Mortdecai
7f806e0b92
Round 2 tested the hypothesis that 26B's silent-stop was about write_file argument size. Result: refuted. - Patch-mode (apply_patch instead of write_file): 26B fails identically at iter 6. Tool-arg size is not the cause. - Truncation sweep on tool responses reveals the real trigger: cap at 800 or 1200 chars → 26B PASSES (1200-cap is 8.4s, fastest of any run). Cap at 1600, 2000, or unlimited → 26B silent-stops with eval=4. Revised understanding: 26B silent-stops when cumulative tool-response context crosses a shape threshold around 1200-1600 chars per response. Not a tool-arg bug, not a raw code-gen bug — 26B emits correct code fine in both one-shot and short-context settings. Production CLI agents (openclaw, open code, aider) typically truncate tool responses by default, so this failure may not surface in them. Custom harnesses should cap ≤1200 chars per tool response when targeting the 26B MoE. Updates GOTCHAS (rewritten entry with the truncation sweep table), SYNTHESIS model-selection row, CORPUS_cli_coding_agent.md pointer, docs/reference/bakeoff-2026-04-18.md with full Round 2 methodology and data. Adds harness_patch.py (apply_patch edit tool), harness_patch_truncated.py (env-configurable TOOL_RESULT_CAP), all 7 run logs, and a .secrets.baseline for detect-secrets false positives on JSON timestamps.
262 lines
16 KiB
JSON
262 lines
16 KiB
JSON
{
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"model": "gemma4:26b",
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"edit_tool": "apply_patch",
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"tool_result_cap": 800,
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"workdir": "/home/claude/bin/gemma4-research/scripts/bakeoff/runs_patch/gemma4-26b-truncated/work",
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"started_at": 1776533701.8915875,
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"turns": [
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{
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"iteration": 1,
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"elapsed_s": 0.55,
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"content": "",
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"tool_calls": [
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{
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"name": "run_bash",
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"arguments": {
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"command": "ls -R"
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},
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"result": "exit=0\n--- stdout ---\n.:\ncalc\nREADME.md\ntests\n\n./calc:\n__init__.py\n__pycache__\nstats.py\n\n./calc/__pycache__:\n__init__.cpython-313.pyc\nstats.cpython-313.pyc\n\n./tests:\n__pycache__\ntest_stats.py\n\n./tests/__pycache__:\ntest_stats.cpython-313-pytest-9.0.2.pyc\n\n--- stderr ---\n"
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}
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],
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"prompt_eval_count": 458,
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"eval_count": 21
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},
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{
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"iteration": 2,
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"elapsed_s": 0.61,
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"content": "",
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"tool_calls": [
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{
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"name": "read_file",
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"arguments": {
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"path": "README.md"
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},
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"result": "# Bakeoff Task\n\nA tiny Python package (`calc/`) with a statistics module. Run `pytest` from this\ndirectory \u2014 two tests currently fail because `median` returns the upper-middle\nelement instead of averaging the two middle elements on even-length inputs.\n\nYour job: make all tests pass. Do not disable or modify the tests.\n\nAllowed tools:\n- `read_file(path)` \u2014 read a file (relative to this directory)\n- `write_file(path, content)` \u2014 overwrite a file (relative to this directory)\n- `run_bash(command)` \u2014 run a shell command (cwd is this directory)\n\nWhen all tests pass, reply with a short summary of the fix and stop calling tools.\n"
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}
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],
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"prompt_eval_count": 599,
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"eval_count": 21
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},
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{
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"iteration": 3,
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"elapsed_s": 0.64,
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"content": "",
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"tool_calls": [
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{
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"name": "run_bash",
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"arguments": {
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"command": "pytest"
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},
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"result": "exit=2\n--- stdout ---\n============================= test session starts ==============================\nplatform linux -- Python 3.13.5, pytest-9.0.2, pluggy-1.6.0\nrootdir: /home/claude/bin/gemma4-research/scripts/bakeoff/runs_patch/gemma4-26b-truncated/work\nplugins: asyncio-1.3.0, anyio-4.12.1\nasyncio: mode=Mode.STRICT, debug=False, asyncio_default_fixture_loop_scope=None, asyncio_default_test_loop_scope=function\ncollected 0 items / 1 error\n\n==================================== ERRORS ====================================\n_____________________ ERROR collecting tests/test_stats.py _____________________\nImportError while importing test module '/home/claude/bin/gemma4-research/scripts/bakeoff/runs_patch/gemma4-26b-truncated/work/tests/test_stats.py'.\nHint: make sure your test modules/packages "
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}
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],
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"prompt_eval_count": 780,
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"eval_count": 19
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},
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{
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"iteration": 4,
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"elapsed_s": 0.76,
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"content": "",
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"tool_calls": [
