Files
feynman/skills/runpod-compute/SKILL.md
Advait Paliwal 7024a86024 Replace Pi tool registrations with skills and CLI integration
- Remove all manually registered Pi tools (alpha_search, alpha_get_paper,
  alpha_ask_paper, alpha_annotate_paper, alpha_list_annotations,
  alpha_read_code, session_search, preview_file) and their wrappers
  (alpha.ts, preview.ts, session-search.ts, alpha-tools.test.ts)
- Add Pi skill files for alpha-research, session-search, preview,
  modal-compute, and runpod-compute in skills/
- Sync skills to ~/.feynman/agent/skills/ on startup via syncBundledAssets
- Add node_modules/.bin to Pi subprocess PATH so alpha CLI is accessible
- Add /outputs extension command to browse research artifacts via dialog
- Add Modal and RunPod as execution environments in /replicate and
  /autoresearch prompts
- Remove redundant /alpha-login /alpha-logout /alpha-status REPL commands
  (feynman alpha CLI still works)
- Update README, researcher agent, metadata, and website docs

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-25 00:38:45 -07:00

49 lines
1.5 KiB
Markdown

---
name: runpod-compute
description: Provision and manage GPU pods on RunPod for long-running experiments. Use when the user needs persistent GPU compute with SSH access, large datasets, or multi-step experiments.
---
# RunPod Compute
Use `runpodctl` CLI for persistent GPU pods with SSH access.
## Setup
```bash
brew install runpod/runpodctl/runpodctl # macOS
runpodctl config --apiKey=YOUR_KEY
```
## Commands
| Command | Description |
|---------|-------------|
| `runpodctl create pod --gpuType "NVIDIA A100 80GB PCIe" --imageName "runpod/pytorch:2.4.0-py3.11-cuda12.4.1-devel-ubuntu22.04" --name experiment` | Create a pod |
| `runpodctl get pod` | List all pods |
| `runpodctl stop pod <id>` | Stop (preserves volume) |
| `runpodctl start pod <id>` | Resume a stopped pod |
| `runpodctl remove pod <id>` | Terminate and delete |
| `runpodctl gpu list` | List available GPU types and prices |
| `runpodctl send <file>` | Transfer files to/from pods |
| `runpodctl receive <code>` | Receive transferred files |
## SSH access
```bash
ssh root@<IP> -p <PORT> -i ~/.ssh/id_ed25519
```
Get connection details from `runpodctl get pod <id>`. Pods must expose port `22/tcp`.
## GPU types
`NVIDIA GeForce RTX 4090`, `NVIDIA RTX A6000`, `NVIDIA A40`, `NVIDIA A100 80GB PCIe`, `NVIDIA H100 80GB HBM3`
## When to use
- Long-running experiments needing persistent state
- Large dataset processing
- Multi-step work with SSH access between iterations
- Always stop or remove pods after experiments
- Check availability: `command -v runpodctl`