1\n else:\n hi = mid\n return -1\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nYou are reviewing a refactor. BEFORE: def bsearch(items, target):\n lo, hi = 0, len(items)\n while lo < hi:\n mid = (lo + hi) // 2\n if items[mid] == target:\n return mid\n elif items[mid] < target:\n lo = mid\n else:\n hi = mid\n return -1\nPROPOSED AFTER: def bsearch(items, target):\n lo, hi = 0, len(items)\n while lo < hi:\n mid = (lo + hi) // 2\n if items[mid] == target:\n return mid\n elif items[mid] < target:\n lo = mid + 1\n else:\n hi = mid\n return -1\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "long"}
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{"text": "You are reviewing a refactor. BEFORE: def bsearch(items, target):\n lo, hi = 0, len(items)\n while lo < hi:\n mid = (lo + hi) // 2\n if items[mid] == target:\n return mid\n elif items[mid] < target:\n lo = mid + 1\n else:\n hi = mid\n return -1\nPROPOSED AFTER: def bsearch(items, target):\n lo, hi = 0, len(items)\n while lo < hi:\n mid = (lo + hi) // 2\n if items[mid] == target:\n return mid\n elif items[mid] < target:\n lo = mid\n else:\n hi = mid\n return -1\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nYou are reviewing a refactor. BEFORE: def bsearch(items, target):\n lo, hi = 0, len(items)\n while lo < hi:\n mid = (lo + hi) // 2\n if items[mid] == target:\n return mid\n elif items[mid] < target:\n lo = mid + 1\n else:\n hi = mid\n return -1\nPROPOSED AFTER: def bsearch(items, target):\n lo, hi = 0, len(items)\n while lo < hi:\n mid = (lo + hi) // 2\n if items[mid] == target:\n return mid\n elif items[mid] < target:\n lo = mid\n else:\n hi = mid\n return -1\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nYou are reviewing a refactor. BEFORE: def bsearch(items, target):\n lo, hi = 0, len(items)\n while lo < hi:\n mid = (lo + hi) // 2\n if items[mid] == target:\n return mid\n elif items[mid] < target:\n lo = mid + 1\n else:\n hi = mid\n return -1\nPROPOSED AFTER: def bsearch(items, target):\n lo, hi = 0, len(items)\n while lo < hi:\n mid = (lo + hi) // 2\n if items[mid] == target:\n return mid\n elif items[mid] < target:\n lo = mid\n else:\n hi = mid\n return -1\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "long"}
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{"text": "You are reviewing a refactor. BEFORE: def apply_settings(overrides):\n result = {}\n result[\"retries\"] = overrides.get(\"retries\", 3)\n result[\"timeout\"] = overrides.get(\"timeout\", 30)\n result[\"verbose\"] = overrides.get(\"verbose\", False)\n return result\nPROPOSED AFTER: def apply_settings(overrides):\n result = {}\n if \"retries\" in overrides:\n result[\"retries\"] = overrides[\"retries\"]\n else:\n result[\"retries\"] = 3\n if \"timeout\" in overrides:\n result[\"timeout\"] = overrides[\"timeout\"]\n else:\n result[\"timeout\"] = 30\n if \"verbose\" in overrides:\n result[\"verbose\"] = overrides[\"verbose\"]\n else:\n result[\"verbose\"] = False\n return result\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nYou are reviewing a refactor. BEFORE: def apply_settings(overrides):\n result = {}\n result[\"retries\"] = overrides.get(\"retries\", 3)\n result[\"timeout\"] = overrides.get(\"timeout\", 30)\n result[\"verbose\"] = overrides.get(\"verbose\", False)\n return result\nPROPOSED AFTER: def apply_settings(overrides):\n result = {}\n if \"retries\" in overrides:\n result[\"retries\"] = overrides[\"retries\"]\n else:\n result[\"retries\"] = 3\n if \"timeout\" in overrides:\n result[\"timeout\"] = overrides[\"timeout\"]\n else:\n result[\"timeout\"] = 30\n if \"verbose\" in overrides:\n result[\"verbose\"] = overrides[\"verbose\"]\n else:\n result[\"verbose\"] = False\n return result\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nYou are reviewing a refactor. BEFORE: def apply_settings(overrides):\n result = {}\n result[\"retries\"] = overrides.get(\"retries\", 3)\n result[\"timeout\"] = overrides.get(\"timeout\", 30)\n result[\"verbose\"] = overrides.get(\"verbose\", False)\n return result\nPROPOSED AFTER: def apply_settings(overrides):\n result = {}\n if \"retries\" in overrides:\n result[\"retries\"] = overrides[\"retries\"]\n else:\n result[\"retries\"] = 3\n if \"timeout\" in overrides:\n result[\"timeout\"] = overrides[\"timeout\"]\n else:\n result[\"timeout\"] = 30\n if \"verbose\" in overrides:\n result[\"verbose\"] = overrides[\"verbose\"]\n else:\n result[\"verbose\"] = False\n return result\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "long"}
