菜单
Companion CLIs for Runpod workflows — HuggingFace, GitHub, Docker, and AWS.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
runpod-flash — code-first serverless: write Python locally, run it on remote Runpod GPUs/CPUs with `flash dev` (hot-reload + live worker logs), then `flash deploy`. Use for @Endpoint/@remote functions, resource config, and debugging flash deployments. For CLI-only infra management use runpodctl or runpod-mcp.
Manage Runpod infrastructure — pods, serverless endpoints, jobs, templates, network volumes, container-registry auth, GPU/CPU catalog, and billing — via the Runpod MCP server's structured tool calls. Use when the Runpod MCP tools (create-pod, list-endpoints, …) are connected in this session, or to connect them (hosted OAuth or local npx). Prefer this over runpodctl for plain infra CRUD when MCP is available; use runpodctl for the terminal, Hub deploys, file transfer, or SSH setup.
Start here for any Runpod task — running GPU/CPU pods, deploying serverless endpoints, templates, network volumes, building images, or understanding how Runpod works. Routes the request to the right Runpod skill (runpod-mcp, runpodctl, flash, companion-clis, or runpod-usage). Use when it is unclear which Runpod skill applies.
How Runpod works and how to work it — pods vs serverless, GPU/VRAM selection, storage, building a container, networking, plus the agentic pod development loop (provision → ssh-exec → set up → poll readiness) and on-pod install hygiene (uv/apt). Use to answer "how does X work", "which GPU", "how do I build a container", or "how do I stand up a workload on a pod". Guidance, not a tool — execute with runpodctl, runpod-mcp, or flash.
Runpod CLI for managing GPU/CPU workloads from the terminal — pods, serverless endpoints, templates, network volumes, Hub deploys, models, SSH, and file transfer (send/receive). Use for terminal/CI/scripting, Hub browse/deploy, SSH setup, `doctor`, or when the Runpod MCP tools are not connected. For structured tool calls in an MCP-enabled session, prefer runpod-mcp.
| name | companion-clis |
| description | Companion CLIs for Runpod workflows — HuggingFace, GitHub, Docker, and AWS. |
| allowed-tools | Bash(hf:*), Bash(gh:*), Bash(docker:*), Bash(aws:*), Bash(ssh-keygen:*), Bash(ssh-add:*), Bash(ssh-agent:*) |
| compatibility | Linux, macOS, Windows |
| metadata | {"author":"runpod","version":"1.1.0"} |
| license | Apache-2.0 |
Four CLIs commonly needed alongside Runpod. Each has its own credentials + command reference in reference/ — plus a one-time <cli>-setup.md for install (only opened if the CLI isn't installed). Load only the one the task needs, not all four.
| CLI | Use it to | Full reference |
|---|---|---|
hf (HuggingFace) | Download models from the Hub to cache/bake into images | reference/huggingface.md |
gh (GitHub) | Manage worker repos + cut releases (Hub indexes releases) | reference/github.md |
docker | Build/validate/push images to Docker Hub for Runpod to pull | reference/docker.md |
aws (S3) | Read/write network-volume storage over Runpod's S3 API | reference/aws.md |
Each requires credentials before use. Read the per-tool reference for auth steps and commands; install is a separate one-time <cli>-setup.md.
If you are on Windows, install WSL2 before proceeding — it gives you the native Linux environment all these CLIs target. In PowerShell as Administrator, then restart:
wsl --install
Afterward open the Ubuntu app to finish setup, then follow the Linux instructions in each reference.
Download models locally so they're cached for a Docker build/run. Auth and hf download recipes: reference/huggingface.md (install: reference/huggingface-setup.md).
hf CLI, not pip install huggingface_hub (that's the older huggingface-cli with different syntax).hf auth login, or export HF_TOKEN=hf_... (env var wins over saved token).Manage worker repositories and cut releases. Auth and commands: reference/github.md (install + SSH-key setup: reference/github-setup.md).
gh release create.ssh-keygen -t ed25519) registers with both GitHub (gh ssh-key add) and HuggingFace (paste in browser).Build, validate, and push images to Docker Hub. Credentials and commands: reference/docker.md (install: reference/docker-setup.md).
--platform=linux/amd64 — Runpod runs on x86 Linux.latest — latest doesn't track the newest push, so workers can silently pull the wrong image.Access network-volume storage over Runpod's S3-compatible API (bucket name = network volume ID). Credentials, region rules, and commands: reference/aws.md (install: reference/aws-setup.md).
user_...), secret = S3 API key (rps_...).runpodctl/REST/GraphQL creates them — if they're not already in ~/.aws/credentials/env and S3 access is needed, stop and ask the user to generate them (Settings > S3 API Keys).--region DATACENTER --endpoint-url https://s3api-DATACENTER.runpod.io/ (datacenter = the volume's DC, not an AWS region).