Remote Compute Modal Agent Skill
Explain Wisp's current Modal boundary and migrate a requested Modal workload to a supported direct SSH Run when possible. Use when an existing workflow mentions Modal, BYOC cloud compute, provider images, or cloud GPU dispatch.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/xuzhougeng/wisp-science --skill remote-compute-modalThe instruction itself
2 sections, as written by the authorModal compute boundary
Wisp does not currently implement a Modal ExecutionContext or Run backend.
Only local, wsl:<distro>, and direct ssh:<alias> contexts can be passed to
run_in_context. Python receives no provider SDK, cloud credentials, image
builder, or cloud-job handle.
What to do
- Do not submit, build, monitor, or claim to reuse a Modal image.
- If the workload can run on a user-controlled Linux GPU host, select and
Probe an SSH context, load compute-env-setup, build the required user-space
environment there, then load remote-compute-ssh and submit a persisted Run.
- Keep large inputs and model weights remote. Stage only small project scripts
and configuration with input_paths.
- If no suitable SSH context exists, explain that the workload cannot be
dispatched by this Wisp build. Do not offer an untracked local SDK call as a
substitute.
A future Modal integration must add a typed execution context and a mockable
Run backend implementing resource requests, environment/image references,
keyring-backed secret binding, submit, poll, cancel, recovery, and output
harvest. That belongs in Rust, not in a Python sidecar.
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How to use it
Take xuzhougeng/remote-compute-modal from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.