How do I install the Runpodctl skill?

Run npx skillmds@latest add dvcrn/runpodctl in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Runpodctl safe to use?

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Which AI agents work with Runpodctl?

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Is Runpodctl free to use?

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Who published Runpodctl?

dvcrn (@dvcrn) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Runpodctl by dvcrn — Agent Skill

Name: Runpodctl
Rating: 4.2 (5 reviews)
Author: dvcrn

Runpodctl

Manage RunPod GPU pods, serverless endpoints, templates, network volumes, and models using the runpodctl CLI. Use when the user wants to list/create/stop/delete pods, manage serverless endpoints, check GPU availability, or manage RunPod resources.

dvcrn Updated Sep 8, 2026 32 repo stars

File contents

RunPod CLI Skill

Manage GPU pods, serverless endpoints, templates, network volumes, and models on RunPod.

Binary location: ~/.local/bin/runpodctl Spelling: "Runpod" (capital R). Command is runpodctl (lowercase).

Setup (first time)

If API key not yet configured:

~/.local/bin/runpodctl config set --apiKey YOUR_API_KEY

API key: https://runpod.io/console/user/settings

Check setup:

~/.local/bin/runpodctl user

Pods

~/.local/bin/runpodctl pod list               # List running pods
~/.local/bin/runpodctl pod list --all         # All pods including stopped
~/.local/bin/runpodctl pod get <pod-id>       # Pod details + SSH info
~/.local/bin/runpodctl pod create --template-id runpod-torch-v21 --gpu-id "NVIDIA RTX 4090"
~/.local/bin/runpodctl pod start <pod-id>
~/.local/bin/runpodctl pod stop <pod-id>
~/.local/bin/runpodctl pod restart <pod-id>
~/.local/bin/runpodctl pod delete <pod-id>

GPUs & Templates

~/.local/bin/runpodctl gpu list                          # Available GPUs + prices
~/.local/bin/runpodctl template list --type official     # Official templates
~/.local/bin/runpodctl template search pytorch           # Search templates
~/.local/bin/runpodctl template get <template-id>        # Template details

Serverless Endpoints

~/.local/bin/runpodctl serverless list
~/.local/bin/runpodctl serverless get <endpoint-id>
~/.local/bin/runpodctl serverless create --name "x" --template-id "tpl_abc"
~/.local/bin/runpodctl serverless update <endpoint-id> --workers-max 5
~/.local/bin/runpodctl serverless delete <endpoint-id>

Network Volumes

~/.local/bin/runpodctl network-volume list
~/.local/bin/runpodctl network-volume create --name "x" --size 100 --data-center-id "US-GA-1"
~/.local/bin/runpodctl network-volume delete <volume-id>

Models

~/.local/bin/runpodctl model list
~/.local/bin/runpodctl model list --name "llama"
~/.local/bin/runpodctl model add --name "my-model" --model-path ./model

Account

~/.local/bin/runpodctl user          # Account info + balance

Accessing pods

Exposed ports via: https://<pod-id>-<port>.proxy.runpod.net

Notes

Always use ~/.local/bin/runpodctl (full path) in exec commands — PATH may not be loaded in sandbox
Pod create requires either --template-id or --image
GPU IDs must match exactly (e.g., "NVIDIA RTX 4090", "NVIDIA A100 80GB PCIe")

---name: runpodctldescription: Manage RunPod GPU pods, serverless endpoints, templates, network volumes, and models using the runpodctl CLI. Use when the user wants to list/create/stop/delete pods, manage serverless endpoints, check GPU availability, or manage RunPod resources.---# RunPod CLI SkillManage GPU pods, serverless endpoints, templates, network volumes, and models on RunPod.> **Binary location:** `~/.local/bin/runpodctl`> **Spelling:** "Runpod" (capital R). Command is `runpodctl` (lowercase).## Setup (first time)If API key not yet configured:```bash~/.local/bin/runpodctl config set --apiKey YOUR_API_KEY```API key: https://runpod.io/console/user/settingsCheck setup:```bash~/.local/bin/runpodctl user```## Pods```bash~/.local/bin/runpodctl pod list # List running pods~/.local/bin/runpodctl pod list --all # All pods including stopped~/.local/bin/runpodctl pod get <pod-id> # Pod details + SSH info~/.local/bin/runpodctl pod create --template-id runpod-torch-v21 --gpu-id "NVIDIA RTX 4090"~/.local/bin/runpodctl pod start <pod-id>~/.local/bin/runpodctl pod stop <pod-id>~/.local/bin/runpodctl pod restart <pod-id>~/.local/bin/runpodctl pod delete <pod-id>```## GPUs & Templates```bash~/.local/bin/runpodctl gpu list # Available GPUs + prices~/.local/bin/runpodctl template list --type official # Official templates~/.local/bin/runpodctl template search pytorch # Search templates~/.local/bin/runpodctl template get <template-id> # Template details```## Serverless Endpoints```bash~/.local/bin/runpodctl serverless list~/.local/bin/runpodctl serverless get <endpoint-id>~/.local/bin/runpodctl serverless create --name "x" --template-id "tpl_abc"~/.local/bin/runpodctl serverless update <endpoint-id> --workers-max 5~/.local/bin/runpodctl serverless delete <endpoint-id>```## Network Volumes```bash~/.local/bin/runpodctl network-volume list~/.local/bin/runpodctl network-volume create --name "x" --size 100 --data-center-id "US-GA-1"~/.local/bin/runpodctl network-volume delete <volume-id>```## Models```bash~/.local/bin/runpodctl model list~/.local/bin/runpodctl model list --name "llama"~/.local/bin/runpodctl model add --name "my-model" --model-path ./model```## Account```bash~/.local/bin/runpodctl user # Account info + balance```## Accessing podsExposed ports via: `https://<pod-id>-<port>.proxy.runpod.net`## Notes- Always use `~/.local/bin/runpodctl` (full path) in exec commands — PATH may not be loaded in sandbox- Pod create requires either `--template-id` or `--image`- GPU IDs must match exactly (e.g., `"NVIDIA RTX 4090"`, `"NVIDIA A100 80GB PCIe"`)

Frequently asked questions