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nemotron-customize

Plan, configure, and chain repo-native Nemotron customization steps into single-step or multi-step pipelines: curation, translation, SFT/PEFT (AutoModel or…

Skill by NVIDIA Nemotron Team <noreply@nvidia.com>

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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

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About

Plan, configure, and chain repo-native Nemotron customization steps into single-step or multi-step pipelines: curation, translation, SFT/PEFT (AutoModel or Megatron-Bridge), pretraining/CPT, RL alignment (DPO/RLVR/GRPO/RLHF), BYOB/MCQ benchmarks, checkpoint conversion, ModelOpt optimization, env profiles, and evaluation of trained checkpoints or existing/hosted endpoints. Use when a request names a Nemotron step or workflow, or asks to clean, translate, train, fine-tune, align, convert, optimize, evaluate, or compose these into a pipeline. Do NOT use for frontend/dashboard/visualization work, generic ML advice, billing/access, or non-Nemotron coding tasks.

Use cases: frontend, data, ml, productivity

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
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Secrets
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Install scripts
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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/nemotron-customize

What's inside

Skill name
nemotron-customize
Description
Plan, configure, and chain repo-native Nemotron customization steps into single-step or multi-step pipelines: curation, translation, SFT/PEFT (AutoModel or Megatron-Bridge), pretraining/CPT, RL alignment (DPO/RLVR/GRPO/RLHF), BYOB/MCQ benchmarks, checkpoint conversion, ModelOpt optimization, env profiles, and evaluation of trained checkpoints or existing/hosted endpoints. Use when a request names a Nemotron step or workflow, or asks to clean, translate, train, fine-tune, align, convert, optimize, evaluate, or compose these into a pipeline. Do NOT use for frontend/dashboard/visualization work, generic ML advice, billing/access, or non-Nemotron coding tasks.
License
Apache-2.0
Metadata
author: NVIDIA Nemotron Team <noreply@nvidia.com> · version: 0.1.1
Instructions
309 lines in SKILL.md · view on GitHub

Files (35)

  • plugin.json · .claude-plugin/
  • BENCHMARK.md
  • SKILL.md
  • evals.json · evals/
  • ARTIFACTS.md · references/
  • CATALOG.md · references/
  • COMMANDS.md · references/
  • HARDWARE.md · references/
  • PATTERNS.md · references/
  • WORKFLOW.md · references/
  • PROJECT.md · references/act/
  • STAGE.md · references/act/
  • README.md · references/context/
  • automodel-launcher-executor-modes.txt · references/context/
  • automodel-pretrain.txt · references/context/
  • automodel-sft-peft-core.txt · references/context/
  • byob-benchmark-curator-translation.txt · references/context/
  • checkpoint-conversion.txt · references/context/
  • curator-data-acquisition.txt · references/context/
  • curator-processing-language-quality.txt · references/context/
  • curator-translation-faith.txt · references/context/
  • data-designer-sdg.txt · references/context/
  • eval-deploy-formats.txt · references/context/
  • eval-sovereign-benchmarks.txt · references/context/
  • eval-standard-nlu.txt · references/context/
  • index.toml · references/context/
  • mbridge-parallelism-performance.txt · references/context/
  • mbridge-pretrain.txt · references/context/
  • mbridge-sft.txt · references/context/
  • modelopt-optimization.txt · references/context/
  • nemo-rl-alignment.txt · references/context/
  • nemotron-data-prep.txt · references/context/
  • CALIBRATION.md · references/examples/
  • skill-card.md
  • skill.oms.sig

SKILL.md (first lines)

# nemotron-customize

IMPORTANT: Read this file before answering any `nemotron-customize`,
Nemotron customization, Curator curation, translation, SFT, PEFT, RL,
conversion, optimization, checkpoint or existing/hosted-endpoint evaluation, or
multi-step pipeline request. This applies whether the user names one step or
asks you to compose several steps into a pipeline.

Evaluation requests count even when no training is involved: "evaluate",
"benchmark", "smoke test", or "score" an existing/hosted endpoint, an API/model
ID, or a deployed model all route to `eval/model_eval`. Read this skill for
those too.

## Purpose

Turn a model-customization request into a repo-native Nemotron step pipeline.
Plan the DAG, validate artifact wiring, and create only the YAML/config files
needed to run existing steps.

Use this skill only for inspecting, configuring, validating, running, or
submitting existing Nemotron steps or multi-step training/customization
pipelines. For frontend, dashboard, visualization, generic ML advice,
billing/access, or unrelated coding tasks, stop with a short scope note and do
not inspect the step catalog or edit files in that turn.

