Remote Compute Modal
Run GPU jobs on the user's own Modal account via host.compute.create('byoc:modal', ...).
Install
npx skills add HughYau/AcademicForge --skill remote-compute-modal -g -a claude-code -y- Repository
- HughYau/AcademicForge2.6k
- Category
- Media
- Updated
- 2mo ago
- License
- Apache-2.0
- Context cost
- Mediumabout 3,000 tokens
- Runs scripts
- Yes, review before use
What it does
Run GPU jobs on the user's own Modal account via host.compute.create('byoc:modal', ...). Covers the create→submit→wait_for_notification flow, the compute_provider kernel for env setup, image/volume resolution, and the two approval cards. Load once you've decided to dispatch to Modal.
You're dispatching to the user's Modal account: containers spin up in Modal's cloud, on hardware you name in plain terms (gpu/cpu/memory/timeout), under their workspace, on their bill. That's the reason there are two approval cards rather than one, and the reason the env-setup surface is a separate kernel rather than something you can call inline from the control-plane kernel: each card is the user consenting to a specific, bounded use of their credential, and the architecture keeps those grants legible by keeping the surfaces apart.
If compute.create('byoc:modal', …) returns unknown provider 'byoc:modal',
Modal isn't enabled in this install, ask the user to enable it under
Settings → Compute → Modal (or surface the prompt; you can't enable it for
them).
For first-time environment setup, see env-setup.md in this skill
directory, it walks through driving the compute_provider kernel to
build and record images.
Two timeouts, one timeline
Modal has two deadline timers. Both live INSIDE the sandbox, and neither can cost you the outputs of a job that ran. The timeline every job runs on:
