executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
runtime-configurationInstall, inspect, and configure TotalSegmentator runtime dependencies, devices, weights, licenses, offline caches, and usage statistics.
Independent GitHub snapshot · Automated classification · Original documentation governs
Use this sub-skill when an agent needs to make TotalSegmentator importable, choose a backend device, inspect local runtime state, pre-stage model weights, configure offline/license behavior, or disable usage telemetry. It owns setup and diagnostics, not segmentation command construction.
pip install TotalSegmentator; verify with TotalSegmentator --version, totalseg_info --json, or the bundled checker.python scripts/check_totalseg_runtime.py --task total --device cpu --json for a safe smoke check that imports metadata/registry/config helpers, checks PyTorch visibility, and never downloads weights or runs models.references/install-and-backends.md for Python/PyTorch requirements, optional dependencies, and cpu/gpu/gpu:N/mps selection.references/configuration.md for TOTALSEG_HOME_DIR, TOTALSEG_WEIGHTS_PATH, config.json, weights, offline staging, licenses, and usage-stat settings.references/troubleshooting.md when imports, CUDA/MPS, offline weights, licenses, preview rendering, optional dependencies, or config isolation fail.--roi_subset names, route to ../capability-discovery/SKILL.md.TotalSegmentator -i ... -o ... commands or python_api.totalsegmentator(...) calls, route to ../segmentation-workflows/SKILL.md.../outputs-and-statistics/SKILL.md.crop_to_body, route to ../dicom-and-formats/SKILL.md.../auxiliary-analysis/SKILL.md.../advanced-training/SKILL.md.totalseg_info and totalsegmentator.registry for capability decisions; they are safe, fast, and do not load models.totalseg_download_weights when the user expects network and storage use.