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{
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"name": "read_file",
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"arguments": {
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"path": "tests/test_stats.py"
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},
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"result": "from calc.stats import mean, median, mode, variance\n\n\ndef test_mean_basic():\n assert mean([1, 2, 3, 4, 5]) == 3.0\n\n\ndef test_median_odd():\n assert median([1, 2, 3]) == 2\n\n\ndef test_median_even():\n assert median([1, 2, 3, 4]) == 2.5\n\n\ndef test_median_unsorted():\n assert median([3, 1, 4, 1, 5, 9, 2, 6]) == 3.5\n\n\ndef test_median_floats():\n assert median([1.0, 2.0, 3.0, 4.0]) == 2.5\n\n\ndef test_mode_basic():\n assert mode([1, 2, 2, 3]) == 2\n\n\ndef test_variance_basic():\n # sample variance (n-1) of [1, 2, 3, 4, 5] is 10/4 = 2.5\n assert variance([1, 2, 3, 4, 5]) == 2.5\n"
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}
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],
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"prompt_eval_count": 1040,
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"eval_count": 25
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},
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{
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"iteration": 5,
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"elapsed_s": 0.83,
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"content": "",
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"tool_calls": [
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{
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"name": "run_bash",
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"arguments": {
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"command": "export PYTHONPATH=$PYTHONPATH:. && pytest"
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},
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"result": "exit=1\n--- stdout ---\n============================= test session starts ==============================\nplatform linux -- Python 3.13.5, pytest-9.0.2, pluggy-1.6.0\nrootdir: /home/claude/bin/gemma4-research/scripts/bakeoff/runs_patch/gemma4-26b-truncated/work\nplugins: asyncio-1.3.0, anyio-4.12.1\nasyncio: mode=Mode.STRICT, debug=False, asyncio_default_fixture_loop_scope=None, asyncio_default_test_loop_scope=function\ncollected 7 items\n\ntests/test_stats.py ..FFF.. [100%]\n\n=================================== FAILURES ===================================\n_______________________________ test_median_even _______________________________\n\n def test_median_even():\n> assert median([1, 2, 3, 4]) == 2.5\nE assert 3 == 2.5\nE + where 3 = med"
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}
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],
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"prompt_eval_count": 1343,
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"eval_count": 26
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},
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{
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"iteration": 6,
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"elapsed_s": 0.74,
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"content": "",
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"tool_calls": [
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{
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"name": "read_file",
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"arguments": {
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"path": "calc/stats.py"
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},
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"result": "\"\"\"Basic statistics helpers.\"\"\"\n\n\ndef mean(numbers):\n \"\"\"Arithmetic mean of a non-empty list.\"\"\"\n return sum(numbers) / len(numbers)\n\n\ndef median(numbers):\n \"\"\"Return the median of a list of numbers.\"\"\"\n s = sorted(numbers)\n n = len(s)\n return s[n // 2]\n\n\ndef mode(numbers):\n \"\"\"Return the most common value. Ties broken by first occurrence.\"\"\"\n counts = {}\n for x in numbers:\n counts[x] = counts.get(x, 0) + 1\n best = None\n best_count = -1\n for x in numbers:\n if counts[x] > best_count:\n best = x\n best_count = counts[x]\n return best\n\n\ndef variance(numbers):\n \"\"\"Sample variance (divides by n-1).\"\"\"\n if len(numbers) < 2:\n raise ValueError(\"variance requires at least 2 values\")\n m = mean(numbers)\n return"
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}
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],
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"prompt_eval_count": 1611,
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"eval_count": 23
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},
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{
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"iteration": 7,
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"elapsed_s": 0.76,
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"content": "",
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"tool_calls": [
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{
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"name": "read_file",
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"arguments": {
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"path": "calc/stats.py"
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},
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"result": "\"\"\"Basic statistics helpers.\"\"\"\n\n\ndef mean(numbers):\n \"\"\"Arithmetic mean of a non-empty list.\"\"\"\n return sum(numbers) / len(numbers)\n\n\ndef median(numbers):\n \"\"\"Return the median of a list of numbers.\"\"\"\n s = sorted(numbers)\n n = len(s)\n return s[n // 2]\n\n\ndef mode(numbers):\n \"\"\"Return the most common value. Ties broken by first occurrence.\"\"\"\n counts = {}\n for x in numbers:\n counts[x] = counts.get(x, 0) + 1\n best = None\n best_count = -1\n for x in numbers:\n if counts[x] > best_count:\n best = x\n best_count = counts[x]\n return best\n\n\ndef variance(numbers):\n \"\"\"Sample variance (divides by n-1).\"\"\"\n if len(numbers) < 2:\n raise ValueError(\"variance requires at least 2 values\")\n m = mean(numbers)\n return"
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}
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],
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"prompt_eval_count": 1876,
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"eval_count": 23
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},
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{
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"iteration": 8,
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"elapsed_s": 0.76,
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"content": "",
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"tool_calls": [
