companion-clis

Companion CLIs

For creating or improving a documented template project, start with runpod-build-template; return here for the selected CLI operation.

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.

If the request starts with an imported ComfyUI workflow whose model filenames lack verified URLs or hashes, route to the ComfyUI model-repair guide in runpod-templates. Return here when the exact Hugging Face repository/file is already known and the task is simply to download, cache, or bake that artifact.

Each requires credentials before use. Read the per-tool reference for auth steps and commands; install is a separate one-time <cli>-setup.md.

These CLIs are usually one step inside a larger job. For the whole job the verified example is in runpod/golden-paths/README.md — baking vs mounting a model (25), building a minimal image (22), or moving data to a network volume (07).

These are third-party CLIs on their own release trains, so `<cli> --help` is authoritative for flags and subcommands — the references here cover the Runpod-specific usage and the traps, not the tool's full surface. Check --help before reporting that one of them cannot do something.

Windows: choose the shell, then set up WSL2 if needed

Check existing native, WSL2 or remote tools before installing another copy. The Windows hf and gh setup recipes in this skill use WSL2 and their Linux installers. If choosing that route and WSL2 is missing, run this in PowerShell as Administrator, then restart if prompted:

wsl --install

Afterward open the Ubuntu app to finish setup, then follow the Linux instructions in each reference. Keep commands, credentials and paths in the selected environment. File authoring alone does not require installing these CLIs.

HuggingFace CLI

Download models locally so they're cached for a Docker build/run. Auth and hf download recipes: [reference/huggingface.md](reference/huggingface.md) (install: reference/huggingface-setup.md).

• Use the standalone hf CLI, not pip install huggingface_hub (that's the older huggingface-cli with different syntax).
• Auth via hf auth login, or export HF_TOKEN=hf_... (env var wins over saved token).

GitHub CLI

Manage worker repositories and cut releases. Auth and commands: [reference/github.md](reference/github.md) (install + SSH-key setup: reference/github-setup.md).

• The Hub indexes releases, not commits — every Hub listing update needs a new gh release create.
• One SSH key (ssh-keygen -t ed25519) registers with both GitHub (gh ssh-key add) and HuggingFace (paste in browser).

Docker

Build, validate, and push images to Docker Hub. Credentials and commands: [reference/docker.md](reference/docker.md) (install: reference/docker-setup.md).

• Always build `--platform=linux/amd64` — Runpod runs on x86 Linux.
• Always use explicit semantic tags; never `latest` — latest doesn't track the newest push, so workers can silently pull the wrong image.
• Docker Hub auth uses a personal access token, not your password. For private images, register the credential once in Console → Container Registry Settings.

AWS CLI

Access network-volume storage over Runpod's S3-compatible API (bucket name = network volume ID). Credentials, region rules, and commands: [reference/aws.md](reference/aws.md) (install: reference/aws-setup.md).

• Runpod's S3 API, not AWS: access key = Runpod user id (user_...), secret = S3 API key (rps_...).
• S3 API keys are Console-only. No 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).
• Every command needs --region DATACENTER --endpoint-url https://s3api-DATACENTER.runpod.io/ (datacenter = the volume's DC, not an AWS region).
• For large/many-file transfers with reliable resume, see reference/aws.md → optional resumable volume transfers.