tao-run-deft-aoi
Skill: tao-run-deft-aoi
When to Use This Skill
Use this skill when the user wants an agent to run the full DEFT AOI improvement loop for an NVIDIA TAO VisualChangeNet / ChangeNet PCB inspection model: baseline evaluation, RCA, ingestion of pre-generated synthetic defects, data mining, retraining, and deployment gating until a KPI target is met. AnomalyGen is not run inline in this EA variant — the customer pre-generates NG/OK pairs out-of-band and places them under <workspace>/augmentation/anomalygen/.
- "Run the DEFT loop"
- "Fine-tune until FAR < 0.1% at recall=100%"
- "Improve my AOI ChangeNet model using RCA and synthetic defects"
- "Iterate training until false accept rate meets the target"
Do not use this skill for a single standalone TAO training run, one-off inference, generic anomaly generation, or RCA-only analysis. Use the relevant agent directly when the user asks for only that step.
Base Model
The loop operates on NVIDIA TAO Visual ChangeNet classify with the NVIDIA C-RADIOv2-B backbone, fine-tuned end-to-end. The architecture is defined in specs/baseline_spec.yaml — that file is the source of truth. All pretrained weights come from HuggingFace (HF_TOKEN required); NGC_API_KEY_* only gate container pulls. ChangeNet backbone resolution + the staged-file/HF-URL fallback for model.backbone.pretrained_backbone_path are owned by references/visual-changenet.md. SigLIP for k-NN mining is owned by references/tao-mine-aoi-images.md. No AnomalyGen-side checkpoints are required in this EA variant — pre-generated synthetic pairs are ingested directly from <workspace>/augmentation/anomalygen/{reconstructed_image,original_image}/; see Pipeline step 3 in references/pipeline.md.