hello-qm/catgo-lrg/cluster-config-test

Claude Code and agent skill by hello-qm/catgo-lrg

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Validate an HPC/cluster configuration against the live cluster BEFORE submitting a VASP workflow, or diagnose why a remote job produced no output. Reads the user's submit script / run config, then calls the validate_hpc_config tool to probe the real cluster over SSH (POTCAR directories, per-element pseudopotentials, and VASP binary resolution under the real module-load + conda environment). Use whenever the user asks to "test my cluster config", "check if VASP will run", "verify my HPC setup", or after a job silently failed for environment/path reasons.

Install

npx vskill@latest install hello-qm/catgo-lrg/cluster-config-test

SKILL.md

Cluster Config Test

Provider-agnostic: works for any in-app AI (DeepSeek, Qwen, Kimi, Gemini, Anthropic, Codex, …). You validate the cluster by calling the validate_hpc_config tool — you do NOT run raw SSH yourself.

When to Use

  • The user wants to confirm their cluster settings work before running a workflow.
  • A submitted VASP job "completed" but produced no real output, or POTCAR was missing.
  • The user pasted a submit script and asks whether it will run on their cluster.

Why this matters (the failure it catches)

CatGo builds the POTCAR on the remote host by concatenating <potcar_root>/<functional>/<variant>/POTCAR in POSCAR element order. If the POTCAR root is wrong/unreachable, an element pseudopotential is missing, or the VASP binary doesn't resolve under the job's module-load/conda environment, the run fails — and a plain SLURM job can still exit 0, so the failure is easy to miss. Validate first.

Procedure

1. Gather the config

From the user's run configuration or their submit script, collect:

  • potcar_root — directory holding the POTCAR tree, e.g. /scratch/user/VASP/pot64
  • potcar_functional — e.g. potpaw_PBE (default), potpaw_PBE.54, potpaw_LDA
  • vasp_command — the run line, e.g. srun --hint=nomultithread vasp_std
  • module_loads — every module load/module switch line (newline-separated)
  • python_env — the source …/conda.sh + conda activate … lines

If the user only pasted a submit script, parse these out of it. If something is missing, ask the user for it (do not guess paths).

2. Call the tool
json
validate_hpc_config({
"potcar_root": "/scratch/user/VASP/pot64",
"potcar_functional": "potpaw_PBE",
"vasp_command": "srun --hint=nomultithread vasp_std",
"module_loads": "module load vasp/6.4.2",
"python_env": "source /scratch/user/miniconda3/etc/profile.d/conda.sh\nconda activate catgo"
})

The active HPC session and the element list (from the loaded structure) are filled in automatically — only pass elements/session_id to override. The tool returns { success, checks: [{ name, ok, severity, detail }], message }.

3. Interpret and report
  • severity: "error" + ok: false → will break the run. Report the exact problem

and fix (wrong POTCAR root, missing element pseudopotential, etc.).

  • severity: "warn" (e.g. the VASP binary not resolving) → advisory: the binary may

live only on compute nodes, or the module-load line is wrong. Tell the user which.

  • success: true → cluster is ready; offer to run the workflow.

Map results to the common causes:

Check failsLikely cause / fix
POTCAR root directorywrong/unreachable path; fix potcar_root, check it exists on this host
Functional directorywrong functional name; pick the one that exists (e.g. potpaw_PBE.54)
Element POTCARs (missing X)that element's pseudopotential dir is absent under the functional
VASP binary (warn)wrong/absent module load, or binary only on compute nodes
4. Re-test after fixes

After the user updates a path or module line, call validate_hpc_config again. Iterate until success: true, then proceed to submit.

Notes

  • Read-only: the tool only probes; it never writes or submits.
  • If there is no connected cluster, the tool errors — tell the user to connect a cluster

in the HPC panel first.

  • This is the deeper counterpart to the "Test configuration" button in the Run dialog:

the button checks fixed fields; here you read the user's actual submit script.

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
176
Repository forks
19
7-day trend score
26

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 1 Aug 2026, 3 months ago.

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