SLURM Job Script Generator

Goal

Generate a correct, copy-pasteable SLURM job script (.sbatch) for running a simulation, and surface common configuration mistakes (bad walltime format, conflicting memory flags, oversubscription hints).

Requirements

• Python 3.8+
• No external dependencies (Python standard library only)
• Works on Linux, macOS, and Windows (script generation only)

Inputs to Gather

Input	Description	Example
Job name	Short identifier for the job	phasefield-strong-scaling
Walltime	SLURM time limit	00:30:00
Partition	Cluster partition/queue (if required)	compute
Account	Project/account (if required)	matsim
Nodes	Number of nodes to allocate	2
MPI tasks	Total tasks, or tasks per node	128 or 64 per node
Threads	CPUs per task (OpenMP threads)	2
Memory	--mem or --mem-per-cpu (cluster policy dependent)	32G
GPUs	GPUs per node (optional)	4
Working directory	Where the run should execute	$SLURM_SUBMIT_DIR
Modules	Environment modules to load (optional)	gcc/12, openmpi/4.1
Run command	The command to launch under SLURM	./simulate --config cfg.json

Decision Guidance

MPI vs MPI+OpenMP layout

Does the code use OpenMP / threading?
├── NO  → Use MPI-only: cpus-per-task=1
└── YES → Use hybrid: set cpus-per-task = threads per MPI rank
          and export OMP_NUM_THREADS = cpus-per-task

Rule of thumb: if you see diminishing strong-scaling efficiency at high MPI ranks, try fewer ranks with more threads per rank (and measure).

Memory flag selection

• Use either --mem (per node) or --mem-per-cpu (per CPU), not both.
• Follow your cluster’s documentation; some sites enforce one style.
• SLURM --mem units are integer MB by default, or an integer with suffix K/M/G/T (and --mem=0 commonly means “all memory on node”).

Script Outputs (JSON Fields)

Script	Key Outputs
scripts/slurm_script_generator.py	results.script, results.directives, results.derived, results.warnings

Workflow

1. Gather cluster constraints (partition/account, GPU policy, memory policy).
2. Choose a process layout (MPI-only vs hybrid MPI+OpenMP).
3. Generate the script with slurm_script_generator.py.
4. Inspect warnings (conflicts, suspicious layouts).
5. Save the generated script as job.sbatch.
6. Submit with sbatch job.sbatch and monitor with squeue.

CLI Examples

# Preview a job script (prints to stdout)
python3 skills/hpc-deployment/slurm-job-script-generator/scripts/slurm_script_generator.py \
  --job-name phasefield \
  --time 00:10:00 \
  --partition compute \
  --nodes 1 \
  --ntasks-per-node 8 \
  --cpus-per-task 2 \
  --mem 16G \
  --module gcc/12 \
  --module openmpi/4.1 \
  -- \
  ./simulate --config config.json

# Write to a file and also emit structured JSON
python3 skills/hpc-deployment/slurm-job-script-generator/scripts/slurm_script_generator.py \
  --job-name phasefield \
  --time 00:10:00 \
  --nodes 1 \
  --ntasks 16 \
  --cpus-per-task 1 \
  --out job.sbatch \
  --json \
  -- \
  /bin/echo hello

Conversational Workflow Example

User: I need an sbatch script for my MPI simulation. I want 2 nodes, 64 ranks per node, 2 OpenMP threads per rank, and 2 hours.

Agent workflow:

1. Confirm partition/account and whether GPUs are needed.
2. Generate a hybrid job script:

   python3 scripts/slurm_script_generator.py --job-name run --time 02:00:00 --nodes 2 --ntasks-per-node 64 --cpus-per-task 2 -- -- ./simulate
   

3. Explain the mapping:
   • Total ranks = 128
   • Threads per rank = 2 (OMP_NUM_THREADS=2)
4. If the user provides node core counts, sanity-check oversubscription using --cores-per-node.

Error Handling

Error	Cause	Resolution
time must be HH:MM:SS or D-HH:MM:SS	Bad walltime format	Use 00:30:00 or 1-00:00:00
nodes must be positive	Non-positive nodes	Provide --nodes >= 1
Provide either --mem or --mem-per-cpu, not both	Conflicting memory directives	Choose one memory style
Provide a run command after --	Missing launch command	Add -- ./simulate ...

Security

Input Validation

• --time is validated against strict HH:MM:SS or D-HH:MM:SS format via regex
• --nodes, --ntasks, --ntasks-per-node, --cpus-per-task, --gpus are validated as positive integers with upper bounds
• --mem and --mem-per-cpu are validated against SLURM's accepted format (<int>[K|M|G|T]); providing both simultaneously is rejected
• --job-name is validated against [a-zA-Z0-9_.-]+ (no shell metacharacters)
• --partition and --account are validated against safe-character allowlists
• --module values are validated to prevent shell injection (no ;, |, &, backticks, or $)

File Access

• The script reads no external files; all inputs are provided via CLI arguments
• --out writes the generated sbatch script to a single specified file path
• The generated script is a plain-text shell script with #SBATCH directives; it contains no dynamically generated code

Tool Restrictions

• Read: Used to inspect script source, references, and existing job scripts
• Bash: Used to execute slurm_script_generator.py with explicit argument lists; the generated script itself is NOT executed by the agent
• Write: Used to save the generated .sbatch file; writes are scoped to the user's working directory
• Grep/Glob: Used to locate existing scripts, configs, and cluster documentation

Safety Measures

• No eval(), exec(), or dynamic code generation
• All subprocess calls use explicit argument lists (no shell=True)
• The run command (after --) is included verbatim in the generated script but is never executed by the skill itself
• Module names are sanitized to prevent injection into module load directives
• Generated scripts use set -euo pipefail for safe shell execution on the cluster

Limitations

• Does not query cluster hardware or site policies; it can only validate internal consistency.
• SLURM installations vary (GPU directives, QoS rules, partitions). Adjust directives for your site.

References

• references/slurm_directives.md - Common #SBATCH directives and mapping tips

Version History

• v1.0.0 (2026-02-25): Initial SLURM job script generator