Agent skill · nvidia
paidf-auto-labeling
Use when a user needs to get started with PAIDF Auto-Labeling, plan a scenario, run or debug a shipped cookbook, author prompts or cookbooks, migrate a pipeline, or configure a stage. Confirm critical inputs (data path, output path, endpoints) and ask when any are missing. This is a router: read the matching reference instead of inventing a workflow.
What it needs
About 3k tokens when loaded.
What this skill does
PAIDF Auto-Labeling Use this skill when a user wants to kick off PAIDF Auto-Labeling on their own data, domain, or use case, or when the request matches a shipped cookbook, stage, authoring, or migration task. This is a router: sequence the specialized references instead of duplicating their detail. Routing (Read First) Request looks like Read --- --- New user, clean checkout, first validated run, "how do I get started" This file, then the matching reference below Choose annotation targets / stage subset for a domain references/scenario-planning.md Create, review, or adapt a cookbook references/cookbook-authoring.md Write or adapt VLM/LLM prompts or question banks references/prompt-authoring.md Migrate an existing annotation repo into this one references/pipeline-migration.md Run the video data augmentation cookbook references/video-data-augmentation.md Run or choose an EPAS / PAS cookbook references/event-and-person-attribute-search.md Run event-verification reasoning references/event-verification-reasoning.md Debug an already-integrated workflow references/workflow-runner-debugging.md Implement or review a new stage or Dockerized service references/workflow-stage-integration.md Configure or debug one production stage The matching file under references/stages/ Stage references: super-resolution, detection-and-tracking, captioning, visual-qa, reasoning, person-attribute-search, grounding-2d, referring-expressions, training-export. Instructions 1. Confirm the critical run inputs with the user before doing anything else, and ask a concise question whenever one is missing or ambiguous - never guess or silently invent a default. At minimum confirm: input data path, output path, VLM/LLM endpoint URLs and model names, model cache path, GPU ids, and (for reasoning-capable models) the maxtokens cap. Restate the confirmed values back to the user before the first execution. 2. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nvidia/paidf-auto-labeling