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{
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"name": "run_bash",
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"arguments": {
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"command": "cat calc/stats.py"
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},
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"result": "exit=0\n--- stdout ---\n\"\"\"Basic statistics helpers.\"\"\"\n\n\ndef mean(numbers):\n \"\"\"Arithmetic mean of a non-empty list.\"\"\"\n return sum(numbers) / len(numbers)\n\n\ndef median(numbers):\n \"\"\"Return the median of a list of numbers.\"\"\"\n s = sorted(numbers)\n n = len(s)\n return s[n // 2]\n\n\ndef mode(numbers):\n \"\"\"Return the most common value. Ties broken by first occurrence.\"\"\"\n counts = {}\n for x in numbers:\n counts[x] = counts.get(x, 0) + 1\n best = None\n best_count = -1\n for x in numbers:\n if counts[x] > best_count:\n best = x\n best_count = counts[x]\n return best\n\n\ndef variance(numbers):\n \"\"\"Sample variance (divides by n-1).\"\"\"\n if len(numbers) < 2:\n raise ValueError(\"variance requires at least 2 values\")\n m = me"
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}
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],
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"prompt_eval_count": 2141,
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"eval_count": 24
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},
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{
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"iteration": 9,
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"elapsed_s": 0.78,
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"content": "",
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"tool_calls": [
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{
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"name": "run_bash",
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"arguments": {
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"command": "cat calc/stats.py"
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},
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"result": "exit=0\n--- stdout ---\n\"\"\"Basic statistics helpers.\"\"\"\n\n\ndef mean(numbers):\n \"\"\"Arithmetic mean of a non-empty list.\"\"\"\n return sum(numbers) / len(numbers)\n\n\ndef median(numbers):\n \"\"\"Return the median of a list of numbers.\"\"\"\n s = sorted(numbers)\n n = len(s)\n return s[n // 2]\n\n\ndef mode(numbers):\n \"\"\"Return the most common value. Ties broken by first occurrence.\"\"\"\n counts = {}\n for x in numbers:\n counts[x] = counts.get(x, 0) + 1\n best = None\n best_count = -1\n for x in numbers:\n if counts[x] > best_count:\n best = x\n best_count = counts[x]\n return best\n\n\ndef variance(numbers):\n \"\"\"Sample variance (divides by n-1).\"\"\"\n if len(numbers) < 2:\n raise ValueError(\"variance requires at least 2 values\")\n m = me"
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}
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],
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"prompt_eval_count": 2409,
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"eval_count": 24
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},
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{
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"iteration": 10,
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"elapsed_s": 0.79,
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"content": "",
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"tool_calls": [
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{
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"name": "run_bash",
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"arguments": {
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"command": "cat calc/stats.py"
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},
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"result": "exit=0\n--- stdout ---\n\"\"\"Basic statistics helpers.\"\"\"\n\n\ndef mean(numbers):\n \"\"\"Arithmetic mean of a non-empty list.\"\"\"\n return sum(numbers) / len(numbers)\n\n\ndef median(numbers):\n \"\"\"Return the median of a list of numbers.\"\"\"\n s = sorted(numbers)\n n = len(s)\n return s[n // 2]\n\n\ndef mode(numbers):\n \"\"\"Return the most common value. Ties broken by first occurrence.\"\"\"\n counts = {}\n for x in numbers:\n counts[x] = counts.get(x, 0) + 1\n best = None\n best_count = -1\n for x in numbers:\n if counts[x] > best_count:\n best = x\n best_count = counts[x]\n return best\n\n\ndef variance(numbers):\n \"\"\"Sample variance (divides by n-1).\"\"\"\n if len(numbers) < 2:\n raise ValueError(\"variance requires at least 2 values\")\n m = me"
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}
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],
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"prompt_eval_count": 2677,
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"eval_count": 24
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},
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{
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"iteration": 11,
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"elapsed_s": 0.78,
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"content": "",
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"tool_calls": [
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{
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"name": "run_bash",
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"arguments": {
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"command": "cat calc/stats.py"
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},
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"result": "exit=0\n--- stdout ---\n\"\"\"Basic statistics helpers.\"\"\"\n\n\ndef mean(numbers):\n \"\"\"Arithmetic mean of a non-empty list.\"\"\"\n return sum(numbers) / len(numbers)\n\n\ndef median(numbers):\n \"\"\"Return the median of a list of numbers.\"\"\"\n s = sorted(numbers)\n n = len(s)\n return s[n // 2]\n\n\ndef mode(numbers):\n \"\"\"Return the most common value. Ties broken by first occurrence.\"\"\"\n counts = {}\n for x in numbers:\n counts[x] = counts.get(x, 0) + 1\n best = None\n best_count = -1\n for x in numbers:\n if counts[x] > best_count:\n best = x\n best_count = counts[x]\n return best\n\n\ndef variance(numbers):\n \"\"\"Sample variance (divides by n-1).\"\"\"\n if len(numbers) < 2:\n raise ValueError(\"variance requires at least 2 values\")\n m = me"
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}
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],
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"prompt_eval_count": 2945,
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"eval_count": 24
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},
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{
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"iteration": 12,