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{"text": "You are reviewing a refactor. BEFORE: def apply_settings(overrides):\n result = {}\n if \"retries\" in overrides:\n result[\"retries\"] = overrides[\"retries\"]\n else:\n result[\"retries\"] = 3\n if \"timeout\" in overrides:\n result[\"timeout\"] = overrides[\"timeout\"]\n else:\n result[\"timeout\"] = 30\n if \"verbose\" in overrides:\n result[\"verbose\"] = overrides[\"verbose\"]\n else:\n result[\"verbose\"] = False\n return result\nPROPOSED AFTER: def apply_settings(overrides):\n result = {}\n result[\"retries\"] = overrides.get(\"retries\", 3)\n result[\"timeout\"] = overrides.get(\"timeout\", 30)\n result[\"verbose\"] = overrides.get(\"verbose\", False)\n return result\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nYou are reviewing a refactor. BEFORE: def apply_settings(overrides):\n result = {}\n if \"retries\" in overrides:\n result[\"retries\"] = overrides[\"retries\"]\n else:\n result[\"retries\"] = 3\n if \"timeout\" in overrides:\n result[\"timeout\"] = overrides[\"timeout\"]\n else:\n result[\"timeout\"] = 30\n if \"verbose\" in overrides:\n result[\"verbose\"] = overrides[\"verbose\"]\n else:\n result[\"verbose\"] = False\n return result\nPROPOSED AFTER: def apply_settings(overrides):\n result = {}\n result[\"retries\"] = overrides.get(\"retries\", 3)\n result[\"timeout\"] = overrides.get(\"timeout\", 30)\n result[\"verbose\"] = overrides.get(\"verbose\", False)\n return result\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nYou are reviewing a refactor. BEFORE: def apply_settings(overrides):\n result = {}\n if \"retries\" in overrides:\n result[\"retries\"] = overrides[\"retries\"]\n else:\n result[\"retries\"] = 3\n if \"timeout\" in overrides:\n result[\"timeout\"] = overrides[\"timeout\"]\n else:\n result[\"timeout\"] = 30\n if \"verbose\" in overrides:\n result[\"verbose\"] = overrides[\"verbose\"]\n else:\n result[\"verbose\"] = False\n return result\nPROPOSED AFTER: def apply_settings(overrides):\n result = {}\n result[\"retries\"] = overrides.get(\"retries\", 3)\n result[\"timeout\"] = overrides.get(\"timeout\", 30)\n result[\"verbose\"] = overrides.get(\"verbose\", False)\n return result\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "long"}
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{"text": "You are reviewing a refactor. BEFORE: import re\ndef extract_tags(text):\n return re.findall(r\"<(.+)>\", text)\nPROPOSED AFTER: import re\ndef extract_tags(text):\n return re.findall(r\"<([^<>]+)>\", text)\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nYou are reviewing a refactor. BEFORE: import re\ndef extract_tags(text):\n return re.findall(r\"<(.+)>\", text)\nPROPOSED AFTER: import re\ndef extract_tags(text):\n return re.findall(r\"<([^<>]+)>\", text)\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nYou are reviewing a refactor. BEFORE: import re\ndef extract_tags(text):\n return re.findall(r\"<(.+)>\", text)\nPROPOSED AFTER: import re\ndef extract_tags(text):\n return re.findall(r\"<([^<>]+)>\", text)\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "long"}
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{"text": "You are reviewing a refactor. BEFORE: import re\ndef extract_tags(text):\n return re.findall(r\"<([^<>]+)>\", text)\nPROPOSED AFTER: import re\ndef extract_tags(text):\n return re.findall(r\"<(.+)>\", text)\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nYou are reviewing a refactor. BEFORE: import re\ndef extract_tags(text):\n return re.findall(r\"<([^<>]+)>\", text)\nPROPOSED AFTER: import re\ndef extract_tags(text):\n return re.findall(r\"<(.+)>\", text)\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nYou are reviewing a refactor. BEFORE: import re\ndef extract_tags(text):\n return re.findall(r\"<([^<>]+)>\", text)\nPROPOSED AFTER: import re\ndef extract_tags(text):\n return re.findall(r\"<(.+)>\", text)\nDoes the AFTER version introduce a bug that the BEFORE version does not\nhave? Reply with only YES or NO.\n", "category": "diff_checking", "noise_level": "long"}
