ai-content-pipeline

Build multi-step AI content creation pipelines combining image, video, audio, and text. Workflow examples: generate image -> animate -> add voiceover -> merge with music. Tools: FLUX, Veo, Kokoro TTS, OmniHuman, media merger, upscaling. Use for: YouTube videos, social media content, marketing materials, automated content. Triggers: content pipeline, ai workflow, content creation, multi-step ai, content automation, ai video workflow, generate and edit, ai content factory, automated content creation, ai production pipeline, media pipeline, content at scale

242 stars

Best use case

ai-content-pipeline is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. Build multi-step AI content creation pipelines combining image, video, audio, and text. Workflow examples: generate image -> animate -> add voiceover -> merge with music. Tools: FLUX, Veo, Kokoro TTS, OmniHuman, media merger, upscaling. Use for: YouTube videos, social media content, marketing materials, automated content. Triggers: content pipeline, ai workflow, content creation, multi-step ai, content automation, ai video workflow, generate and edit, ai content factory, automated content creation, ai production pipeline, media pipeline, content at scale

Build multi-step AI content creation pipelines combining image, video, audio, and text. Workflow examples: generate image -> animate -> add voiceover -> merge with music. Tools: FLUX, Veo, Kokoro TTS, OmniHuman, media merger, upscaling. Use for: YouTube videos, social media content, marketing materials, automated content. Triggers: content pipeline, ai workflow, content creation, multi-step ai, content automation, ai video workflow, generate and edit, ai content factory, automated content creation, ai production pipeline, media pipeline, content at scale

Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.

Practical example

Example input

Use the "ai-content-pipeline" skill to help with this workflow task. Context: Build multi-step AI content creation pipelines combining image, video, audio, and text.
Workflow examples: generate image -> animate -> add voiceover -> merge with music.
Tools: FLUX, Veo, Kokoro TTS, OmniHuman, media merger, upscaling.
Use for: YouTube videos, social media content, marketing materials, automated content.
Triggers: content pipeline, ai workflow, content creation, multi-step ai,
content automation, ai video workflow, generate and edit, ai content factory,
automated content creation, ai production pipeline, media pipeline, content at scale

Example output

A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.

When to use this skill

  • Use this skill when you want a reusable workflow rather than writing the same prompt again and again.

When not to use this skill

  • Do not use this when you only need a one-off answer and do not need a reusable workflow.
  • Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/ai-content-pipeline/SKILL.md --create-dirs "https://raw.githubusercontent.com/aiskillstore/marketplace/main/skills/inference-sh/ai-content-pipeline/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/ai-content-pipeline/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How ai-content-pipeline Compares

Feature / Agentai-content-pipelineStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Build multi-step AI content creation pipelines combining image, video, audio, and text. Workflow examples: generate image -> animate -> add voiceover -> merge with music. Tools: FLUX, Veo, Kokoro TTS, OmniHuman, media merger, upscaling. Use for: YouTube videos, social media content, marketing materials, automated content. Triggers: content pipeline, ai workflow, content creation, multi-step ai, content automation, ai video workflow, generate and edit, ai content factory, automated content creation, ai production pipeline, media pipeline, content at scale

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# AI Content Pipeline

Build multi-step content creation pipelines via [inference.sh](https://inference.sh) CLI.

## Quick Start

```bash
curl -fsSL https://cli.inference.sh | sh && infsh login

# Simple pipeline: Generate image -> Animate to video
infsh app run falai/flux-dev --input '{"prompt": "portrait of a woman smiling"}' > image.json
infsh app run falai/wan-2-5 --input '{"image_url": "<url-from-previous>"}'
```

## Pipeline Patterns

### Pattern 1: Image -> Video -> Audio

```
[FLUX Image] -> [Wan 2.5 Video] -> [Foley Sound]
```

### Pattern 2: Script -> Speech -> Avatar

```
[LLM Script] -> [Kokoro TTS] -> [OmniHuman Avatar]
```

### Pattern 3: Research -> Content -> Distribution

```
[Tavily Search] -> [Claude Summary] -> [FLUX Visual] -> [Twitter Post]
```

