Get Available Resources
Run this before spinning up any heavy computation to see what you're working with. It detects CPU cores, GPUs (NVIDIA, AMD, or Apple Silicon), RAM, and disk space, then writes a JSON file with concrete recommendations like "use 6 workers for joblib" or "your dataset won't fit in memory, use Dask." The recommendations are context aware, so if you've got 64GB of RAM it won't nag you about out-of-core processing, and if you've got an M2 chip it'll suggest PyTorch with MPS backend instead of CUDA libraries. Honestly most useful when you're working across different machines or don't want to mentally calculate whether your 50GB dataset needs chunking on your 16GB laptop.
- skills.sh installs
- 2.1K
- GitHub stars
- 56.6K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add k-dense-ai/scientific-agent-skills --skill get-available-resources --agent claude-codeInstalls into .claude/skills of the current project.
Files
Get Available Resources
Build a conservative picture of resources available to the current process. Keep host inventory, process affinity, cgroup/container limits, scheduler allocation, and accelerator runtime usability separate.
Safety contract
Follow these rules:
- Run detection when the user requests it or a specific workload needs resource planning. Do not persist a fingerprint for every scientific task.
- Use stdout by default. Persist only when the user chooses an explicit generic local filename.
- Do not run stress tests, benchmarks, large allocations, write probes, device resets, driver installation, or clock/power changes.
- Do not dump the environment. Read only the named Slurm and accelerator variables implemented by the detector.
- Do not report hostnames, absolute paths, cgroup paths, job IDs, device UUIDs, PCI addresses, or raw visibility-variable values.
- Treat a missing observation as unknown. Never convert unknown to unlimited.
- Never infer that a visible host CPU, memory pool, or GPU is usable inside a scheduler allocation or container.
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- Repository
- github.com/k-dense-ai/scientific-agent-skills
- Categories
- Testing & QA, AI & Agent Building, Productivity & Planning
- First seen
- Jun 3, 2026
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