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{"text": "Summarise the most important non-obvious gotcha in this code:\n\niteration:\n retries: 0\n backoff: 2.0\ncache:\n enabled: true\n max_size: 128\n\n(config/config.yaml)\n\nWhat does the retries: 0 value signal, and what happens to cache when\nits subkeys are missing? How does a function that uses key-in-d checks\ndiffer from one that uses d-get-default in each case?\n", "category": "file_summarization", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nSummarise the most important non-obvious gotcha in this code:\n\niteration:\n retries: 0\n backoff: 2.0\ncache:\n enabled: true\n max_size: 128\n\n(config/config.yaml)\n\nWhat does the retries: 0 value signal, and what happens to cache when\nits subkeys are missing? How does a function that uses key-in-d checks\ndiffer from one that uses d-get-default in each case?\n", "category": "file_summarization", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nSummarise the most important non-obvious gotcha in this code:\n\niteration:\n retries: 0\n backoff: 2.0\ncache:\n enabled: true\n max_size: 128\n\n(config/config.yaml)\n\nWhat does the retries: 0 value signal, and what happens to cache when\nits subkeys are missing? How does a function that uses key-in-d checks\ndiffer from one that uses d-get-default in each case?\n", "category": "file_summarization", "noise_level": "long"}
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{"text": "Summarise the most important non-obvious gotcha in this code:\n\ndef dedupe(items, key=None):\n seen = set()\n out = []\n for item in items:\n k = key(item) if key else item\n if k in seen:\n continue\n seen.add(k)\n out.append(item)\n return out\n\n(from tests/test_task_set.py)\n\nWhat two guarantees does this function provide beyond what set() offers?\n", "category": "file_summarization", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nSummarise the most important non-obvious gotcha in this code:\n\ndef dedupe(items, key=None):\n seen = set()\n out = []\n for item in items:\n k = key(item) if key else item\n if k in seen:\n continue\n seen.add(k)\n out.append(item)\n return out\n\n(from tests/test_task_set.py)\n\nWhat two guarantees does this function provide beyond what set() offers?\n", "category": "file_summarization", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nSummarise the most important non-obvious gotcha in this code:\n\ndef dedupe(items, key=None):\n seen = set()\n out = []\n for item in items:\n k = key(item) if key else item\n if k in seen:\n continue\n seen.add(k)\n out.append(item)\n return out\n\n(from tests/test_task_set.py)\n\nWhat two guarantees does this function provide beyond what set() offers?\n", "category": "file_summarization", "noise_level": "long"}
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{"text": "Summarise the most important non-obvious gotcha in this code:\n\ndef retry(fn, attempts=3, backoff=2.0):\n delay = 1.0\n for i in range(attempts):\n try:\n return fn()\n except Exception:\n if i == attempts - 1:\n raise\n time.sleep(delay)\n delay *= backoff\n\n(from src/eval_proficiency.py)\n\nWhat happens to the exception when all attempts are exhausted? How does\nthe delay between retries change?\n", "category": "file_summarization", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nSummarise the most important non-obvious gotcha in this code:\n\ndef retry(fn, attempts=3, backoff=2.0):\n delay = 1.0\n for i in range(attempts):\n try:\n return fn()\n except Exception:\n if i == attempts - 1:\n raise\n time.sleep(delay)\n delay *= backoff\n\n(from src/eval_proficiency.py)\n\nWhat happens to the exception when all attempts are exhausted? How does\nthe delay between retries change?\n", "category": "file_summarization", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nSummarise the most important non-obvious gotcha in this code:\n\ndef retry(fn, attempts=3, backoff=2.0):\n delay = 1.0\n for i in range(attempts):\n try:\n return fn()\n except Exception:\n if i == attempts - 1:\n raise\n time.sleep(delay)\n delay *= backoff\n\n(from src/eval_proficiency.py)\n\nWhat happens to the exception when all attempts are exhausted? How does\nthe delay between retries change?\n", "category": "file_summarization", "noise_level": "long"}
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{"text": "Summarise the most important non-obvious gotcha in this code:\n\ngen = (x * 2 for x in range(5))\nfor _ in range(3):\n for v in gen:\n print(v)\nprint(list(gen))\n\n(from dispatcher.py)\n\nWhat is printed by the inner loop, and what does list(gen) produce\nafterwards?\n", "category": "file_summarization", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nSummarise the most important non-obvious gotcha in this code:\n\ngen = (x * 2 for x in range(5))\nfor _ in range(3):\n for v in gen:\n print(v)\nprint(list(gen))\n\n(from dispatcher.py)\n\nWhat is printed by the inner loop, and what does list(gen) produce\nafterwards?\n", "category": "file_summarization", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nSummarise the most important non-obvious gotcha in this code:\n\ngen = (x * 2 for x in range(5))\nfor _ in range(3):\n for v in gen:\n print(v)\nprint(list(gen))\n\n(from dispatcher.py)\n\nWhat is printed by the inner loop, and what does list(gen) produce\nafterwards?\n", "category": "file_summarization", "noise_level": "long"}