## Complete Workflows

### YouTube Short Pipeline

Create a complete short-form video from a topic.

```bash
# 1. Generate script with Claude
infsh app run openrouter/claude-sonnet-45 --input '{
  "prompt": "Write a 30-second script about the future of AI. Make it engaging and conversational. Just the script, no stage directions."
}' > script.json

# 2. Generate voiceover with Kokoro
infsh app run infsh/kokoro-tts --input '{
  "text": "<script-text>",
  "voice": "af_sarah"
}' > voice.json

# 3. Generate background image with FLUX
infsh app run falai/flux-dev --input '{
  "prompt": "Futuristic city skyline at sunset, cyberpunk aesthetic, 4K wallpaper"
}' > background.json

# 4. Animate image to video with Wan
infsh app run falai/wan-2-5 --input '{
  "image_url": "<background-url>",
  "prompt": "slow camera pan across cityscape, subtle movement"
}' > video.json

# 5. Add captions (manually or with another tool)

# 6. Merge video with audio
infsh app run infsh/media-merger --input '{
  "video_url": "<video-url>",
  "audio_url": "<voice-url>"
}'
```

### Talking Head Video Pipeline

Create an AI avatar presenting content.

```bash
# 1. Write the script
infsh app run openrouter/claude-sonnet-45 --input '{
  "prompt": "Write a 1-minute explainer script about quantum computing for beginners."
}' > script.json

# 2. Generate speech
infsh app run infsh/kokoro-tts --input '{
  "text": "<script>",
  "voice": "am_michael"
}' > speech.json

# 3. Generate or use a portrait image
infsh app run falai/flux-dev --input '{
  "prompt": "Professional headshot of a friendly tech presenter, neutral background, looking at camera"
}' > portrait.json

# 4. Create talking head video
infsh app run bytedance/omnihuman-1-5 --input '{
  "image_url": "<portrait-url>",
  "audio_url": "<speech-url>"
}' > talking_head.json
```

### Product Demo Pipeline

Create a product showcase video.

```bash
# 1. Generate product image
infsh app run falai/flux-dev --input '{
  "prompt": "Sleek wireless earbuds on white surface, studio lighting, product photography"
}' > product.json

# 2. Animate product reveal
infsh app run falai/wan-2-5 --input '{
  "image_url": "<product-url>",
  "prompt": "slow 360 rotation, smooth motion"
}' > product_video.json

# 3. Upscale video quality
infsh app run falai/topaz-video-upscaler --input '{
  "video_url": "<product-video-url>"
}' > upscaled.json

# 4. Add background music
infsh app run infsh/media-merger --input '{
  "video_url": "<upscaled-url>",
  "audio_url": "https://your-music.mp3",
  "audio_volume": 0.3
}'
```

### Blog to Video Pipeline

Convert written content to video format.

```bash
# 1. Summarize blog post
infsh app run openrouter/claude-haiku-45 --input '{
  "prompt": "Summarize this blog post into 5 key points for a video script: <blog-content>"
}' > summary.json

# 2. Generate images for each point
for i in 1 2 3 4 5; do
  infsh app run falai/flux-dev --input "{
    \"prompt\": \"Visual representing point $i: <point-text>\"
  }" > "image_$i.json"
done

# 3. Animate each image
for i in 1 2 3 4 5; do
  infsh app run falai/wan-2-5 --input "{
    \"image_url\": \"<image-$i-url>\"
  }" > "video_$i.json"
done

# 4. Generate voiceover
infsh app run infsh/kokoro-tts --input '{
  "text": "<full-script>",
  "voice": "bf_emma"
}' > narration.json

# 5. Merge all clips
infsh app run infsh/media-merger --input '{
  "videos": ["<video1>", "<video2>", "<video3>", "<video4>", "<video5>"],
  "audio_url": "<narration-url>",
  "transition": "crossfade"
}'
```

## Pipeline Building Blocks

### Content Generation

| Step | App | Purpose |
|------|-----|---------|
| Script | `openrouter/claude-sonnet-45` | Write content |
| Research | `tavily/search-assistant` | Gather information |
| Summary | `openrouter/claude-haiku-45` | Condense content |

### Visual Assets

| Step | App | Purpose |
|------|-----|---------|
| Image | `falai/flux-dev` | Generate images |
| Image | `google/imagen-3` | Alternative image gen |
| Upscale | `falai/topaz-image-upscaler` | Enhance quality |

### Animation

| Step | App | Purpose |
|------|-----|---------|
| I2V | `falai/wan-2-5` | Animate images |
| T2V | `google/veo-3-1-fast` | Generate from text |
| Avatar | `bytedance/omnihuman-1-5` | Talking heads |

### Audio

| Step | App | Purpose |
|------|-----|---------|
| TTS | `infsh/kokoro-tts` | Voice narration |
| Music | `infsh/ai-music` | Background music |
| Foley | `infsh/hunyuanvideo-foley` | Sound effects |

