Agent skill · nvidia
paidf-curation-and-retrieval
Use when operating PAIDF Curation and Retrieval or NVIDIA Cosmos Curator pipelines (split, filter, caption, embed, dedup, shard, image annotate) or PAIDF Data Mining nearest-neighbor matching on Curator embeddings. Activate for Make or CLI pipeline config, GPU run preflight, FFmpeg sidecar, SAM3 keys, or Curator-to-TAO handoff. Do not use for generic ETL, vector-database RAG, model training, orchestration, or embeddings outside Cosmos Curator and PAIDF Data Mining.
What it needs
About 7k tokens when loaded.
What this skill does
PAIDF Curator Operator Skill GPU-accelerated video and image curation via NVIDIA Cosmos Curator inside Physical AI Data Factory — Curation and Retrieval (paidf-curation-and-retrieval). This skill is a short Curator index. Embedding handoff boundaries live in data-mining.md and curation-retrieval-workflow.md; mining execution is make help and the repository cookbooks. Video: split, dedup, shard. Image: annotate (load → filter → embed → caption → write). Handoff: Curator IV2 or CE1 parquet that downstream mining can consume. See data-mining.md and curation-retrieval-workflow.md. Purpose Turn raw video and image collections into curated, training-ready datasets. This skill configures and runs cosmos-curator pipelines (clip splitting, filtering, captioning, embeddings, SAM3 event verification, dedup, WebDataset sharding, image annotate) and supports KPI-driven, distribution-aware, and restrictive curation. Instructions 1. Classify the request as advisory, config, run, or TAO handoff. Do not mix those routes. 2. For config work, complete the mandatory pre-flight below before writing YAML. 3. For an explicit run, load running-pipelines.md, validate the config, obtain credentials only through approved injection, then execute after authorization. 4. For a TAO handoff, validate Curator output and the declared embedding family using data-mining.md before mining. 5. Return the Output Format below. Never print secret values. Examples Advisory: "How much SHM should I set?" → read running-pipelines.md and report guidance. Do not run Docker. Config with no KPI: complete the calibration interview in calibration-config.md, then emit YAML. Run: after sample clips are staged, make run-pipeline with the traffic split-minimal cookbook recipe only after preflight and user authorization. FFmpeg missing in the container: install the host sidecar (make ffmpeg-install) per ffmpeg-sidecar.md. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nvidia/paidf-curation-and-retrieval