Multi-file
analysisOfficial
Official Provider SkillView repo
Root cause analysis for SOP monitoring pipeline failures. Analyzes end-to-end evaluation logs, DDM temporal segmentation, VLM action recognition, training data, and fine-tuning configs to identify failure patterns and produce an evidence-driven RCA report with actionable improvement recommendations.
Files14 files
SKILL.md606 lines
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Skill details
Versionv1.0.0
AuthorNVIDIA
Categoryanalysis
Skill IDNVIDIA/sop-monitoring-blueprints/agentic/sop-agentic-ft/plugins/sop-rca-plugin/skills/sop-rca
Files14 files
Related skills
Deepstream SopUse this skill when building, deploying, evaluating, debugging, or measuring latency for the DeepStream SOP Inference Microservice — a GPU-accelerated FastAPI service that detects whether operators perform assembly-line steps in order via event boundary detection (GEBD) plus VLM classification. Trigger even if the user does not name it: verify operator step sequence, detect missing or out-of-order SOP steps, score factory/work-cell video for procedure compliance, run VLM-based SOP checking on inSop BuildOrchestrate the end-to-end SOP pipeline, including preflight prerequisite checks, verifying models and downloading assets, generating the DeepStream SOP microservice with RTSP output, evaluating the microservice, and building, deploying, and testing the VSS SOP blueprint. Use when asked to run the full SOP pipeline, set up the SOP pipeline from scratch, execute preflight checks, verify models, download assets, generate the SOP microservice, evaluate the microservice, build the VSS blueprint, depSop By Action EvalUse when running by-action VLM evaluation (per-action-clip inference + accuracy metrics) against the BP evaluation-ms HTTP API. Invoked as /sop-by-action-eval <inputs.yaml> [natural language parameter overrides]Sop Cr FinetuningFine-tune Cosmos-Reason2 (CR2) VLM for SOP monitoring. Use when you need to launch and monitor a VLM training run with a given dataset ID.Sop Data AugmentationUse when the user wants to run data augmentation on an annotated dataset, configure augmentation parameters, check augmentation status, or understand what each QA augmentation type does (BCQ, MCQ, GQA, DMCQ, DSQA, ENQA)Sop Ddm FinetuningFine-tune DDM-Net temporal boundary detector for SOP monitoring. Use when you need to launch and monitor a DDM-Net training run with a given dataset ID.