القائمة
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.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Search, read, and query research papers via the `alpha` CLI (alphaXiv-backed). Use when the user asks about academic papers, wants to find research on a topic, needs to read a specific paper, ask questions about a paper, inspect a paper's code repository, or manage paper annotations.
Autonomous experiment loop that tries ideas, measures results, keeps what works, and discards what doesn't. Use when the user asks to optimize a metric, run an experiment loop, improve performance iteratively, or automate benchmarking.
Contribute changes to the Feynman repository itself. Use when the task is to add features, fix bugs, update prompts or skills, change install or release behavior, improve docs, or prepare a focused PR against this repo.
Run a thorough, source-heavy investigation on any topic. Use when the user asks for deep research, a comprehensive analysis, an in-depth report, or a multi-source investigation. Produces a cited research brief with provenance tracking.
Execute research code inside isolated Docker containers for safe replication, experiments, and benchmarks. Use when the user selects Docker as the execution environment or asks to run code safely, in isolation, or in a sandbox.
Explain research, papers, or technical ideas in plain English with minimal jargon, concrete analogies, and clear takeaways. Use when the user says "ELI5 this", asks for a simple explanation of a paper or research result, wants jargon removed, or asks what something technically dense actually means.
| 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. |
Use runpodctl CLI for persistent GPU pods with SSH access.
brew install runpod/runpodctl/runpodctl # macOS
runpodctl config --apiKey=YOUR_KEY
| 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 root@<IP> -p <PORT> -i <path-to-ephemeral-runpod-key>
Get connection details from runpodctl get pod <id>. Pods must expose port 22/tcp.
NVIDIA GeForce RTX 4090, NVIDIA RTX A6000, NVIDIA A40, NVIDIA A100 80GB PCIe, NVIDIA H100 80GB HBM3
command -v runpodctlThis skill inherits the SeaBridgeAI /goal default protocol. Frame the work with a persistent goal, Definition of Done, validation plan, risks, dependencies, expected artifacts, and completion evidence. Do not claim completion until the DoD is validated or a hard blocker is documented.
Canonical protocol: C:\Users\adelm\SeaBridgeAI\everything-claude-code\protocols\GOAL_PROTOCOL.md