"Runway hello world \u2014 AI video generation and creative AI platform.\n\
Scanned 9/2/2026
Install to Claude Code
npx -y skills add jeremylongshore/tons-of-skills-marketplace --skill runway-hello-world --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Runway Hello World?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/jeremylongshore-runway-hello-world-60938571)More formats (shields.io, HTML) on the badges page.
---
name: runway-hello-world
description: "Runway hello world \u2014 AI video generation and creative AI platform.\n\
Use when working with Runway for video generation, image editing, or creative AI.\n\
Trigger with phrases like \"runway hello world\", \"runway-hello-world\", \"AI video\
\ generation\".\n"
allowed-tools: Read, Write, Edit, Bash(pip:*), Bash(npm:*), Bash(curl:*), Grep
version: 1.4.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
tags:
- saas
- runway
- ai
- video-generation
- creative
compatibility: Designed for Claude Code
---
# Runway Hello World
## Overview
Generate your first AI video from a text prompt using Runway's Gen-3 Alpha model.
## Prerequisites
- Completed `runway-install-auth`
- API credits available in your Runway account
## Instructions
### Step 1: Text-to-Video Generation
```python
from runwayml import RunwayML
client = RunwayML()
# Create a text-to-video generation task
task = client.image_to_video.create(
model='gen3a_turbo',
prompt_text='A golden retriever running through a field of sunflowers, cinematic lighting, slow motion',
duration=5, # 5 or 10 seconds
ratio='16:9', # 16:9 or 9:16
)
print(f"Task created: {task.id}")
```
### Step 2: Poll for Completion
```python
import time
# The SDK has a built-in helper for polling
task_result = client.tasks.retrieve(task.id)
# Or poll manually
while task_result.status not in ('SUCCEEDED', 'FAILED'):
time.sleep(5)
task_result = client.tasks.retrieve(task.id)
print(f" Status: {task_result.status}")
if task_result.status == 'SUCCEEDED':
print(f"Video URL: {task_result.output[0]}")
else:
print(f"Failed: {task_result.failure}")
```
### Step 3: Download the Video
```python
import urllib.request
if task_result.status == 'SUCCEEDED':
video_url = task_result.output[0]
urllib.request.urlretrieve(video_url, 'output.mp4')
print("Video saved to output.mp4")
```
### Step 4: Using the Built-in Wait Helper
```python
# Simpler approach — SDK polls automatically
task = client.image_to_video.create(
model='gen3a_turbo',
prompt_text='Ocean waves crashing on rocky cliffs at sunset, aerial view',
duration=5,
)
# Wait for completion (default timeout: 10 minutes)
result = task.wait_for_task_output()
print(f"Video: {result.output[0]}")
```
## Output
- Video generation task created
- Task polled until completion
- Generated video URL retrieved
- Video downloaded to local file
## Error Handling
| Error | Cause | Solution |
|-------|-------|----------|
| Task `FAILED` | Content policy violation | Adjust prompt to comply with content policy |
| `402 Insufficient credits` | No API credits | Add credits at dev.runwayml.com |
| Timeout | Generation taking too long | Increase timeout or use shorter duration |
| Low quality output | Prompt too vague | Add style keywords: "cinematic", "4K", "professional" |
## Resources
- [API Getting Started](https://docs.dev.runwayml.com/guides/using-the-api/)
- [API Reference](https://docs.dev.runwayml.com/api/)
- [Input Parameters](https://docs.dev.runwayml.com/assets/inputs/)
## Next Steps
Advanced text-to-video: `runway-core-workflow-a`
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!