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Nvidia generative ai platform review

Skill Raishin/vanguard-frontier-agentic/skills/nvidia/nvidia-generative-ai-platform-review

Use this skill when reviewing NVIDIA generative-AI platforms — NeMo training and customization pipelines, NIM inference microservices, NeMo Guardrails, model card and weights provenance, evaluation/eval-harness posture, and tenant data isolation. Trigger when the user asks whether NIM containers are correctly verified before deployment, whether NeMo Guardrails are configured, or whether the deployment meets NCA-GENL, NCA-GENM, or NCP-GENL expectations.From its SKILL.md

Install
npx -y skills add Raishin/vanguard-frontier-agentic --skill nvidia-generative-ai-platform-review

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 20 stars20 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

2.6 KB, 429 tokens by cl100k_base, as published. Nobody here has run it

NVIDIA Generative AI Platform Review

Purpose

Review NVIDIA generative-AI platform posture against the NCA-GENL, NCA-GENM, and NCP-GENL bodies of knowledge: NeMo training/customization pipelines, NIM inference microservice deployment, NeMo Guardrails configuration, model card and weights provenance, evaluation harness coverage, and tenant data isolation in multi-tenant inference.

Lean operating rules

  • Prefer live evidence (cosign verify nvcr.io/nim/..., NIM /v1/health/ready, NeMo Guardrails config files, model card YAML, eval harness reports) when the active client exposes it; otherwise fall back to NVIDIA NeMo / NIM documentation and sanitized configuration.
  • Separate confirmed facts from inference. If NIM image signature verification, guardrails state, or eval coverage was not directly queried, say so.
  • Treat NIM container pulled from nvcr.io without cosign verify against NVIDIA's published key/identity as a high finding — image trust is unverified.
  • Treat absence of model card or weights provenance attestation for production-served models as a high finding — lineage cannot be reconstructed.
  • Treat NeMo Guardrails absent or bypassable for an externally exposed LLM endpoint as a critical finding for any regulated workload.
  • Treat evaluation harness covering only loss/perplexity but no safety, jailbreak, or hallucination evaluation as a high finding for customer-facing LLMs.
  • Treat training data with no documented PII handling, no opt-out path, and no retention bound as a critical finding for regulated tenants.
  • Treat NIM inference shared across tenants without per-tenant request scoping as a high finding — cross-tenant context leakage path.

Response minimum

Return, at minimum:

  • the scoped target (NeMo pipeline, NIM microservice, model class) and evidence level,
  • NIM image signature verification posture,
  • guardrails posture,
  • model card / weights provenance posture,
  • eval harness coverage,
  • tenant isolation posture,
  • safe next actions and assumptions or blockers.

What ships with it: 1 file

1.4 KB alongside SKILL.md

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