run-gauss
SkillDocs & knowledgeActs as a knowledge base providing environment checklists, directory/scratch management, and bash command templates. USE WHEN you need to guide the execution of Gaussian computational chemistry jobs (.gjf) on local or remote/HPC environments.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the run-gauss skill
What this skill tells your AI
The instructions your AI receives, as published by jinzhezenggroup/computational-chemistry-agent-skills in quantum-chemistry/run-gauss/SKILL.md and read by ahel’s review.
Ask the user for these details
- Run location:
<local>or<remote/HPC>(and scheduler if any) - Environment setup:
<env_setup_cmds>(e.g. module load / source script) - Gaussian executable:
<gaussian_exec>(e.g.g16,g09, or absolute path) - Working directory:
- local prep dir:
<local_work_dir>(if applicable) - remote run dir:
<remote_work_dir>(if applicable) - per-task dir:
<task_work_dir>
- local prep dir:
- Files:
- input:
<input.gjf> - Gaussian output:
<gaussian_log> - wrapper stdout/stderr (if needed):
<stdout_log>,<stderr_log>
- input:
- Scratch:
GAUSS_SCRDIR=<scratch_dir>(e.g../scratch,$TMPDIR, or site-provided scratch)- whether to clean scratch after the run
Command template
<env_setup_cmds>
export GAUSS_SCRDIR=<scratch_dir>
mkdir -p "$GAUSS_SCRDIR"
<gaussian_exec> < <input.gjf> > <gaussian_log>
rm -rf "$GAUSS_SCRDIR"
Generate / assemble .gjf (when there is not an existing one)
Use gjf-flux to extract/assemble .gjf sections and build workflows.
Find the extract/assemble skill: gjf-flux
Submit via dpdispatcher (recommended)
Recommend using dpdispatcher to submit Gaussian calculations.
Find the submission skill: dpdisp-submit
Signals
- GitHub stars
- 138
- Forks
- 26
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
run-gauss- Source
- github.com/jinzhezenggroup/computational-chemistry-agent-skills