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    {
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      "status": "PASS",
      "details": {
        "working": true,
        "argv": [
          "convert",
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          "yolo2xlabel",
          "--mode",
          "detect",
          "--images",
          "--labels",
          "--output",
          "--classes"
        ],
        "kind": "cli",
        "returncode": 0,
        "stdout": "\u2713 Converted 1 files to XLABEL format: <host-path>",
        "stderr": "\nConverting YOLO detect to XLABEL:   0%|          | 0/1 [00:00<?, ?it/s]\nConverting YOLO detect to XLABEL: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 1/1 [00:00<00:00, 710.78it/s]",
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  "source": "https://github.com/CVHub520/X-AnyLabeling",
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  "steps": [
    "cd <host-path> && ls -la && cat README.md | head -300",
    "python3 --version; which pip3 node npm uv conda 2>&1; cat /etc/os-release | head -2; echo \"proxy=$HTTP_PROXY $HTTPS_PROXY\"; echo CDP=$CDP_URL",
    "cd <host-path> && sed -n 1,200p docs/en/get_started.md; echo ----; sed -n 1,200p docs/en/cli.md",
    "cd <host-path> && (python3 -m venv venv-cpu 2>&1 || (sudo apt-get update -qq && sudo apt-get install -y -qq python3-venv >/dev/null 2>&1 && python3 -m venv venv-cpu)) && ./venv-cpu/bin/pip install -q -U uv 2>&1 | tail -3; ./venv-cpu/bin/uv --version",
    "cd <host-path> && rm -rf venv-cpu && sudo apt-get update -qq >/dev/null 2>&1; sudo apt-get install -y -qq python3.12-venv >/tmp/apt.log 2>&1; echo apt=$?; python3 -m venv venv-cpu && ls venv-cpu/bin | head -20",
    "cd <host-path> && export NODE_USE_ENV_PROXY=1 && <host-path> install -q -U uv 2>&1 | tail -3; <host-path> pip install --python <host-path> -e \".[cpu]\" > /tmp/install.log 2>&1; echo rc=$?; tail -15 /tmp/install.log",
    "cd <host-path> && sed -n '/### 3.3/,/## 4/p' docs/en/cli.md | head -120; grep -ril \"mcp\" --include=*.md . | head; ls <host-path> | grep -i xany",
    "cd <host-path> && ls tests; find . -path ./node_modules -prune -o \\( -iname \"classes.txt\" -o -iname \"*.txt\" -path \"*yolo*\" \\) -print | head -20; find . -type d -iname \"*yolo*\" | head -20",
    "cd <host-path> && rm -rf probe_data probe_out && mkdir -p probe_data/images probe_data/labels && <host-path> -I -c \"\nimport cv2, numpy as np\ncv2.imwrite('<host-path>', np.zeros((100,100,3),np.uint8))\n\" && echo \"0 0.5 0.5 0.2 0.2\" > probe_data/labels/a.txt && echo object > probe_data/classes.txt && cd <host-path> && <host-path> convert --task yolo2xlabel --mode detect --images <host-path> --labels <host-path> --output <host-path> --classes <host-path>; echo rc=$?; ls <host-path>; cat <host-path> 2>/dev/null | head -40",
    "sudo apt-get install -y -qq libgl1 libegl1 libxkbcommon0 libdbus-1-3 libfontconfig1 libglib2.0-0 libxcb-cursor0 >/tmp/apt2.log 2>&1; echo apt=$?; cd <host-path> && <host-path> checks 2>&1 | tail -25; echo rc=$?",
    "cd <host-path> && <host-path> convert --task yolo2xlabel --mode detect --images <host-path> --labels <host-path> --output <host-path> --classes <host-path>; echo rc=$?; ls <host-path>; cat <host-path> 2>/dev/null | head -40",
