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name: auto-labeling-models description: "Operate AnyLabeling model-backed auto-labeling: catalogs, custom configs, registry extensions, YOLO detectors, SAM-family segmentation, prompts, caches, and diagnostics." disable-model-invocation: true metadata: disco-role: operating license: GPL 3.0

Auto-labeling models

Use this sub-skill when the task concerns AnyLabeling's model-backed auto-labeling system rather than manual drawing, label-file export, packaging, or release automation.

Load this when

• Inspecting the built-in auto-labeling model catalog or a user-provided custom model config.yaml.
• Diagnosing model selection, download/cache state, unknown model types, missing model files, or Hugging Face/network download failures.
• Working with ModelRegistry, ModelManager, threaded model loading/inference, or registry import side effects.
• Configuring or troubleshooting YOLOv5/YOLOv8 rectangle detection models.
• Configuring or troubleshooting Segment Anything, MobileSAM, SAM2, SAM3, SAM3 text prompts, prompt marks, mask post-processing, output modes, or the macOS CoreML SAM2 branch.

Do not use this for

• Manual annotation editing, shape list behavior, label-file schemas, dataset export/import, or result insertion details after AutoLabelingResult reaches the UI. Route those to annotation-ui-and-data.
• PyPI packaging, CPU/GPU wheel selection, CI, publishing, or standalone executable builds. Route those to packaging-release.

Reference map

• Model catalog and configs: built-in catalog behavior, custom config contracts, registry keys, download/cache semantics, and extension checklist.
• Auto-labeling workflows: UI-to-manager workflow, prompt modes, YOLO outputs, SAM-family variants, SAM3 text prompts, caches, and optional real-inference playbook.
• Troubleshooting: unknown model types, invalid configs, missing files, downloads, BOM YAML, SAM3 text mode, thresholds, mask dtype, variant detection, CUDA/CoreML confusion.

Bundled safe diagnostics

The scripts are read-only and perform no downloads:

• scripts/inspect_model_catalog.py summarizes a catalog file or an installed package catalog, optionally merging already-present cache config.yaml files.
• scripts/check_custom_model_config.py validates a custom model config, resolves referenced local/cache files, and optionally inspects a present ONNX decoder to catch SAM2/SAM3/SAM1 variant mismatches.

Run each script with --help before use.