Matlab Use Visual Inspection
matlab/matlab-agentic-toolkit
Build machine vision inspection systems with MATLAB Visual Inspection Toolbox.
Reference desk for Nemotron 3 Nano / Llama-Nemotron Nano 3 — architecture, training data, recipes, evaluation, quantization, deployment.
$ npx skills add NVIDIA-NeMo/Nemotron --skill nemotron-nano3 -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install NVIDIA-NeMo/Nemotron nemotron-nano3 --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/NVIDIA-NeMo/Nemotron.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/nemotron-nano3 .claude/skills/nemotron-nano3 && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "nemotron-nano3" agent skill from https://github.com/NVIDIA-NeMo/Nemotron/tree/main/skills/nemotron-nano3 into .claude/skills/nemotron-nano3/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nemotron-nano3", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/NVIDIA-NeMo/Nemotron/tree/main/skills/nemotron-nano3Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add NVIDIA-NeMo/Nemotron --skill nemotron-nano3 -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install NVIDIA-NeMo/Nemotron nemotron-nano3 --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA-NeMo/Nemotron.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/nemotron-nano3 .agents/skills/nemotron-nano3 && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "nemotron-nano3" agent skill from https://github.com/NVIDIA-NeMo/Nemotron/tree/main/skills/nemotron-nano3 into .agents/skills/nemotron-nano3/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nemotron-nano3", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NVIDIA-NeMo/Nemotron --skill nemotron-nano3 -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install NVIDIA-NeMo/Nemotron nemotron-nano3 --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA-NeMo/Nemotron.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/nemotron-nano3 .cursor/skills/nemotron-nano3 && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "nemotron-nano3" agent skill from https://github.com/NVIDIA-NeMo/Nemotron/tree/main/skills/nemotron-nano3 into .cursor/skills/nemotron-nano3/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nemotron-nano3", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/NVIDIA-NeMo/Nemotron.git --path skills/nemotron-nano3--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add NVIDIA-NeMo/Nemotron --skill nemotron-nano3 -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install NVIDIA-NeMo/Nemotron nemotron-nano3 --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA-NeMo/Nemotron.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/nemotron-nano3 .gemini/skills/nemotron-nano3 && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "nemotron-nano3" agent skill from https://github.com/NVIDIA-NeMo/Nemotron/tree/main/skills/nemotron-nano3 into .gemini/skills/nemotron-nano3/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nemotron-nano3", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install NVIDIA-NeMo/Nemotron nemotron-nano3Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add NVIDIA-NeMo/Nemotron --skill nemotron-nano3 -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/NVIDIA-NeMo/Nemotron.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/nemotron-nano3 .github/skills/nemotron-nano3 && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "nemotron-nano3" agent skill from https://github.com/NVIDIA-NeMo/Nemotron/tree/main/skills/nemotron-nano3 into .github/skills/nemotron-nano3/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nemotron-nano3", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NVIDIA-NeMo/Nemotron --skill nemotron-nano3 -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install NVIDIA-NeMo/Nemotron nemotron-nano3 --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA-NeMo/Nemotron.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/nemotron-nano3 .opencode/skills/nemotron-nano3 && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "nemotron-nano3" agent skill from https://github.com/NVIDIA-NeMo/Nemotron/tree/main/skills/nemotron-nano3 into .opencode/skills/nemotron-nano3/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nemotron-nano3", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
nemotron-nano3Reference desk for Nemotron 3 Nano / Llama-Nemotron Nano 3 — architecture, training data, recipes, evaluation, quantization, deployment.
Nemotron Nano3 is an agent skill from NVIDIA-NeMo/Nemotron. Reference desk for Nemotron 3 Nano / Llama-Nemotron Nano 3 — architecture, training data, recipes, evaluation, quantization, deployment. Use when the user asks facts about the model rather than building a pipeline.
Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 20 other files (for example `INDEX.md`, `context/quick-reference.md` and `model-card.md`).
It sits in AI & LLM Engineering, covering LLM inference and serving and Deployment. It works with NVIDIA AI Platform. The repository describes itself as: Developer Asset Hub for NVIDIA Nemotron — A one-stop resource for training recipes, usage cookbooks, datasets, and full end-to-end reference examples to build with Nemotron models. The licence is Apache-2.0.
3 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit ca8c409. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Nemotron Nano3 loads about 1.9k tokens when it runs. Until then it costs about 57 tokens; SKILL.md has 836 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from NVIDIA-NeMo/Nemotron at commit ca8c409, republished under its Apache-2.0 licence (© NVIDIA-NeMo). 836 words, ~1,883 tokens.
.claude/skills/nemotron-nano3/SKILL.md (or your agent's skills folder). This skill also uses 17 other files; get the full folder from GitHub.Invocation: /nemotron-nano3.
