What is remote-compute-ssh?
Submit recoverable SSH-direct research Runs with live progress cards and model-free monitoring.
xuzhougeng/wisp-science
Submit recoverable SSH-direct research Runs with live progress cards and model-free monitoring.
npx skills add https://github.com/xuzhougeng/wisp-science --skill "skills/remote-compute-ssh"Quick start
Install it or open the source, trigger it with a clear task, then follow the source workflow.
npx skills add https://github.com/xuzhougeng/wisp-science --skill "skills/remote-compute-ssh"Use remote-compute-ssh to help me with: [describe your task]. Before you begin, tell me what input you need, the steps you will follow, and the expected output.
No structured workflow was detected; follow the original SKILL.md below.
Continue to the workflowDirect answers
Submit recoverable SSH-direct research Runs with live progress cards and model-free monitoring.
It is relevant to workflows involving Operations, Research.
SkillSignal detected this source-specific command: npx skills add https://github.com/xuzhougeng/wisp-science --skill "skills/remote-compute-ssh". Inspect the repository and command before running it.
The upstream source does not declare a dedicated Agent platform.
Static analysis detected exec-script signals. Review the cited source lines before installing; these signals are not a security audit.
This page combines upstream documentation with deterministic repository, quality, and static-risk signals. It is not described as a manual test or security review.
SkillSignal brief
Submit recoverable SSH-direct research Runs with live progress cards and model-free monitoring.
Useful in these contexts
Core capabilities
Quality breakdown
Based on traceable docs and repository signals; stars are not treated as quality.
Compare before choosing
These links are selected from shared tasks, functions, stacks, platforms, and same-name variants. Compare the source owner, documentation, permissions, and maintenance signals.
Use when the user says "review the design", "check the UI", or wants a comprehensive UI/UX review. Uses a 7-phase methodology covering interaction, responsiveness, accessibility, and more.
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
Use NeuroKit2 to build or audit reproducible research workflows for physiological time-series preprocessing, event/interval analysis, multimodal alignment, variability, and complexity. Trigger when code imports neurokit2 or needs its current APIs, schemas, and method-aware validation—not for diagnosis or device validation.
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.
Use when the user says "plan a feature", "brainstorm", "explore this idea", or wants to go from idea to structured plan and roadmap.
Use this skill after choosing an ssh:<alias> execution context. Wisp owns the
job lifecycle locally: run_in_context creates the Run record, stages explicit
inputs with persisted byte progress, and starts a detached supervisor on the server.
The Runs panel and SQLite record remain authoritative if the conversation ends
or Wisp restarts.
run_in_context calls for read-only discovery such as
nvidia-smi -L, which python3, or module avail. Free-form shell SSH is
disabled. Use the interpreter path reported by the context probe; do not
assume a python alias exists when the probe found python3.run_in_context call. Include environment
activation in the command so the Run is reproducible.monitor_run exactly once with
the returned Run id. Wisp inserts a live card in the conversation, suspends
the tool without additional model calls, and resumes the same agent turn
with the terminal result. For fire-and-forget work, report the Run id and end
the turn instead.get_run only for one explicit status snapshot; never call it repeatedly
to wait. Use cancel_run when the user asks to stop.Never monitor a Run with Start-Sleep, sleep, ssh ... ps, kill -0, a
shell polling loop, nohup, background &, or hand-written PID files. Those
duplicate the control plane and can strand the agent turn. A transient SSH
error is stored as last_poll_error; do not resubmit, because Wisp retries the
same idempotent remote handle.
{
"context_id": "ssh:gpu-box",
"title": "Motif enrichment across 2,000 backgrounds",
"command": "source ~/miniforge3/etc/profile.d/conda.sh && conda activate genomics && python motif_enrichment_analysis.py",
"timeout_secs": 14400,
"input_paths": ["scripts/motif_enrichment_analysis.py"]
}
Then, when live monitoring is needed:
{ "run_id": "<id returned by run_in_context>" }
Pass that object to monitor_run once. The call may remain suspended for hours;
it does not consume model tokens while the Run Manager watches the job.
input_paths are project-relative local files. Wisp validates them, copies
them into an isolated inputs/ directory, and flattens them to their basenames.
The command starts in that directory, so the example above can use the staged
script by basename. Upload progress, throughput, and ETA appear in the Run card. For a large dataset already on
the server, reference its absolute remote path in command; do not copy it
back to the laptop just to send it out again.
A remote command or application exiting non-zero is normal exploration after a successful login. Read stderr, correct the command from the probed capabilities, and continue. Stop only when SSH rejects authentication or host trust; do not repeat a rejected login with guessed credentials or SSH options.
The control directory is ~/.wisp-science/runs/<run-id> and the command starts
in its inputs/ subdirectory. stdout and stderr are
tailed into the Run record. The SSH supervisor requires setsid, GNU-compatible
timeout, bash, and /proc; a missing prerequisite fails the Run instead of
running without a wall-time limit. Wisp maps the supervisor timeout marker to
timed_out.
SSH-direct v1 does not expand remote output globs or automatically download a
remote directory. Do not promise that relative output_specs will be
harvested. When the command writes a result to a known durable server path, it
may register that exact path as a remote Artifact reference:
{
"output_specs": [
{
"glob": "ssh://gpu-box/home/me/project/results/motif_enrichment_all.tsv",
"kind": "table",
"residency": "remote"
}
]
}
For a small result that must become local, wait until the Run is terminal, then transfer it as a separate quick operation and register the local file. Large outputs should remain remote references.
Use transfer_between_contexts for one exact remote file or directory. The
destination may be another selected SSH context or local. Never compose
nested ssh, scp, or rsync -e ssh inside run_in_context.
For a local download, set destination_context_id to local and provide the
exact new absolute local path. Ask the user when that path is unspecified.
Wisp stages the item beside the destination, never overwrites an existing
path, and removes partial staging data after failure or cancellation. Call
monitor_run once with the returned Run id.
When the user approves persistent A→B trust, call configure_ssh_trust first.
It creates a dedicated key on A, carries only the public key through Wisp,
installs it on B, and verifies the directed edge. The transfer then prefers
rsync when both servers provide it and falls back to scp. If the user does not
want server SSH configuration changed, select the relay route; Wisp downloads
to a private local temporary directory and uploads with B's separately stored
credentials.
cancel_run({"run_id":"..."}) changes an SSH Run to cancelling. Wisp
verifies the persisted token, PGID, and Linux process start time before sending
TERM to the remote process group; it records cancelled only after remote
confirmation. If the server is temporarily unreachable, the Run stays
cancelling and retry continues after reconnection or app restart.
Active statuses are submitted, running, and cancelling. Terminal statuses
are succeeded, failed, timed_out, cancelled, and lost. lost means
the remote token/control directory/process identity was definitively missing,
not merely that one SSH poll failed.
This implementation is SSH-direct and assumes a Linux-like server with sh,
bash, nohup, setsid, and /proc. Do not daemonize or create a new session
inside the job, because that escapes process-group cancellation.
Scheduler lifecycle is not implemented yet. Do not submit sbatch, qsub, or
bsub through this direct runner: the Run would only track the short submit
command, not the scheduler job. On a shared login node, ask the user for a
dedicated compute host or explain that scheduler-aware submit/poll/cancel is a
separate capability still needed.