Individual skill

tensorpool-gpu-cloud

Safely inspect and operate TensorPool GPU clusters and jobs using the current tp CLI, with explicit approval before any billable or destructive action.

backend/cli/skills/cloud-compute/tensorpool/SKILL.md

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# TensorPool GPU Cloud

Use this skill for TensorPool cluster, job, and storage workflows. Treat provider availability, instance names, quotas, and prices as live data: inspect them at execution time and never rely on values copied into a skill.

## OpenScience credential boundary

- A key saved in **Customize > Compute > TensorPool** is encrypted control-plane data. It is not exported into Bash, Task, notebooks, kernels, plugins, or MCP servers.
- Use `provider_compute` with `account`, `list_resources`, `resource_status`, `list_jobs`, or `job_status` for live reads. OpenScience selects the exact reviewed `tp` argv, admits the key only to that isolated child, and marks `last_used` only after success.
- **Test connection** uses the same boundary for exactly `tp --no-input me`.
- The saved key is admitted only when **Test connection** approves a root/admin-managed, non-writable `tp` executable. A normal user-owned pip, pipx, or Homebrew install is credential-only and cannot be used by `provider_compute`; use an administrator-managed install or wait for a managed/native adapter.
- Never print, echo, persist, or ask the user to paste a saved key into chat.
- A generic agent shell can use `tp` only when the user has independently authenticated that shell. The saved credential cannot create, submit, edit, attach, destroy, or otherwise mutate resources; do not ask the user to weaken this boundary.

## Current CLI contract