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NV-Generate-MR · nvidia | DecimalAI

scienceby nvidia

NV-Generate-MR

nvidia/nv-generate-mr

Source nvidia/skills ↗License Apache-2.0

Used for generating synthetic body MRI volumes with NV-Generate-CTMR rflow-mr. Not for paired masks or production training data.

SkillScore100Maintained

Automatic

AI Engineer pack

Last verified 8/12/2026

What it changes

Passed 20 of 20 test cases with the skill, and 6 of 20 without it.

Without skill32%

With skill100%

Checks it passed that the model alone missed

The command does not contain rm.
The command sets NV_GENERATE_ROOT.
The command includes --model_only.

and 21 more in the full report

15 fixed7 passed either way0 still failing0 broke

Pass-rate lift: +68 pp
Tokens: +80%
Agent turns: 0%
Response time: -62%

Model gemini-3.6-flashMeasured 8/12/2026v122 of 22 cases passed with skill · 20 comparable

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/nvidia-nv-generate-mr/SKILL.md https://app.decimal.ai/s/nvidia-nv-generate-mr/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add nvidia-nv-generate-mr, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/nvidia-nv-generate-mr/ and pins it in .decimal/skills.lock

decimalai skills add nvidia-nv-generate-mr

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/nvidia-nv-generate-mr/SKILL.md https://app.decimal.ai/s/nvidia-nv-generate-mr/SKILL.md

Raw file: /s/nvidia-nv-generate-mr/SKILL.md ↗ · machine-readable summary at /s/nvidia-nv-generate-mr.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 13 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 13

Prompt

I need to run synthetic T1 body MRI volume generation using the NV-Generate-MR wrapper. My request configuration file is located at `configs/body_mri_params.json` and I want the results saved in `runs/synthetic_body_t1_01`. Please provide the exact single-block bash command to perform this run, making sure dependencies are properly installed first.

What was checked, without and with the skill
Checked	Without skill	With skill
The command references scripts/run_mr.py.	Missed	Passed
The command includes pip install -r "$NV_GENERATE_ROOT/requirements.txt".	Missed	Passed
The command passes --modality mri_t1.	Missed	Passed
The command sets NV_GENERATE_ROOT.	Missed	Passed

case-01 · gemini-3.6-flash · 8/12/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md137 lines3 filesincludes scripts

NV-Generate-MR

Purpose

Used for generating synthetic body MRI volumes with NV-Generate-CTMR rflow-mr. Not for paired masks or production training data.
Use the wrapper exactly as documented; do not replace the upstream entrypoint with a handwritten implementation.
Do not write custom inference code for normal runs. The wrapper owns config staging, output paths, and validation.
Manifest I/O: inputs are model_config_override; outputs are synthetic_mr_volumes and result_json.

Instructions

Read skill_manifest.yaml before changing arguments, side effects, or validation gates.
Run scripts/run_mr.py through the documented command below; keep outputs under a caller-provided run directory.
If a host agent exposes run_script, use run_script("scripts/run_mr.py", args=[...]); otherwise run the Bash/Python command shown below.
Emit a single bash code block, and keep the python -m pip install -r "$NV_GENERATE_ROOT/requirements.txt" step in that same command — the runtime may be a fresh environment without nibabel/MONAI, so dropping the install fails with ModuleNotFoundError.
Do not add rm, mkdir, or any cleanup of --output-dir; the wrapper creates it. Use a fresh --output-dir instead of deleting one.
Check the emitted JSON and paired verifier guidance before treating the run as evidence.

Available Scripts

Script	Purpose	Arguments
`scripts/run_mr.py`	Primary entrypoint declared by skill_manifest.yaml.	`MODEL_CONFIG.json --output-dir OUT_DIR --modality mri_t1 [--random-seed N] [--yes]`

Prerequisites

Runtime requirements: GPU/CUDA when declared by the manifest; Python packages listed in runtime.side_effects.pip_packages.
Side effects: writes generated outputs under the caller's --output-dir, may cache model assets under ~/.cache/huggingface/, and may contact https://huggingface.co or https://github.com during setup.
Run commands from the repository root unless an existing section below says otherwise.

Limitations

This is a thin wrapper. Inference, sampling, and decoding are delegated entirely to NVIDIA-Medtech/NV-Generate-CTMR's scripts.diff_model_infer. Do not modify code under $NV_GENERATE_ROOT or the repo-local fallback at .workbench_data/upstreams/NV-Generate-CTMR.
rflow-mr generates image-only synthetic MRI volumes. It does not emit paired segmentation masks.
The upstream README recommends rflow-mr-brain instead for brain MRI synthesis; use skills/nv-generate-mr-brain for that path.
NV-Generate-MR weights are listed by upstream as NVIDIA Non-Commercial. Do not use outputs as production training data without legal and quality review.
Not for clinical deployment, clinical interpretation, autonomous diagnosis, regulatory submission.

Troubleshooting

Error	Cause	Fix
Missing dependency or import error	Runtime package drift from `skill_manifest.yaml`.	Install the packages declared in the manifest or use the documented setup command.
Empty or schema-invalid output	Wrong input path, unsupported modality, or upstream failure.	Re-run with a known fixture and inspect the wrapper JSON plus stderr.
Validation gate failure	Output violated a declared engineering invariant.	Keep the failed evidence pack and use the gate message to repair inputs or wrapper code.

Track record

Benchmark

20 / 20

test cases passed, vs 6 / 20 without

Adoption

Users: 0
Times used: 0

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/3/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

nvidia / skills

skills/nv-generate-mr/SKILL.md

View on GitHub ↗

License Apache-2.0Imported 8/3/2026Version v1Bundled 2 files · scripts

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See it in action

What's inside

NV-Generate-MR

Purpose

Instructions

Available Scripts

Prerequisites

Limitations

Troubleshooting

Track record

Benchmark

Adoption

SkillSafety

Source

Other skills for the same job

Related skills