ai-content-pipeline

inferen-sh/skills · updated Apr 8, 2026

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$npx skills add https://github.com/inferen-sh/skills --skill ai-content-pipeline
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summary

Multi-step AI content creation pipelines combining image, video, audio, and text generation.

  • Chains tools like FLUX (image generation), Wan 2.5 (animation), Kokoro TTS (voice), and OmniHuman (talking heads) into complete workflows via the inference.sh CLI
  • Includes four ready-to-use pipeline templates: YouTube shorts (script → voiceover → background → animation → merge), talking head videos, product demos, and blog-to-video conversion
  • Supports common patterns such as image-to-video-to
skill.md

AI Content Pipeline

Build multi-step content creation pipelines via inference.sh CLI.

AI Content Pipeline

Quick Start

Requires inference.sh CLI (infsh). Install instructions

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.

# 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 '{
  "prompt": "<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.

# 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 '{
  "prompt": "<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.

# 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.

# 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 '{
  "prompt": "<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

# 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@infsh-cli

Browse all apps: infsh app list

Documentation

how to use ai-content-pipeline

How to use ai-content-pipeline on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add ai-content-pipeline
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/inferen-sh/skills --skill ai-content-pipeline

The skills CLI fetches ai-content-pipeline from GitHub repository inferen-sh/skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/ai-content-pipeline

Reload or restart Cursor to activate ai-content-pipeline. Access the skill through slash commands (e.g., /ai-content-pipeline) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.548 reviews
  • Arjun Garcia· Dec 28, 2024

    Keeps context tight: ai-content-pipeline is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Chaitanya Patil· Dec 20, 2024

    I recommend ai-content-pipeline for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Pratham Ware· Dec 20, 2024

    ai-content-pipeline has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Nikhil Diallo· Dec 12, 2024

    ai-content-pipeline is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Kiara Ramirez· Dec 8, 2024

    ai-content-pipeline reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Arjun Flores· Nov 27, 2024

    ai-content-pipeline is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Piyush G· Nov 11, 2024

    Useful defaults in ai-content-pipeline — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Xiao Tandon· Nov 7, 2024

    ai-content-pipeline has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Arjun Gupta· Nov 3, 2024

    ai-content-pipeline reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Min Desai· Oct 26, 2024

    Keeps context tight: ai-content-pipeline is the kind of skill you can hand to a new teammate without a long onboarding doc.

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