### Post-Production

| Step | App | Purpose |
|------|-----|---------|
| Upscale | `falai/topaz-video-upscaler` | Enhance video |
| Merge | `infsh/media-merger` | Combine media |
| Caption | `infsh/caption-video` | Add subtitles |

## Best Practices

1. **Plan the pipeline first** - Map out each step before running
2. **Save intermediate results** - Store outputs for iteration
3. **Use appropriate quality** - Fast models for drafts, quality for finals
4. **Match resolutions** - Keep consistent aspect ratios throughout
5. **Test each step** - Verify outputs before proceeding

## Related Skills

```bash
# Video generation models
npx skills add inference-sh/skills@ai-video-generation

# Image generation
npx skills add inference-sh/skills@ai-image-generation

# Text-to-speech
npx skills add inference-sh/skills@text-to-speech

# LLM models for scripts
npx skills add inference-sh/skills@llm-models

# Full platform skill
npx skills add inference-sh/skills@inference-sh
```

Browse all apps: `infsh app list`

## Documentation

- [Content Pipeline Example](https://inference.sh/docs/examples/content-pipeline) - Official pipeline guide
- [Building Workflows](https://inference.sh/blog/guides/ai-workflows) - Workflow best practices

Related Skills

seo-content-writer

242
from aiskillstore/marketplace

Writes SEO-optimized content based on provided keywords and topic briefs. Creates engaging, comprehensive content following best practices. Use PROACTIVELY for content creation tasks.

seo-content-refresher

242
from aiskillstore/marketplace

Identifies outdated elements in provided content and suggests updates to maintain freshness. Finds statistics, dates, and examples that need updating. Use PROACTIVELY for older content.

seo-content-planner

242
from aiskillstore/marketplace

Creates comprehensive content outlines and topic clusters for SEO. Plans content calendars and identifies topic gaps. Use PROACTIVELY for content strategy and planning.

seo-content-auditor

242
from aiskillstore/marketplace

Analyzes provided content for quality, E-E-A-T signals, and SEO best practices. Scores content and provides improvement recommendations based on established guidelines. Use PROACTIVELY for content review.

ml-pipeline-workflow

242
from aiskillstore/marketplace

Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training and deployment workflows.

machine-learning-ops-ml-pipeline

242
from aiskillstore/marketplace

Design and implement a complete ML pipeline for: $ARGUMENTS

hig-components-content

242
from aiskillstore/marketplace

Apple Human Interface Guidelines for content display components. Use this skill when the user asks about charts component, collection view, image view, web view, color well, image well, activity view, lockup, data visualization, content display, displaying images, rendering web content, color pickers, or presenting collections of items in Apple apps. Also use when the user says how should I display charts, what's the best way to show images, should I use a web view, how do I build a grid of items, what component shows media, or how do I present a share sheet. Cross-references: hig-foundations for color/typography/accessibility, hig-patterns for data visualization patterns, hig-components-layout for structural containers, hig-platforms for platform-specific component behavior.

deployment-pipeline-design

242
from aiskillstore/marketplace

Design multi-stage CI/CD pipelines with approval gates, security checks, and deployment orchestration. Use when architecting deployment workflows, setting up continuous delivery, or implementing GitOps practices.

data-engineering-data-pipeline

242
from aiskillstore/marketplace

You are a data pipeline architecture expert specializing in scalable, reliable, and cost-effective data pipelines for batch and streaming data processing.

content-marketer

242
from aiskillstore/marketplace

Elite content marketing strategist specializing in AI-powered content creation, omnichannel distribution, SEO optimization, and data-driven performance marketing. Masters modern content tools, social media automation, and conversion optimization with 2024/2025 best practices. Use PROACTIVELY for comprehensive content marketing.

azure-ai-contentunderstanding-py

242
from aiskillstore/marketplace

Azure AI Content Understanding SDK for Python. Use for multimodal content extraction from documents, images, audio, and video. Triggers: "azure-ai-contentunderstanding", "ContentUnderstandingClient", "multimodal analysis", "document extraction", "video analysis", "audio transcription".

azure-ai-contentsafety-ts

242
from aiskillstore/marketplace

Analyze text and images for harmful content using Azure AI Content Safety (@azure-rest/ai-content-safety). Use when moderating user-generated content, detecting hate speech, violence, sexual content, or self-harm, or managing custom blocklists.