skilld
All skills
nvidia avatar

/mcore-run-on-slurm

@416539c
by NVIDIA Corporationnvidia/skills3.5k stars
424

How to launch distributed Megatron-LM training jobs on a SLURM cluster. Covers a minimal sbatch skeleton, environment-variable setup for torch.distributed.run, CUDA_DEVICE_MAX_CONNECTIONS rules across hardware and parallelism modes, container conventions, monitoring, and per-rank failure diagnosis.

Ask your Agent

Use this Skill: https://skilld.dev/gh/nvidia/skills/mcore-run-on-slurm

This session only. Nothing lands on disk.

BENCHMARK.md

≈701 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Evaluation Report

Evaluation of the mcore-run-on-slurm skill before publication through NVSkills-Eval.

This benchmark summarizes 3-Tier Evaluation from NVSkills-Eval results for the skill. The goal is to document whether the skill is safe, discoverable, effective, and useful for agents before it is published for broader workflow use.

Evaluation Summary

  • Skill: mcore-run-on-slurm
  • Evaluation date: 2026-05-29
  • NVSkills-Eval profile: external
  • Overall verdict: PASS
  • Tier 3 live agent evaluation: not available in this report

Agents Used

  • Tier 3 agent details were not available in this report.

Metrics Used

Reported benchmark dimensions:

  • Security: checks whether skill-assisted execution avoids unsafe behavior such as secret leakage, destructive commands, or unauthorized access.
  • Correctness: checks whether the agent follows the expected workflow and produces the correct final output.
  • Discoverability: checks whether the agent loads the skill when relevant and avoids using it when irrelevant.
  • Effectiveness: checks whether the agent performs measurably better with the skill than without it.
  • Efficiency: checks whether the agent uses fewer tokens and avoids redundant work.

Underlying evaluation signals used in this run:

  • No Tier 3 evaluation signal details were available in this report.

Test Tasks

Tier 3 evaluation task details were not available in this report.

Results

Tier 3 dimension rollup was not available in this report.

Tier 1: Static Validation Summary

Tier 1 validation passed with observations. NVSkills-Eval ran 9 checks and found 7 total findings.

Top findings:

  • MEDIUM QUALITY/quality_correctness: SKILL_SPEC recommended field missing: 'metadata.tags' (skills/mcore-run-on-slurm/SKILL.md)
  • MEDIUM SCHEMA/body_recommended_section: Missing recommended section: '## Instructions' (skills/mcore-run-on-slurm/SKILL.md)
  • MEDIUM SCHEMA/body_recommended_section: Missing recommended section: '## Examples' (skills/mcore-run-on-slurm/SKILL.md)
  • LOW QUALITY/quality_discoverability: Description very long (299 chars, recommend 50-150) (skills/mcore-run-on-slurm/SKILL.md)
  • LOW QUALITY/quality_discoverability: No '## Purpose' section (skills/mcore-run-on-slurm/SKILL.md)

Tier 2: Deduplication Summary

Tier 2 validation passed. NVSkills-Eval ran 2 checks and found 0 total findings.

Notable observations:

  • Context Deduplication: Collected 1 file(s)
  • Inter-Skill Deduplication: Parsed skill 'mcore-run-on-slurm': 299 char description

Publication Recommendation

The skill is suitable to proceed toward NVSkills-Eval publication based on this benchmark. Skill owners should keep this file with the skill and refresh it when the evaluation dataset, skill behavior, or target agents materially change.

Source: SKILL.md on GitHub

Third-party checks

No alerts3mo3 checks · Risk SAFE
  • Gen Agent Trust Hub3mo

    This skill is a technical guide for launching Megatron-LM distributed training jobs on SLURM clusters. It provides standard sbatch script templates, environment configuration, and troubleshooting steps using official NVIDIA tools and repositories.

  • Socket3mo

    No alerts

  • Snyk3mo

    Risk: LOW · No issues

Provenance

Signed by skilld at 416539c. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated 4 months ago

Capability

metadata
{
  "author": "Philip Petrakian <ppetrakian@nvidia.com>"
}
Other metadata
when_to_use
Submitting a SLURM job; writing or debugging an sbatch script; configuring multi-node distributed training; setting MASTER_ADDR / MASTER_PORT / WORLD_SIZE; diagnosing a SLURM job failure; 'how do I run on the cluster', 'sbatch', 'multi-node training'.

README badge

README badge for nvidia/skills/mcore-run-on-slurm