Display read-only status of local and remote compute resources.
npx skills add https://github.com/s-choung/Research-Skills --skill hpc-monitor
Please help me install this Agent Skill. Skill: hpc-monitor Source: https://github.com/s-choung/Research-Skills/tree/main/skills/hpc-monitor Command: npx skills add https://github.com/s-choung/Research-Skills --skill hpc-monitor
This Skill gives you a single, read-only snapshot of your local machine, SLURM GPU cluster, CPU server, and Matlantis jobs so you can quickly tell what is busy, queued, or idle without logging into each system separately.
Run the hpc-monitor skill to show my local machine, SLURM GPU cluster, CPU server, and Matlantis job status in one read-only snapshot.
High-intent search queries and answers about installing and using this skill.
You can check SLURM GPU queue status alongside local system resources by running a single read-only snapshot command that aggregates local CPU, RAM, and disk usage with remote cluster summaries into one unified display.
Monitoring remote HPC jobs and Matlantis papermill progress without individual logins is achieved via a unified status view that uses SSH and bash to gather read-only usage, queue, and process information across all systems.
Yes, you can track Matlantis papermill jobs in a read-only snapshot that lists active jobs, marks your own, and reports progress specifically only when a job has actually emitted a measurable value.
Yes, this HPC monitoring works on scheduler-less bare CPU servers by using SSH to highlight active compute processes and report system load directly without requiring SLURM.
No, you do not need administrative privileges to monitor remote SLURM clusters and CPU servers because the process uses standard Unix utilities over SSH to gather read-only usage and queue information without modifying system state.
Your HPC health check shows pending GPU jobs but no active CPU server processes because the read-only snapshot distinguishes between SLURM queue pressure and actual compute processes running on scheduler-less bare servers.
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