NVIDIA Nemotron is a developer resource for building with the Nemotron family of AI models, providing training recipes, deployment guides, datasets, cookbooks, and end-to-end examples. It is intended for developers and researchers training, customizing, deploying, or applying Nemotron models to agentic AI use cases. Its catalogue add-ons include a Claude Code plugin that guides users through Nemotron customization steps.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add NVIDIA-NeMo/Nemotron --skill nemotron-retrieval-recipesgit clone --depth 1 https://github.com/NVIDIA-NeMo/NemotronWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/nvidia-nemo/nemotron/nemotron-retrieval-recipes)<a href="https://agentmods.dev/skills/nvidia-nemo/nemotron/nemotron-retrieval-recipes"><img src="https://agentmods.dev/badge/skills/nvidia-nemo/nemotron/nemotron-retrieval-recipes/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/nvidia-nemo/nemotron/nemotron-retrieval-recipes"><img src="https://agentmods.dev/badge/skills/nvidia-nemo/nemotron/nemotron-retrieval-recipes.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 57 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 87 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00042 | $0.02758 |
| Opus 5.5 | $0.00017 | $0.01103 |
| Sonnet 5.5 | $0.00008 | $0.00552 |
| Haiku 4.5 | $0.00004 | $0.00276 |
Grade A, and why
nemotron-retrieval-recipes scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Nemotron Retrieval Recipes
Invocation: $nemotron-retrieval-recipes.
Purpose
Use this skill to plan, run, and debug public Nemotron embedding and reranking recipes. The bundled references support planning without a Nemotron checkout or network access. Before execution, verify the installed CLI's capabilities and the selected configuration because recipe interfaces can change.
Use it only for tasks tied to the public Nemotron embed or rerank recipe flow. If the request is unrelated retrieval theory, generic vector database selection, generic benchmark advice, or non-recipe Docker/Slurm/NIM troubleshooting, stop with a short scope note and do not inspect recipe files in that turn.
Security Notes
Use Bash for repo-scoped inspection, help, dry-run, and user-approved execution commands. Do not run API, GPU, Docker, Slurm, NIM, or other long-running work unless the user explicitly asks for it. Before Stage 0 SDG for either family, confirm the user's data-governance policy permits sending corpus content to the configured inference endpoints; otherwise use an approved private or air-gapped path. Never run broad environment dumps or commands that expose secret values. Prefer dotlist overrides and config review over editing recipe defaults.
Runtime and Source Priority
Resolve references/ links relative to this skill folder, not the working
directory. External source links are optional, commit-pinned background.
Do not require repository documentation to answer a planning question.
Execution examples assume a prepared Nemotron checkout. At the bundled
revision, the CLI resolves recipe scripts from the working directory: run
from the checkout root even if nemotron is installed globally. Use
uv run nemotron there, or nemotron directly in an activated environment.
Do not run uv sync in an unrelated project. Without a checkout or runtime,
provide a plan from the bundled references and identify setup as an execution
prerequisite. Never require a checkout just to explain the workflow.
What ships with it
11 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago Changed · +19 lines · +6 tokens per session 7754b0bd0077
- 1mo ago First seen · 143 lines · 36 tokens per session scan A 5a4c2b4d1663
nemotron-retrieval-recipes is a skill published in the GitHub repository NVIDIA-NeMo/Nemotron (2,218 stars, last pushed 5d ago), licensed Apache-2.0. It adds 42 tokens to every session and 2,758 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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