You are the retrieval skill for Nemotron 3 Nano / Llama-Nemotron Nano 3. Use this skill when the user wants facts about the model itself: architecture, training data, pretraining, SFT, RL, evaluation, quantization, deployment behavior, or how the public Nano3 recipes relate to the tech report.
This skill is a knowledge base, not a code generator.
Answer questions about Nemotron 3 Nano with the most authoritative source available in this repo:
src/nemotron/recipes/nano3/ code maps to the paperWhen the user wants to build, fine-tune, reproduce, customize, or generate pipeline code, hand off to /nemotron-customize.
Concise. Technical. Cite the exact file(s) you used.
Always resolve conflicts in this order:
skills/nemotron-nano3/paper/*.mdskills/nemotron-nano3/recipes/*.mdskills/nemotron-nano3/model-card.mddocs/nemotron/nano3/*.md and src/nemotron/recipes/nano3/*Interpretation rule:
If the paper and recipe differ, say:
“Paper claim:” for the report’s result or method
“Public recipe:” for the open-source reproducible path
Read in this order:
skills/nemotron-nano3/INDEX.mdskills/nemotron-nano3/paper/*.mdskills/nemotron-nano3/recipes/*.mdUse skills/nemotron-nano3/context/quick-reference.md when the user asks:
/nemotron-customize?”Pick the narrowest file that answers the question:
| Question type | Read first |
|---|---|
| “What is Nano3?” | model-card.md, paper/_overview.md |
| Architecture / active params / context length | paper/architecture.md |
| Pretraining corpus / schedule / scaling | paper/data.md, paper/pretraining.md |
| SFT data / chat template / reasoning control | paper/sft.md |
| RLVR / RLHF / GRPO / DPO | paper/rl.md, paper/safety.md |
| Benchmark numbers / comparisons | paper/evaluation.md, model-card.md |
| Safety / refusal / over-refusal / hallucinated tools | paper/safety.md, model-card.md |
| Public recipe mapping | recipes/overview.md + matching stage file |
| “Can I reproduce the paper exactly?” | recipes/overview.md, model-card.md, paper/* |
Every substantive answer should cite the exact file path(s).
Good:
Source: skills/nemotron-nano3/paper/architecture.mdSources: skills/nemotron-nano3/paper/evaluation.md; skills/nemotron-nano3/model-card.mdBetter when needed:
Paper: skills/nemotron-nano3/paper/rl.mdPublic recipe: skills/nemotron-nano3/recipes/stage2_rl.mdIf you synthesize across sources, say so explicitly:
Synthesis from paper + recipe summary: ...Do not dump the whole knowledge base unless asked.
Preferred sequence:
INDEX.mdWhen a question spans both “paper” and “how to run it,” answer in two blocks:
If the user wants to implement something, switch from knowledge to pipeline-building:
Then say:
“This is now a build/customization task. I should hand off to
/nemotron-customize.”
Use skills/nemotron-nano3/context/quick-reference.md to map:
nemotron-customize step or Explorer-mode fallbackImportant caveat:
nemotron-customize currently has direct catalog support for packing, SFT, RL, eval, conversion, curation, translationsrc/nemotron/steps/STEPS.md; route that as an Explorer-mode or direct recipe taskUser:
How many parameters are active in Nemotron 3 Nano and why is it faster than similarly sized models?
Answer pattern:
paper/architecture.mdUser:
Can I reproduce the paper’s SFT and RL results with the public repo?
Answer pattern:
recipes/overview.md/nemotron-customizeUser:
How does Nano3 compare to Qwen3 and GPT-OSS?
Answer pattern:
paper/evaluation.mdmodel-card.md/nemotron-customize when the task becomes procedural or generativeskills/nemotron-nano3/
├── INDEX.md
├── model-card.md
├── paper/
│ ├── _overview.md
│ ├── architecture.md
│ ├── pretraining.md
│ ├── sft.md
│ ├── rl.md
│ ├── evaluation.md
│ ├── data.md
│ └── safety.md
├── recipes/
│ ├── overview.md
│ ├── stage0_pretrain.md
│ ├── stage1_sft.md
│ ├── stage2_rl.md
│ └── stage3_eval.md
└── context/
├── index.toml
└── quick-reference.mdUse this skill to understand Nano3.
Use /nemotron-customize to build with Nano3.
© NVIDIA-NeMo, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 17 other files in skills/nemotron-nano3 of NVIDIA-NeMo/Nemotron.
