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ai-content-pipelineAI 内容管道

Agent Skill

用于辅助文档、README、Markdown、说明文和内容稿件的整理与改写。它适合让 Agent 提炼结构、补齐章节、统一术语、检查链接或把零散材料整理成可读文档。使用时应保留项目已有事实、命令和路径,不要把未确认的信息写成确定结论;涉及对外文案时,还需要控制语气,避免过度营销或夸大能力。

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CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ai-content-pipeline(AI 内容管道)
来源仓库:https://github.com/inf-sh/skills
仓库路径:skills/ai-content-pipeline
安装命令:
npx skills add inf-sh/skills --skill "ai-content-pipeline"
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

AgentSkills.tonpx skills
npx skills add inf-sh/skills --skill "ai-content-pipeline"

简介

构建结合图像、视频、音频和文本的多步骤 AI 内容创建管道。工作流程示例:生成图像 -> 动画 -> 添加画外音 -> 与音乐合并。工具:FLUX、Veo、Kokoro TTS、OmniHuman、媒体合并、升级。用于:YouTube 视频、社交媒体内容、营销材料、自动化内容。触发器:内容管道、人工智能工作流程、内容创建、多步骤人工智能、内容自动化、人工智能视频工作流程、生成和编辑、人工智能内容工厂、自动化内容创建、人工智能生产管道、媒体管道、大规模内容

SKILL.md

name
ai-content-pipeline
description
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
allowed-tools
Bash(infsh *)

AI Content Pipeline

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

AI Content Pipeline

Quick Start

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.

# 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.

# 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.

# 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 '{
  "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

StepAppPurpose
Scriptopenrouter/claude-sonnet-45Write content
Researchtavily/search-assistantGather information
Summaryopenrouter/claude-haiku-45Condense content

Visual Assets

StepAppPurpose
Imagefalai/flux-devGenerate images
Imagegoogle/imagen-3Alternative image gen
Upscalefalai/topaz-image-upscalerEnhance quality

Animation

StepAppPurpose
I2Vfalai/wan-2-5Animate images
T2Vgoogle/veo-3-1-fastGenerate from text
Avatarbytedance/omnihuman-1-5Talking heads

Audio

StepAppPurpose
TTSinfsh/kokoro-ttsVoice narration
Musicinfsh/ai-musicBackground music
Foleyinfsh/hunyuanvideo-foleySound effects

Post-Production

StepAppPurpose
Upscalefalai/topaz-video-upscalerEnhance video
Mergeinfsh/media-mergerCombine media
Captioninfsh/caption-videoAdd 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@inference-sh

Browse all apps: infsh app list

Documentation

适合场景

01

调用多模型

02

代码和文本生成

03

Agent 推理流程

04

OpenRouter 模型接入

能力概览

能力 1

统一调用多种 LLM

能力 2

支持 Claude、Gemini、Kimi 等模型

能力 3

适合聊天、代码和推理任务

能力 4

可作为 Agent 模型调用入口

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

69.29%
按下载量换算3,160

Cursor

26.37%
按下载量换算1,202

安全审计

暂无安全审计结果可展示。

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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