## Prerequisites

- A checkout of the Nemotron repo with `src/nemotron/steps/` present; run from
  the repo root.
- `uv` available to invoke `uv run nemotron steps ...`.
- For remote execution: an env profile TOML (`NEMOTRON_ENV_FILE` or
  `env*.toml`) with a section matching the selected step.
- For hosted services (translation, hosted eval): the auth environment variable
  expected by the step (for example `NVIDIA_API_KEY`), exported in the
  environment — never inlined or committed.
- User-provided concrete values (model/checkpoint, data paths, output dir,
  hardware/GPU count) before any command is presented as runnable.

## Limitations

- Does not invent new catalog steps. When no existing step, runner, recipe, CLI,
  or config can satisfy the request, it names the gap (Explorer mode) instead of
  fabricating a step.
- Produces YAML/config for existing steps; new Python/shell is out of scope
  except in Explorer mode after the gap is approved.
- Not for deployment-only/serving, frontend, dashboards, generic ML advice, or
  non-Nemotron tasks.
- Does not guess concrete values (paths, model IDs, GPU counts, profiles); it
  asks or returns `Blocked` when they are missing.

## Core Rule

Use bundled references first. The `references/` folder is the first decision
surface for routing, artifacts, patterns, hardware heuristics, and command
shape. Use `src/nemotron/steps/...` only as a live verification/fallback source
when you need exact current config fields, manifests, runner imports, or details
missing from bundled references.

If sources disagree:

1. Checked live repo files win for exact execution.
2. Bundled references win for initial routing and planning.
3. Upstream docs/context packs are used only for exceptional code generation
   or library API details.

## Before You Begin

- Read this `SKILL.md` workflow and the relevant bundled reference before
  opening repo source files.
- Route from `references/CATALOG.md` and `references/ARTIFACTS.md` before any
  broad repo exploration. Once a route is determined, verify only the selected
  live step/config/env files needed for the answer.
- Do not emit commands with fake paths, placeholder model IDs, guessed task IDs,
  guessed batch profiles, or default auth variable names presented as facts.
  Ask for missing concrete values or return a `Blocked` handoff.
- Use `references/COMMANDS.md` as the authoritative checklist before
  finalizing configs or execution commands.
- For pipeline requests, plan before editing. Do not create or modify files
  until the DAG, artifact edges, required inputs, and validation checks are
  stated and approved.
- For one-shot command requests, prefer a complete parameterized command in one
  response over exploratory prose, but only after required inputs are known.
  If the user already provides the needed values and asks for only a command,
  answer with the command first and keep explanation minimal.
- Output discipline (keeps responses tight): emit one command block per step,
  include only flags the step actually defines, and add no speculative or
  invented flags. Keep narrative to a few lines — the command plus the required
  safety/profile callouts, not a tutorial. Do not restate reference content the
  user did not ask for.
- Do not spawn subagents for one-shot command lookup. Use the bundled command
  reference directly; verify only the selected step if needed.

## Safety

Keep Bash scoped to repo-safe commands such as `uv run nemotron steps ...`,
targeted tests, `git status/diff`, and config validation. Never run environment
dumps (`env`, `printenv`, broad `export`) or commands that expose secret values.
For remote submissions, destructive changes, or expensive launches, confirm
before execution.

When inspecting env/config files, avoid printing whole files that may contain
secrets. Use targeted reads, report only section names and env-var names, and
redact values for fields containing `token`, `key`, `secret`, `password`,
`credential`, or `auth`.

## Reference Map

| Question | Read first | Live fallback / verification |
|---|---|---|
| Which step or category fits? | `references/CATALOG.md` | `uv run nemotron steps list/show`, then selected `step.toml` |
| Do artifacts chain? | `references/ARTIFACTS.md` | `src/nemotron/steps/types.toml` |
| What run shape should I emit? | `references/COMMANDS.md` | checked-in config YAML plus active profile TOML |
| Remote profile generation or selection | `references/COMMANDS.md` | active `NEMOTRON_ENV_FILE`, `env.toml`, or `env.*.toml` |
| What hardware/backend should I recommend? | `references/HARDWARE.md` | selected step `[[models]]` and `[[strategies]]` |
| Which cross-step guardrails apply? | `references/PATTERNS.md` | `src/nemotron/steps/patterns/<id>.md` |
| How do I run the full workflow? | `references/WORKFLOW.md` | selected step configs, `step.py`, and runners |
| Which upstream library API should generated code use? | `references/context/index.toml` -> matching pack | selected `step.py`, `_runners/`, upstream docs |
| New project scaffold, only when existing repo code cannot support the request | `references/act/PROJECT.md` | existing repo project/recipe shape |
| Per-stage code rules, only when existing repo code cannot support the request | `references/act/STAGE.md` | selected `step.py` and shared runner |

From NVIDIA/skills, Apache-2.0.

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Details

Version
0.1.1
License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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nemotron-customize skill. Agent Mart. https://agentmart.dev/skills/nvidia-nemotron-customize (last updated 2026-10-24)