slurm-job-debug-template

SkillMedia

Use this skill to render, submit, and inspect a minimal Slurm smoke job before submitting heavier workloads on a real cluster.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the slurm-job-debug-template skill

What this skill tells your AI

The instructions your AI receives, as published by ma-compbio-lab/skillfoundry in skills/hpc/slurm-job-debug-template/SKILL.md and read by ahel’s review.

Purpose

Generate a conservative sbatch template, submit it to Slurm, and capture the accounting record needed to verify the cluster path end to end.

When to use

  • You need a tiny Slurm smoke job.
  • You want a reusable starting point for queue, environment, and log validation.

When not to use

  • You need multi-node or GPU tuning guidance beyond a first smoke job.

Inputs

  • Command string
  • Optional job name, partition, runtime, memory, and output path

Outputs

  • Rendered sbatch script
  • JSON submission and sacct summary

Requirements

  • Python 3.13+
  • sbatch, squeue, and sacct
  • A real Slurm cluster

Procedure

  1. Run python3 skills/hpc/slurm-job-debug-template/scripts/render_sbatch.py --command "echo hello" --job-name smoke.
  2. Inspect the generated script or save it with --out.
  3. Submit a verified smoke job with python3 skills/hpc/slurm-job-debug-template/scripts/submit_smoke_job.py --partition cpu --job-name slurm-smoke --sleep 2 --out slurm/reports/slurm-smoke.json.
  4. Inspect the returned job_id, the log paths in slurm/logs/, and the accounting block from sacct.

Validation

  • Renderer exits successfully.
  • Output contains #SBATCH directives and the command body.
  • Submitted smoke job reaches State=COMPLETED.
  • ExitCode is 0:0.

Failure modes and fixes

  • Missing partition/account information: add them before submission.
  • Output paths wrong: switch to cluster-appropriate scratch or log paths.
  • sacct lags briefly after completion: retry once accounting catches up.

Safety and limits

  • Keep resource requests small for initial smoke jobs.
  • Use a CPU partition and a short walltime for smoke checks.

Examples

  • python3 .../render_sbatch.py --command "python analysis.py" --partition short --time 00:10:00 --mem 2G
  • python3 .../submit_smoke_job.py --partition cpu --job-name slurm-smoke --sleep 1

Provenance

Related skills

  • snakemake-toy-workflow-starter

Signals

GitHub stars
39
Forks
5
Last commit
Sep 2026

ahel review

  • K6low
    bundled executables the agent is told to run

Automated review, not a security audit. Ruleset v1+k2.

Advanced
Catalog kind
skill
Gateway key
slurm-job-debug-template
Source
github.com/ma-compbio-lab/skillfoundry