    "cd <host-path> && mkdir -p .coldpass && cat > .coldpass/probe.json <<'EOF'\n{\n  \"kind\": \"cli\",\n  \"argv\": [\"<host-path>\", \"convert\", \"--task\", \"yolo2xlabel\", \"--mode\", \"detect\", \"--images\", \"<host-path>\", \"--labels\", \"<host-path>\", \"--output\", \"<host-path>\", \"--classes\", \"<host-path>\"],\n  \"cwd\": \"<host-path>\",\n  \"env\": {}\n}\nEOF\ncat > .coldpass/report.json <<'EOF'\n{\n  \"outcome\": \"working\",\n  \"operation\": \"xanylabeling convert --task yolo2xlabel --mode detect on a 1-image YOLO sample (created in <host-path>); verified output a.json contains rectangle label 'object' at (40,40)-(60,60), matching the YOLO box 0.5 0.5 0.2 0.2 on a 100x100 image\",\n  \"operation_scope\": \"CPU install only, CLI conversion. GUI not launched. No browser needed. Repo ships no sample YOLO dataset, so input was synthesized for the test. MCP start/tools/list not applicable (product is not an MCP server).\",\n  \"steps\": [\n    \"python3 -m venv <host-path> (after apt install python3.12-venv)\",\n    \"pip install -U uv (in venv)\",\n    \"cd <host-path> && uv pip install --python <host-path> -e \\\".[cpu]\\\" (from docs/en/get_started.md section 1.2.2 Git Clone, step b)\",\n    \"xanylabeling checks (docs/en/get_started.md; succeeded, App Version 4.2.0)\",\n    \"xanylabeling convert --task yolo2xlabel --mode detect ... (docs/en/cli.md section 3.3; succeeded, 'Converted 1 files')\"\n  ],\n  \"deviations\": [\n    \"README/get_started 'xanylabeling checks' first failed with ImportError: libGL.so.1 not found (PyQt6 import). Ran: sudo apt-get install -y libgl1 libegl1 libxkbcommon0 libdbus-1-3 libfontconfig1 libglib2.0-0 libxcb-cursor0. Then checks succeeded.\",\n    \"python3 -m venv failed: ensurepip not available. Ran: sudo apt-get install -y python3.12-venv, then recreated venv.\",\n    \"Input dataset synthesized (1 PNG via cv2 + YOLO label + classes.txt) because repo has no sample labeled data for the convert example.\"\n  ],\n  \"stuck_step\": null,\n  \"main_blocker\": null,\n  \"suggested_fix\": null\n}\nEOF\n<env-var>=<host-path> python3 -I <host-path> --validate; echo rc=$?",
    "rm -rf <host-path> && ls -la <host-path> 2>&1 | head -1; <env-var>=<host-path> python3 -I <host-path> --validate; echo rc=$?"
  ],
  "platform_conflicts": null,
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  "repo": "CVHub520/X-AnyLabeling",
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  "reasoning": "low",
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  "profile": {
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    "reasoning": "low"
  },
  "date": "2026-10-18T16:00:09.535533+00:00",
  "kind": "repo",
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    "memory_mib": 4096,
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  },
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  "run_id": "CVHub520--X-AnyLabeling-claude-haiku-5-5-1792339015153167026",
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  "model": "claude-haiku-5-5",
  "what_it_did": "xanylabeling convert --task yolo2xlabel --mode detect on a 1-image YOLO sample (created in <host-path>); verified output a.json contains rectangle label 'object' at (40,40)-(60,60), matching the YOLO box 0.5 0.5 0.2 0.2 on a 100x100 image",
  "sandbox_source": null,
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  "test_version": "readme-03aea4c41d53955e3723c330e9927d2a9df627f6642624cc0078a97c73a53c8a",
  "recovery": {
    "source": "legacy-oct16-18",
    "original_run_id": "CVHub520--X-AnyLabeling-claude-haiku-5-5-1792339015153167026",
    "historical": true,
    "ledger_sha256": "c5e6a833c182c1e2aecf69d0bd0020aec63c65d98f3e933e4b32232340312736"
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  "transcript_url": "/transcripts/CVHub520--X-AnyLabeling-claude-haiku-5-5-1792339015153167026.txt",
  "report_url": "/reports/CVHub520--X-AnyLabeling-claude-haiku-5-5-1792339015153167026.json"
}