NVIDIA-NeMo
Review Skills published by NVIDIA-NeMo, their source repositories, maintenance signals, and identity status.
- Skills
- 11
- Repository stars
- 56
- Identity status
- Source-linked
Provenance
Source and identity
- Profile type
- Creator
- Canonical name
- NVIDIA-NeMo
- Public sources
- 1
- License context
- Apache-2.0
Source entries
Agent Skills from NVIDIA-NeMo
Repository stars and maintenance signals provide context, but do not automatically become an individual Skill's quality score.
NVIDIA-NeMo/nemo-platform
add-studio-feature-flag
Adds a NeMo Studio (Vite) feature flag end-to-end: typed definition, runtime injection mapping, FastAPI build env markers, and optional Helm config. Use when the user asks for a new feature flag, VITE_FF_ variable, studio.feature_flags setting, toggling UI behind a flag, or preview/boolean flags for Studio.
NVIDIA-NeMo/nemo-platform
anonymizer
Use when the user wants to detect and replace, hash, redact, annotate, or rewrite PII (names, emails, phone numbers, locations, ...) in a CSV or Parquet dataset using the NeMo Anonymizer plugin.
NVIDIA-NeMo/nemo-platform
deploy-sandbox
Deploys an already-built NAT agent as a policy-governed OpenShell sandbox on a local NeMo Platform, so the same agent image gets Landlock filesystem isolation and a pure default-deny network policy (the sandbox reaches nothing on the network directly; its model calls are brokered by the OpenShell gateway through the inference.local route) for free. Covers the proven wire-inference.local -> package -> DeploymentConfig -> deploy (executor openshell-local) -> wait -> query -> zero-egress proof -> c
NVIDIA-NeMo/nemo-platform
inference
End-to-end reference for inference on the NeMo platform — registering LLM backends as ModelProviders, wiring them to VirtualModels with Switchyard middleware (random routing, translate) and `nemo-guardrails` content-safety rails, and hitting them via the nemo CLI. Use when the task involves registering inference providers, discovering served models, creating VirtualModels, configuring switchyard middleware, layering guardrails alongside translate (correct middleware ordering for OpenAI/Anthropic
NVIDIA-NeMo/nemo-platform
nemo-agent-config
Author and validate Platform-managed NeMo Agents agent.yaml files using the nemo-agents-spec-v1 format. Use when the user wants to create, edit, validate, or adapt an agent.yaml file, choose a supported harness, add instructions, skills, MCP servers, tools, environment, or telemetry.
NVIDIA-NeMo/nemo-platform
nemo-build-agent
End-to-end NeMo Platform agent implementation from an approved agent spec. Registers and deploys the agent, generates evaluation data, runs evaluation, and signs off. Use for full spec-to-deployed-agent work, including builds from an existing legacy NAT workflow.
NVIDIA-NeMo/nemo-platform
nemo-customizer
Fine-tune models on NeMo Platform with `automodel`, `unsloth`, or `rl` (all `submit`-only): HF dataset conversion, filesets, model entities, and job JSON (hyperparameters, batch, schedule, optimizer) + job polling. `automodel`/`unsloth` run SFT/LoRA as Docker GPU jobs; `rl` runs DPO (preference optimization) on a Ray cluster (Kubernetes). Use for train, fine-tune, customize, SFT, LoRA, DPO, preference optimization, learning rate, epochs, or nemo customization.
NVIDIA-NeMo/nemo-platform
nemo-explore
Captures what a NeMo Platform agent should do before any code or YAML. Explores the user's codebase and docs first, fills in every spec field it can infer, then asks the user only for the gaps. Output feeds nemo-spec. Use over generic brainstorming for any NeMo Platform agent design conversation.
NVIDIA-NeMo/nemo-platform
nemo-guardrails
NeMo guardrails CLI reference for creating guardrail configs and applying them to chat completions through an IGW VirtualModel. Covers config CRUD, the standalone `/checks` endpoint for verifying a config, and the `nemo-guardrails` inference middleware plugin attached via VirtualModel MiddlewareCalls. Use when the task involves guardrail configurations, content safety, input/output rails, or `nemo guardrail` / `nemo inference virtual-models` CLI commands for guardrailing inference.
NVIDIA-NeMo/nemo-platform
nemo-model-selection
Recommends an LLM for a NeMo Platform agent based on what the agent actually has to do, explained in plain English before any benchmark name appears. Use when the user is choosing a model for a new agent, assessing a model they already selected, or deciding what belongs in AGENT-SPEC.md or Platform agent.yaml. Invoked by nemo-explore at the model question; also runs standalone when the user starts mid-flow.
NVIDIA-NeMo/nemo-platform
nemo-try-agent
Invokes an existing NeMo Platform agent through a named deployment or directly from a local agent YAML config. Use to try, test, or query an agent and inspect its response.
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