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{"text": "Summarise the most important non-obvious gotcha in this code:\n\nimport datetime\nstart = datetime.datetime(2026, 3, 8, 2, 0)\nend = start + datetime.timedelta(hours=48)\n# start is timezone-naive\n\n(from a schedule module in the router codebase)\n\nWhat is wrong with performing arithmetic on a naive datetime across a\nclock-change boundary?\n", "category": "file_summarization", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nSummarise the most important non-obvious gotcha in this code:\n\nimport datetime\nstart = datetime.datetime(2026, 3, 8, 2, 0)\nend = start + datetime.timedelta(hours=48)\n# start is timezone-naive\n\n(from a schedule module in the router codebase)\n\nWhat is wrong with performing arithmetic on a naive datetime across a\nclock-change boundary?\n", "category": "file_summarization", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nSummarise the most important non-obvious gotcha in this code:\n\nimport datetime\nstart = datetime.datetime(2026, 3, 8, 2, 0)\nend = start + datetime.timedelta(hours=48)\n# start is timezone-naive\n\n(from a schedule module in the router codebase)\n\nWhat is wrong with performing arithmetic on a naive datetime across a\nclock-change boundary?\n", "category": "file_summarization", "noise_level": "long"}
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{"text": "Summarise the most important non-obvious gotcha in this code:\n\nimport sqlite3\nconn = sqlite3.connect(\"mydb.db\")\ncursor = conn.cursor()\ncursor.execute(\n \"INSERT INTO children (parent_id, name) VALUES (1, 'Alice')\")\n\n(from a script in the router codebase)\n\nAssuming a children table has a foreign-key constraint to a parents\ntable, will this insert fail if parent_id=1 doesn't exist? Why or why\nnot?\n", "category": "file_summarization", "noise_level": "clean"}
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{"text": "Tool result: read task input, 4 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n```\n\nTool result: no errors, 4 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 4.</system-reminder>\n\nSummarise the most important non-obvious gotcha in this code:\n\nimport sqlite3\nconn = sqlite3.connect(\"mydb.db\")\ncursor = conn.cursor()\ncursor.execute(\n \"INSERT INTO children (parent_id, name) VALUES (1, 'Alice')\")\n\n(from a script in the router codebase)\n\nAssuming a children table has a foreign-key constraint to a parents\ntable, will this insert fail if parent_id=1 doesn't exist? Why or why\nnot?\n", "category": "file_summarization", "noise_level": "short"}
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{"text": "Tool result: read task input, 40 lines\n\n```python\ndef placeholder(n):\n # deterministic noise snippet 0\n \"\"\"Return the ordinal for reproducible noise wrapping.\"\"\"\n return n + 0\n _step_1 = placeholder(1)\n _step_2 = placeholder(2)\n _step_3 = placeholder(3)\n _step_4 = placeholder(4)\n _step_5 = placeholder(5)\n _step_6 = placeholder(6)\n _step_7 = placeholder(7)\n _step_8 = placeholder(8)\n _step_9 = placeholder(9)\n _step_10 = placeholder(10)\n _step_11 = placeholder(11)\n _step_12 = placeholder(12)\n _step_13 = placeholder(13)\n _step_14 = placeholder(14)\n _step_15 = placeholder(15)\n _step_16 = placeholder(16)\n _step_17 = placeholder(17)\n _step_18 = placeholder(18)\n _step_19 = placeholder(19)\n _step_20 = placeholder(20)\n _step_21 = placeholder(21)\n _step_22 = placeholder(22)\n _step_23 = placeholder(23)\n _step_24 = placeholder(24)\n _step_25 = placeholder(25)\n _step_26 = placeholder(26)\n _step_27 = placeholder(27)\n _step_28 = placeholder(28)\n _step_29 = placeholder(29)\n _step_30 = placeholder(30)\n _step_31 = placeholder(31)\n _step_32 = placeholder(32)\n _step_33 = placeholder(33)\n _step_34 = placeholder(34)\n _step_35 = placeholder(35)\n _step_36 = placeholder(36)\n```\n\nTool result: no errors, 40 statements evaluated\n\n<system-reminder>Session metadata: continuation turn, tool history depth 40.</system-reminder>\n\nSummarise the most important non-obvious gotcha in this code:\n\nimport sqlite3\nconn = sqlite3.connect(\"mydb.db\")\ncursor = conn.cursor()\ncursor.execute(\n \"INSERT INTO children (parent_id, name) VALUES (1, 'Alice')\")\n\n(from a script in the router codebase)\n\nAssuming a children table has a foreign-key constraint to a parents\ntable, will this insert fail if parent_id=1 doesn't exist? Why or why\nnot?\n", "category": "file_summarization", "noise_level": "long"}
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