{
  "checker": {
    "details": {
      "argv": [
        "<host-path>",
        "build",
        "--strict",
        "--config-file",
        "mkdocs.yml"
      ],
      "kind": "cli",
      "needs_browser": false,
      "needs_credentials": false,
      "returncode": 0,
      "scope": "product operation",
      "stderr": "\n[31m \u2502  \u26a0  Warning from the Material for MkDocs team[0m\n[31m \u2502[0m\n[31m \u2502[0m  MkDocs 2.0, the underlying framework of Material for MkDocs,\n[31m \u2502[0m  will introduce backward-incompatible changes, including:\n[31m \u2502[0m\n[31m \u2502  \u00d7 [0mAll plugins will stop working \u2013 the plugin system has been removed\n[31m \u2502  \u00d7 [0mAll theme overrides will break \u2013 the theming system has been rewritten\n[31m \u2502  \u00d7 [0mNo migration path exists \u2013 existing projects cannot be upgraded\n[31m \u2502  \u00d7 [0mClosed contribution model \u2013 community members can't report bugs\n[31m \u2502  \u00d7 [0mCurrently unlicensed \u2013 unsuitable for production use\n[31m \u2502[0m\n[excerpt truncated]",
      "stdout": "",
      "working": true
    },
    "status": "PASS"
  },
  "deviations": [
    "The README's tensoracle[convert] extra was installed as pip install torch from the PyTorch CPU index plus the base package, not the default CUDA torch wheel, to save space. The product is the same.",
    "Plain pip install of mkdocs/mkdocstrings failed in strict build (mkdocstrings Highlight.md TypeError). Used the CI path instead: uv 0.12.5 with the committed uv.lock, which resolved correctly.",
    "The GPU-dependent README operations (open_engine, build_serialized_engine, execution) were not run: no NVIDIA GPU in the guest."
  ],
  "main_blocker": null,
  "operation": "Documented CI docs build (.github/workflows/pages.yml: uv sync --locked --only-group docs; uv run --no-sync mkdocs build --strict --config-file ../mkdocs.yml), run from the repo root with the locked docs environment. Also verified the README's CPU-only converter command: python -m tensoracle.convert model.pth model.safetensors (torch 2.14.1+cpu), which produced a safetensors file read back as state_dict.bias=[0.5,-1.0]. The converter prints nothing on success, so it was not used as the probe.",
  "operation_scope": "Covers packaging/install, the docs build, and the CPU-only .pth->safetensors conversion. NOT verified: engine build, reuse, and execution. These need an NVIDIA GPU, driver, and CUDA context; this VM has no GPU (nvidia-smi not found, no /dev/nvidia*). Test suites were not run, per instructions.",
  "outcome": "working",
  "steps": [
    "apt-get install python3-venv",
    "python3 -m venv <host-path>; pip install . in python/ (tensoracle 0.0-from-vcs, tensorrt-cu13 11.4.0.106 installed; import OK)",
    "pip install torch --index-url https://download.pytorch.org/whl/cpu (for the [convert] extra; torch 2.14.1+cpu)",
    "python -m tensoracle.convert model.pth model.safetensors (rc=0, verified by reading back)",
    "uv 0.12.5 via pip; uv sync --locked --only-group docs with UV_PROJECT_ENVIRONMENT=<host-path>",
    "mkdocs build --strict --config-file mkdocs.yml (rc=0; output in site/, removed after verification so the checker gets a fresh path)"
  ],
  "stuck_step": null,
  "suggested_fix": "Run on a Linux x86_64 host or VM with an sm86/sm89/sm120 NVIDIA GPU, driver, and TensorRT 11 (tensorrt-cu13), then run the README 'Define and build a standard graph' example with open_engine to cover the GPU path."
}