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xuzhougeng/wisp-science/skills/remote-compute-modal/SKILL.md

remote-compute-modal

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.

Source repository stars
560
Declared platforms
0
Static risk flags
0
Last source update
2026-07-28
Source checked
2026-07-28

Decision brief

What it does—and where it fits

Wisp does not currently implement a Modal ExecutionContext or Run backend. Only local, wsl:, and direct ssh: contexts can be passed to runincontext. Python receives no provider SDK, cloud credentials, image builder, or cloud-job handle.

Best for

  • Use when an existing workflow mentions Modal, BYOC cloud compute, provider images, or cloud GPU dispatch.

Not for

  • Tasks that require unconfirmed production actions or broad system permissions.
  • Environments where the pinned source and install steps cannot be inspected.

Compatibility matrix

Platform support, with evidence labels

PlatformStatusEvidenceWhat to check
CodexNot declaredNo explicit evidencePortability before use
Claude CodeNot declaredNo explicit evidencePortability before use
CursorNot declaredNo explicit evidencePortability before use
Gemini CLINot declaredNo explicit evidencePortability before use
Open the compatibility checker

Installation

Inspect first. Install second.

The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

Source-detected install commandSource
npx skills add https://github.com/xuzhougeng/wisp-science --skill "skills/remote-compute-modal"
Safe inspection promptEditorial

Inspect the Agent Skill "remote-compute-modal" from https://github.com/xuzhougeng/wisp-science/blob/95d2c13d1665d46a388b5bdc998dcce0d5ec2eee/skills/remote-compute-modal/SKILL.md at commit 95d2c13d1665d46a388b5bdc998dcce0d5ec2eee. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

Workflow

What the source asks the agent to do

  1. 01

    What to do

    1. Do not submit, build, monitor, or claim to reuse a Modal image. 2. 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…

    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 andKeep large inputs and model weights remote. Stage only small project scripts

Permission review

Static risk signals and limitations

No configured static risk pattern was detected

This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.

Evidence record

Why each signal appears

EvidenceSourceComputedTestedEditorial
SignalValueEvidence typeMeaning
Quality score59/100ComputedDocumentation, specificity, maintenance, and trust rules
Repository stars560SourceRepository attention, not individual Skill quality
Compatibility0 platformsSourceDeclared in the catalog source record
Usage guidecatalog recordEditorialGenerated or reviewed according to the visible evidence level

Pinned source

Provenance and original SKILL.md

Repository
xuzhougeng/wisp-science
Skill path
skills/remote-compute-modal/SKILL.md
Commit
95d2c13d1665d46a388b5bdc998dcce0d5ec2eee
License
AGPL-3.0
Collected
2026-07-28
Default branch
main
View the original SKILL.md

Modal 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

  1. Do not submit, build, monitor, or claim to reuse a Modal image.
  2. 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.
  3. Keep large inputs and model weights remote. Stage only small project scripts and configuration with input_paths.
  4. 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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