Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add HeshamFS/materials-simulation-skills --skill hpc-runtime-doctorgit clone --depth 1 https://github.com/HeshamFS/materials-simulation-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/heshamfs/materials-simulation-skills/hpc-runtime-doctor)<a href="https://agentmods.dev/skills/heshamfs/materials-simulation-skills/hpc-runtime-doctor"><img src="https://agentmods.dev/badge/skills/heshamfs/materials-simulation-skills/hpc-runtime-doctor/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/heshamfs/materials-simulation-skills/hpc-runtime-doctor"><img src="https://agentmods.dev/badge/skills/heshamfs/materials-simulation-skills/hpc-runtime-doctor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00099 | $0.02429 |
| Opus 5 | $0.00049 | $0.01215 |
| Sonnet 5 | $0.00020 | $0.00486 |
| Haiku 4.5 | $0.00010 | $0.00243 |
Grade A, and why
hpc-runtime-doctor scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
- No `eval`, `exec`, `os.system`, or `subprocess`; the script does not launch a scheduler How it starts
The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
HPC Runtime Doctor
Goal
Turn cluster symptoms into a resource-layout diagnosis, environment checklist, and safe retry plan.
Requirements
- Python 3.10+
- No external dependencies
- Works on Linux, macOS, and Windows
Inputs to Gather
| Input | Description | Example |
|---|---|---|
| Scheduler | SLURM, PBS, LSF, local | slurm |
| Nodes/tasks/threads | Runtime layout | 2 nodes, 128 tasks, 2 threads |
| GPUs | Total (whole-job) GPUs via --gpus, or per node via --gpus-per-node |
--gpus 4 or --gpus-per-node 1 |
| Symptoms | Observed failure | oom,killed,slow-gpu |
| MPI/OpenMP/GPU use | Parallel modes | mpi+openmp+gpu |
| Walltime | Requested time | 12:00:00 |
| Scratch | Whether scratch is used | true |
Decision Guidance
- Check resource layout before changing physics settings.
- Confirm module/compiler/MPI/CUDA consistency before debugging solver behavior.
- Treat missing restart files and scratch cleanup as workflow failures, not physics failures.
- For GPU jobs, confirm the executable was built with the requested accelerator backend.
Script Outputs
scripts/hpc_runtime_doctor.py emits:
resource_layout(includestasks_per_node,total_cpus, totalgpus, andgpus_per_node)diagnosesenvironment_checksretry_planscheduler_noteswarnings(layout flags such as ranks-per-GPU oversubscription, OpenMP/thread mismatch, and uneven task placement)
In default (non-JSON) mode the script also prints the resource-layout summary, any
warnings, environment checks, and retry plan, so the most actionable items are never hidden.
Workflow
--gpus is the total (whole-job) GPU count. Use --gpus-per-node (SLURM
--gres=gpu:N semantics) when you know the per-node allocation; total GPUs are then
gpus_per_node * nodes and it overrides --gpus.
python3 skills/hpc-deployment/hpc-runtime-doctor/scripts/hpc_runtime_doctor.py \
--scheduler slurm \
--nodes 2 \
--tasks 128 \
--cpus-per-task 2 \
--gpus 4 \
--symptoms oom,slow-gpu \
--uses-mpi \
--uses-openmp \
--uses-gpu \
--json
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 182 lines · 99 tokens per session scan A 4855ebeb61ff
hpc-runtime-doctor is a skill published in the GitHub repository HeshamFS/materials-simulation-skills (66 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 99 tokens to every session and 2,429 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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