Agent skill · NVIDIA
tao-run-deft-aoi
Run the full DEFT AOI improvement loop for NVIDIA TAO VisualChangeNet / ChangeNet PCB inspection models: baseline evaluate, RCA, Cosmos AnomalyGen / AMP synthetic defects, k-NN mining, retraining, and deployment gating until FAR / recall KPI targets are met. Use for prompts like "run the DEFT loop", "fine-tune until FAR below 0.1% at recall=100%", or "improve my AOI ChangeNet model with RCA and synthetic defects"; do not use for standalone TAO training, one-off inference, generic anomaly generation, or RCA-only analysis.
What it needs
About 8k tokens when loaded.
What this skill does
Skill: tao-run-deft-aoi Standalone install? If this session was not initialized by the TAO skill bank plugin, run the tao-setup skill first (host preflight, credentials, cross-skill discovery). 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, synthetic defect generation, data mining, retraining, and deployment gating until a KPI target is met. "Run the DEFT loop" "Fine-tune until FAR below 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/baselinespec.yaml — that file is the source of truth. All pretrained weights come from HuggingFace (HFTOKEN required); NGCKEY only gates container pulls. ChangeNet backbone resolution + the staged-file/HF-URL fallback for model.backbone.pretrainedbackbonepath are owned by references/visual-changenet.md. SigLIP for k-NN mining is owned by references/tao-mine-aoi-images.md. AnomalyGen-side checkpoints (Cosmos-Predict2, T5, NVDINOV2, C-RADIO-V3, DINOv2-large, SAM2, Qwen3-VL — ~22 GB for 2B-only, ~140 GB with 14B + T5-11b) live under <workspace>/augmentation/anomalygen/basecheckpoints/; the paidf-anomalygen container auto-downloads them on first use. The PCB reference dataset under <workspace>/augmentation/anomalygen/datasets/<project>/ is also auto-fetchable. See references/paidf-anomalygen.md. Train AutoML Policy DEFT AOI owns the iterative data-improvement loop, retraining cadence, and KPI checkpoint selection. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills NVIDIA/tao-run-deft-aoi