Skip to content
Back to skills

ASB04 003158

ASecurity

Provision, manage, and terminate RunPod GPU instances for LLM training. Use when user says "spin up GPU", "create RunPod instance", "terminate pod", "check GPU status", "provision training server", or needs cloud GPU resources.

  • 4 stars
  • 0 votes
  • 0 copies
  • 0 views
  • Added November 11, 2026
ai-agentsbashgitapi

Works with

  • api

Security analysis

A100/100

Scanned November 11, 2026

npx -y skills add Frank-Masciopinto/ironheights --skill ASB04_003158 --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of ASB04 003158?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for ASB04 003158
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/frank-masciopinto-asb04-003158/badge)](https://www.skillsdirectory.com/skills/frank-masciopinto-asb04-003158)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: runpod-ops
description: >
  Provision, manage, and terminate RunPod GPU instances for LLM training. Use when
  user says "spin up GPU", "create RunPod instance", "terminate pod", "check GPU status",
  "provision training server", or needs cloud GPU resources.
allowed-tools: Bash, Read
triggers:
  - spin up GPU
  - create RunPod
  - terminate pod
  - GPU instance
  - provision server
  - check pod status
  - RunPod management
metadata:
  short-description: RunPod GPU instance management
  project-path: $RUNPOD_OPS_REPO (set via env; defaults to GitHub clone)
---

# RunPod Operations Skill

Manage RunPod GPU instances for LLM training and inference.

**Self-contained skill** - auto-installs via `uv run` from git (no pre-installation needed).

## Quick Start

```bash
# Via wrapper (auto-installs from GitHub on demand)
.agents/skills/runpod-ops/run.sh list-instances

# Create an instance
.agents/skills/runpod-ops/run.sh create-instance 70B --hours 4

# Monitor an instance
.agents/skills/runpod-ops/run.sh monitor <pod-id>

# Terminate an instance
.agents/skills/runpod-ops/run.sh terminate <pod-id>
```

## Commands

| Command | Purpose |
|---------|---------|
| `create-instance` | Create GPU pod optimized for model size |
| `list-instances` | Show all running pods with status/cost |
| `monitor` | Live monitoring of pod metrics |
| `terminate` | Safely terminate a pod |
| `estimate-cost` | Estimate training cost before creating |
| `optimize` | Find optimal GPU config using benchmarks |
| `start-training` | Start a training job on RunPod |
| `serve` | Start inference server on RunPod |

## Examples

### Create Instance
.agents/skills/runpod-ops/run.sh create-instance 70B --hours 4
# Returns: pod_id=abc123
```

### Estimate Cost
```bash
.agents/skills/runpod-ops/run.sh estimate-cost 70B --hours 8
```

### Monitor Instance
```bash
.agents/skills/runpod-ops/run.sh monitor <pod-id>
```

### Terminate Instance
```bash
.agents/skills/runpod-ops/run.sh terminate <pod-id>
```

## Environment Variables

| Variable | Required | Description |
|----------|----------|-------------|
| `RUNPOD_API_KEY` | Yes | RunPod API key |

## Typical Workflow

```bash
# 1. Estimate cost
.agents/skills/runpod-ops/run.sh estimate-cost 70B --hours 8

# 2. Create pod
.agents/skills/runpod-ops/run.sh create-instance 70B --hours 8

# 3. Monitor or SSH into pod
.agents/skills/runpod-ops/run.sh monitor <pod-id>

# 4. Run training...

# 5. Terminate when done
.agents/skills/runpod-ops/run.sh terminate <pod-id>
```

## Integration with Memory

After training completes, log the lesson:
```bash
memory-agent learn \
  --problem "Training Qwen3-70B on RunPod" \
  --solution "Used A100-80GB, 8 hours, cost $24.72. Config: lr=2e-5, batch=4"
```

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

View all in ai-agents →

Comments

Loading comments…

Newsletter

Get the weekly list of safe new skills, and the ones we pulled.