| 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 choicecompute-modal — Modal script template, GPU rate awareness, image declaration
Tool surface
Generic:
list_compute_backends() — see what's registered and which are available right nowcompute_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.
