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remote-compute-ssh

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Evaluate and use Remote Compute before choosing where to run GPU, high-memory, parallel, batch, model-inference, bioinformatics, or other long-running scientific work; supports short remote commands and asynchronous jobs with automatic harvest and analysis.

resources/skills/remote-compute-ssh/SKILL.md

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This skill covers remote compute over SSH, including direct execution and Slurm submission:
listing hosts, creating handles, running short remote commands (callCommand), reading/writing host
knowledge docs, and the full async job lifecycle — submit → save `job_id` → read non-blocking
snapshots by that ID →
harvest → analysis turn → publish artifacts.

**Where host.compute runs:** `host.compute` lives ONLY on the control-plane REPL kernel — run
every example below with the `repl_execute` tool (JavaScript), the same kernel that hosts
`host.mcp`. The `python`/`r` data kernels have NO `host.compute` (SSH and approvals stay outside
the sandbox workspace); calling it from a python/r cell will fail with `host.compute is undefined`.

## External compute targets

Use the execution mode returned by `host.compute.listHosts()` to select the file layout and launch options. Each external job requires its own approval, including the bound target, resource request and frozen inputs. SSH-only remote paths and named SSH environments do not apply.
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