compute-environment

name	compute-environment
description	Route long-running research compute across available backends — currently local sandbox and Modal remote, generic enough that AWS/GCP/CloudLab can be added without changing this skill. Use for training, fine-tuning, GPU jobs, large data processing, or scripts that may run for many minutes.
category	Compute
tags	["compute","gpu","modal","training"]
triggers	["train model","gpu","remote compute","modal","run script","long-running","fine-tune"]
license	MIT
metadata	{"skill-author":"Research Copilot"}

Compute Environment

Use compute tools for scripts that are long-running, resource-heavy, or need progress monitoring. Each backend (local, modal, …) is registered with capabilities and a current availability status; the agent picks the right one by calling list_compute_backends and compute_plan with the chosen backend.

Backend routing

Default heuristic:

Use local when	Use Modal when
Quick / exploratory / file wrangling	Needs NVIDIA CUDA GPUs
MLX/Metal on Apple Silicon	Long training / fine-tuning (>30 min locally)
Likely finishes in <30 minutes	Datasets / models too large for the local machine

For backend-specific patterns (script template, GPU choice, cost awareness, sandbox vs container), consult the per-backend skill:

• compute-local — local sandbox tips, smoke-test patterns, sandbox choice
• compute-modal — Modal script template, GPU rate awareness, image declaration

Tool surface

Generic:

• list_compute_backends() — see what's registered and which are available right now
• compute_plan({ backend, command, task_description?, script_path?, timeout_minutes? }) — analyze + queue (or auto-approve when backend doesn't require approval)

Per-backend (replaces <backend> with the toolPrefix returned by list_compute_backends):

• <backend>_execute({ plan_id, … }) — kick off the plan
• <backend>_wait({ run_id, timeout_seconds? }) — block until terminal or timeout
• <backend>_status({ run_id }) — non-blocking snapshot
• <backend>_stop({ run_id }) — cancel (some backends don't support stop)

Approval gate

For backends with capabilities.requiresApproval: true (Modal today, AWS/cloud likely), compute_plan queues the plan and the response carries requires_approval: true plus a message telling the user to approve in the Compute tab. Don't loop on <backend>_execute — call it once; if it returns waiting_for_approval: true, surface the message to the user and stop.

The user can also globally force approval on every backend via Settings → Compute → "Require approval for every compute backend".

Cost awareness

For backends with capabilities.hasCost: true, compute_plan returns a cost_estimate with estimatedTotalUsd, hourlyRateUsd, and coverage. A coverage: 'lower_bound' flag means only one cost dimension is modeled (today Modal models GPU-time only) — actual bills can be higher. Each backend's auto-kill threshold lives in Settings → Compute.

Progress lines

For any backend, scripts emit progress lines on stdout in the form:

##PROGRESS## {"step": 1, "total": 3, "phase": "setup", "percentage": 33}

The runner parses these and surfaces them through <backend>_status / <backend>_wait output so the agent can report fine-grained progress.