get-available-resources

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Detect host inventory and effective CPU, memory, disk, scheduler, container, and accelerator limits when a user asks for resource-aware planning or before a clearly resource-sensitive local workload. Produces a redacted JSON snapshot and conservative planning helpers without stress tests or assuming visible host hardware is usable.

AI & Automation 31,973 stars 3177 forks Updated today MIT

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Skill Content

# 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. The bundled detector uses only fixed executable/argument tuples, no shell, short timeouts, bounded stdout/stderr, and partial-failure warnings. ## Quick start Run from this skill directory. ### Ephemeral stdout snapshot ```bash python scripts/detect_resources.py ``` The command emits only JSON to stdout. Redirect it only when ordinary shell permissions are acceptable. ### Explicit private fil...

Details

Author
K-Dense-AI
Repository
K-Dense-AI/scientific-agent-skills
Created
9 months ago
Last Updated
today
Language
Python
License
MIT

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