Open the folder on GitHubat commit ca8c409
Nemotron Nano3 next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Nemotron Nano3 this skillNVIDIA-NeMo/Nemotron | 2.1k | — | ~1.9k | Automated safety check: Pass | Apache-2.0 | |
| Matlab Use Visual Inspectionmatlab/matlab-agentic-toolkit | 1.1k | — | ~3.1k | Automated safety check: Pass | Custom licence | |
| Model Serving Kubernetessickn33/agentic-awesome-skills | 47k | 1 repos | ~2.3k | Automated safety check: Pass | MIT | |
| Rtvi Vlm Customize ModelNVIDIA/skills | 3.6k | — | ~5k | Automated safety check: Notes | Apache-2.0 | |
| Model Serving KubernetesBagelHole/DevOps-Security-Agent-Skills | 1.2k | — | ~2.1k | Automated safety check: Pass | MIT | |
| SageMaker Serving Image Selectionhuggingface/skills | 11k | 1 repos | ~4.6k | Automated safety check: Pass | Apache-2.0 |
matlab/matlab-agentic-toolkit
Build machine vision inspection systems with MATLAB Visual Inspection Toolbox.
sickn33/agentic-awesome-skills
Deploy ML models on Kubernetes with KServe (formerly KFServing) and NVIDIA Triton Inference Server.
NVIDIA/skills
How to swap the VLM in the VSS Alerts Blueprint — covers RTVI-VLM microservice deployment methods, all three VLM consumers (rtvi-vlm, vlm-as-verifier, vss-agent), and health checks.
BagelHole/DevOps-Security-Agent-Skills
Deploy ML models on Kubernetes with KServe (formerly KFServing) and NVIDIA Triton Inference Server.
huggingface/skills
Chooses the right serving container and current image URI for deploying a Hugging Face model to a SageMaker endpoint, preferring Hugging Face images over generic ones.
Orchestra-Research/AI-Research-SKILLs
Covers serving LLMs with SGLang, whose RadixAttention reuses cached prefixes, and constraining output to JSON, regex or grammar for agent and tool-calling workloads.
NVIDIA-NeMo/Nemotron
Onboard a new model family (Nemotron or third-party) into skills/ — paper chunks, recipe summaries, context packs, and model card.
NVIDIA-NeMo/Nemotron
Add a cross-cutting decision pattern under src/nemotron/steps/patterns/.
NVIDIA-NeMo/Nemotron
Add a new step under src/nemotron/steps/<category/<stepid/ — manifest (step.toml), runner glue, configs, and per-step README.md.
NVIDIA-NeMo/Nemotron
Prepare, validate, build, and use Nemotron Customizer airgap image bundles for offline clusters.
NVIDIA-NeMo/Nemotron
Reference desk for NVIDIA Nemotron 3 Super — architecture, training data, recipes (pretrain/SFT/RL/eval/quantization), and deployment notes.
NVIDIA-NeMo/Nemotron
Run the Nemotron-3.5 Lightning Text2SQL LoRA fine-tuning tutorial (NeMo Megatron-Bridge) end-to-end for the user on a single node: data prep, checkpoint conversion, LoRA fine-tuning of the 30B-A3B…
Works with
Categories
Reference desk for Nemotron 3 Nano / Llama-Nemotron Nano 3 — architecture, training data, recipes, evaluation, quantization, deployment. Nemotron Nano3 is an agent skill from NVIDIA-NeMo/Nemotron. Reference desk for Nemotron 3 Nano / Llama-Nemotron Nano 3 — architecture, training data, recipes, evaluation, quantization, deployment.
Nemotron Nano3 fits situations like: the user asks facts about the model rather than building a pipeline; tasks that involve LLM inference and serving; tasks that involve Deployment.
Run `npx skills add NVIDIA-NeMo/Nemotron --skill nemotron-nano3 -a claude-code`. Or copy the skill folder (skills/nemotron-nano3 in NVIDIA-NeMo/Nemotron) into .claude/skills/nemotron-nano3 in your project. Claude Code loads it when a task matches its description.
Run `npx skills add NVIDIA-NeMo/Nemotron --skill nemotron-nano3 -a codex`. Or copy the skill folder (skills/nemotron-nano3 in NVIDIA-NeMo/Nemotron) into .agents/skills/nemotron-nano3 in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NVIDIA-NeMo/Nemotron --skill nemotron-nano3 -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/nemotron-nano3, .gemini/skills/nemotron-nano3, .github/skills/nemotron-nano3 and .opencode/skills/nemotron-nano3 in your project.
SKILL.md names no scripts, command-line tools or credentials: Nemotron Nano3 is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Nemotron Nano3 is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.9k tokens (SKILL.md is roughly 7.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Nemotron Nano3: Matlab Use Visual Inspection (matlab/matlab-agentic-toolkit, 1.1k stars), Model Serving Kubernetes (sickn33/agentic-awesome-skills, 47k stars), Rtvi Vlm Customize Model (NVIDIA/skills, 3.6k stars) and Model Serving Kubernetes (BagelHole/DevOps-Security-Agent-Skills, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
NVIDIA-NeMo (a GitHub organization) maintains it in NVIDIA-NeMo/Nemotron, which has 2,142 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on October 6, 2026.
Source: NVIDIA-NeMo/Nemotron on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.