# Runway Core Workflow B

> Runway core workflow b — AI video generation and creative AI platform. Use when working with Runway for video generation, image editing, or creative AI. Trigger with phrases like "runway core workflow b", "runway-core-workflow-b", "AI video generation".

- Skill: `gabrielmoreira/runway-core-workflow-b` (Agent Skill)
- Install (CLI): `npx skillmds@latest add gabrielmoreira/runway-core-workflow-b`
- Raw SKILL.md: https://api.skillmd.com/api/skills/gabrielmoreira/runway-core-workflow-b/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Productivity
- License: MIT
- Author: gabrielmoreira (https://skillmd.com/u/gabrielmoreira)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/gabrielmoreira/runway-core-workflow-b

---

# Runway Core Workflow B

## Overview

Image-to-video and video-to-video generation: animate still images and transform existing videos.

## Prerequisites

- Completed `runway-core-workflow-a`

## Instructions

### Step 1: Image-to-Video

```python
from runwayml import RunwayML
client = RunwayML()

# Animate a still image
task = client.image_to_video.create(
    model='gen3a_turbo',
    prompt_image='https://your-cdn.com/landscape.jpg',  # URL to source image
    prompt_text='Camera slowly pans right revealing mountains, gentle wind in trees',
    duration=5,
)
result = task.wait_for_task_output()
print(f"Animated video: {result.output[0]}")
```

### Step 2: Image-to-Video with Data URI

```python
import base64

# Load local image as data URI
with open('photo.jpg', 'rb') as f:
    image_data = base64.b64encode(f.read()).decode()
    data_uri = f"data:image/jpeg;base64,{image_data}"

task = client.image_to_video.create(
    model='gen3a_turbo',
    prompt_image=data_uri,
    prompt_text='Subtle motion, gentle camera push in, atmospheric lighting',
    duration=5,
)
```

### Step 3: Video-to-Video (Style Transfer)

```python
# Transform an existing video with a new style
task = client.video_to_video.create(
    model='gen3a_turbo',
    prompt_video='https://your-cdn.com/input-video.mp4',
    prompt_text='Transform to watercolor painting style, soft colors, artistic brushstrokes',
)
result = task.wait_for_task_output()
print(f"Styled video: {result.output[0]}")
```

### Step 4: Image Specifications

```text
Supported formats: JPEG, PNG, WebP
Supported resolutions:
  - Gen-3 Alpha Turbo: 1280x768 or 768x1280
  - Input images are automatically resized
Max file size: 16MB (URL), varies for data URI
```

## Output

- Still images animated with motion prompts
- Local images encoded as data URIs
- Videos restyled with text prompts
- Proper image format handling

## Error Handling

| Error | Cause | Solution |
|-------|-------|----------|
| `400 Invalid image` | Unsupported format | Use JPEG, PNG, or WebP |
| `413 Image too large` | File exceeds limit | Resize to under 16MB |
| Poor animation quality | Prompt doesn't describe motion | Add camera/motion keywords |
| Style transfer too subtle | Weak prompt | Be more specific about target style |

## Resources

- [Runway API Reference](https://docs.dev.runwayml.com/api/)
- [Input Parameters](https://docs.dev.runwayml.com/assets/inputs/)
- [SDKs](https://docs.dev.runwayml.com/api-details/sdks/)

## Next Steps

Error handling: `runway-common-errors`