Slurm job debug template

Skill ma-compbio-lab/SkillFoundry/skills/hpc/slurm-job-debug-template

A framework for discovering, compiling, and validating reusable skills for scientific agents.

Install

npx -y skills add ma-compbio-lab/SkillFoundry --skill slurm-job-debug-template

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What its author says it does

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

SKILL.md

2.3 KB, 558 tokens by cl100k_base, as published. Nobody here has run it

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

Run python3 skills/hpc/slurm-job-debug-template/scripts/render_sbatch.py --command "echo hello" --job-name smoke.
Inspect the generated script or save it with --out.
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.
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

Slurm quick start: https://slurm.schedmd.com/quickstart.html
Slurm sbatch reference: https://slurm.schedmd.com/sbatch.html
sacct reference: https://slurm.schedmd.com/sacct.html

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