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"elapsed_s": 0.8,
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"content": "",
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"tool_calls": [
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{
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"name": "run_bash",
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"arguments": {
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"command": "ls -l calc/stats.py"
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},
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"result": "exit=0\n--- stdout ---\n-rw-rw-r-- 1 claude claude 857 Apr 18 13:19 calc/stats.py\n\n--- stderr ---\n"
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}
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],
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"prompt_eval_count": 3213,
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"eval_count": 26
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},
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{
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"iteration": 13,
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"elapsed_s": 0.63,
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"content": "",
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"tool_calls": [
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{
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"name": "read_file",
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"arguments": {
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"path": "calc/stats.py"
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},
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"result": "\"\"\"Basic statistics helpers.\"\"\"\n\n\ndef mean(numbers):\n \"\"\"Arithmetic mean of a non-empty list.\"\"\"\n return sum(numbers) / len(numbers)\n\n\ndef median(numbers):\n \"\"\"Return the median of a list of numbers.\"\"\"\n s = sorted(numbers)\n n = len(s)\n return s[n // 2]\n\n\ndef mode(numbers):\n \"\"\"Return the most common value. Ties broken by first occurrence.\"\"\"\n counts = {}\n for x in numbers:\n counts[x] = counts.get(x, 0) + 1\n best = None\n best_count = -1\n for x in numbers:\n if counts[x] > best_count:\n best = x\n best_count = counts[x]\n return best\n\n\ndef variance(numbers):\n \"\"\"Sample variance (divides by n-1).\"\"\"\n if len(numbers) < 2:\n raise ValueError(\"variance requires at least 2 values\")\n m = mean(numbers)\n return"
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}
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],
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"prompt_eval_count": 3288,
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"eval_count": 23
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},
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{
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"iteration": 14,
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"elapsed_s": 2.44,
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"content": "",
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"tool_calls": [
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{
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"name": "apply_patch",
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"arguments": {
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"new_text": "def median(numbers):\n \"\"\"Return the median of a list of numbers.\"\"\"\n s = sorted(numbers)\n n = len(s)\n if n % 2 == 1:\n return s[n // 2]\n else:\n return (s[n // 2 - 1] + s[n // 2]) / 2",
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"old_text": "def median(numbers):\n \"\"\"Return the median of a list of numbers.\"\"\"\n s = sorted(numbers)\n n = len(s)\n return s[n // 2]",
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"path": "calc/stats.py"
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},
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"result": "patched calc/stats.py (replaced 130 chars with 210 chars)"
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}
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],
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"prompt_eval_count": 3553,
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"eval_count": 163
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},
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{
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"iteration": 15,
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"elapsed_s": 0.74,
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"content": "",
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"tool_calls": [
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{
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"name": "run_bash",
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"arguments": {
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"command": "cat calc/stats.py"
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},
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"result": "exit=0\n--- stdout ---\n\"\"\"Basic statistics helpers.\"\"\"\n\n\ndef mean(numbers):\n \"\"\"Arithmetic mean of a non-empty list.\"\"\"\n return sum(numbers) / len(numbers)\n\n\ndef median(numbers):\n \"\"\"Return the median of a list of numbers.\"\"\"\n s = sorted(numbers)\n n = len(s)\n if n % 2 == 1:\n return s[n // 2]\n else:\n return (s[n // 2 - 1] + s[n // 2]) / 2\n\n\ndef mode(numbers):\n \"\"\"Return the most common value. Ties broken by first occurrence.\"\"\"\n counts = {}\n for x in numbers:\n counts[x] = counts.get(x, 0) + 1\n best = None\n best_count = -1\n for x in numbers:\n if counts[x] > best_count:\n best = x\n best_count = counts[x]\n return best\n\n\ndef variance(numbers):\n \"\"\"Sample variance (divides by n-1).\"\"\"\n if len(numbers)"
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}
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],
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"prompt_eval_count": 3741,
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"eval_count": 24
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}
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],
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"final": {
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"halt_reason": "iteration_cap",
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"tests_pass": true,
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"iterations_used": 15,
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"tool_call_counts": {
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"read_file": 5,
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"apply_patch": 1,
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"run_bash": 9
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},
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"wall_clock_s": 13.35
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}
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} |