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Ai Content Pipeline

作者 Ömer Karışman · GitHub ↗ · v0.1.5
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install ai-content-pipeline
功能描述
Build multi-step AI content creation pipelines combining image, video, audio, and text. Workflow examples: generate image -> animate -> add voiceover -> merg...
使用说明 (SKILL.md)

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": "\x3Curl-from-previous>"}'

Install note: The install script only detects your OS/architecture, downloads the matching binary from dist.inference.sh, and verifies its SHA-256 checksum. No elevated permissions or background processes. Manual install & verification available.

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": "\x3Cscript-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": "\x3Cbackground-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": "\x3Cvideo-url>",
  "audio_url": "\x3Cvoice-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": "\x3Cscript>",
  "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": "\x3Cportrait-url>",
  "audio_url": "\x3Cspeech-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": "\x3Cproduct-url>",
  "prompt": "slow 360 rotation, smooth motion"
}' > product_video.json

# 3. Upscale video quality
infsh app run falai/topaz-video-upscaler --input '{
  "video_url": "\x3Cproduct-video-url>"
}' > upscaled.json

# 4. Add background music
infsh app run infsh/media-merger --input '{
  "video_url": "\x3Cupscaled-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: \x3Cblog-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 $i: \x3Cpoint-text>\"
  }" > "image_$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\": \"\x3Cimage-$i-url>\"
  }" > "video_$i.json"
done

# 4. Generate voiceover
infsh app run infsh/kokoro-tts --input '{
  "text": "\x3Cfull-script>",
  "voice": "bf_emma"
}' > narration.json

# 5. Merge all clips
infsh app run infsh/media-merger --input '{
  "videos": ["\x3Cvideo1>", "\x3Cvideo2>", "\x3Cvideo3>", "\x3Cvideo4>", "\x3Cvideo5>"],
  "audio_url": "\x3Cnarration-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@inference-sh

Browse all apps: infsh app list

Documentation

安全使用建议
This skill appears to be an orchestrator that expects you to install and log into the inference.sh CLI and then call many third‑party services. Before installing: (1) do not blindly run curl | sh — download the installer, inspect it, and verify checksums manually; (2) confirm you trust cli.inference.sh / dist.inference.sh and read their privacy/security docs; (3) be prepared that logging in will persist credentials locally and that your content will be sent to external inference providers; (4) avoid supplying high‑privilege or broad tokens — use least privilege and ephemeral keys where possible; (5) if possible, trial the workflow in an isolated/sandboxed environment or VM to limit blast radius; (6) ask the publisher for an explicit list of required credentials and what the CLI stores and transmits. The inconsistencies (no declared install/credentials despite clear install/login steps) make this risky until you validate the external tooling.
功能分析
Type: OpenClaw Skill Name: ai-content-pipeline Version: 0.1.5 The skill is classified as suspicious due to two primary security risks. Firstly, the `SKILL.md` instructs the AI agent to install the `inference.sh` CLI using `curl -fsSL https://cli.inference.sh | sh`. While the skill provides a note explaining the installer's function, executing remote scripts directly via `curl | sh` is a significant supply chain vulnerability, as it relies entirely on the integrity of the remote server and script. Secondly, the `allowed-tools: Bash(infsh *)` permission grants the agent broad capabilities to execute any `infsh` command, which, while used benignly in the provided examples, presents a potential for abuse if the `infsh` CLI itself has vulnerabilities or if the agent is prompted maliciously by a user to execute harmful `infsh` commands.
能力评估
Purpose & Capability
The declared purpose (orchestration of multi-step AI content pipelines) aligns with the workflow examples, but the metadata lists no required binaries, no install steps, and no credentials while the SKILL.md clearly assumes the infsh CLI is installed and that you will log into the inference.sh platform and call many hosted apps. The lack of declared requirements (especially authentication) is inconsistent with the workflows shown.
Instruction Scope
SKILL.md explicitly instructs running curl -fsSL https://cli.inference.sh | sh, running infsh login, and executing many infsh app run commands that will transmit content to third-party services. These instructions direct the agent (or user) to download and execute code and to send potentially sensitive or proprietary content to external endpoints. The docs also rely on interactive login and implicit saved credentials, none of which are declared in the metadata.
Install Mechanism
Although there is no formal install spec in the registry, the instructions recommend piping a remote installer (cli.inference.sh) to sh and downloading binaries from dist.inference.sh. These are download-and-execute operations from a domain that is not a well-known package host; while checksums are referenced, running arbitrary remote install scripts is a higher-risk install mechanism and should be validated manually.
Credentials
The skill metadata declares no required environment variables or primary credential, but the workflows require running infsh login and will likely need API keys/tokens (for inference.sh and for the many backend apps like openrouter, falai, bytedance, etc.). This omission means the skill does not declare the credentials it will need or store, which is a meaningful mismatch and raises the risk of undocumented credential usage or accidental exposure.
Persistence & Privilege
always:false (good), and the skill is not requesting special platform privileges. However, the install instruction will place a binary on disk and infsh login will typically persist credentials locally; these side effects are not declared by the registry metadata and could create persistent agent-facing credentials/configuration on the host.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install ai-content-pipeline
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ai-content-pipeline 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v0.1.5
ai-content-pipeline 0.1.5 - Added comprehensive SKILL.md documentation with detailed pipeline patterns and step-by-step workflow examples. - Described key tools and apps for each stage of AI-powered content creation (image, video, audio, and text). - Included quick start instructions, common pipeline templates, and best practices. - Listed related skills and links to further documentation for easier onboarding and workflow expansion.
v0.1.0
Initial release of ai-content-pipeline. - Enables building multi-step AI content creation pipelines with images, video, audio, and text tools. - Provides ready-to-use workflow patterns for social media, YouTube, product demos, talking head videos, and blog-to-video conversion. - Includes curated app recommendations for each pipeline step (e.g., script generation, TTS, animation, upscaling, media merging). - Offers CLI quick start examples for automated pipeline execution. - Documents best practices, pipeline building blocks, and related skills for easy expansion.
元数据
Slug ai-content-pipeline
版本 0.1.5
许可证
累计安装 2
当前安装数 2
历史版本数 2
常见问题

Ai Content Pipeline 是什么?

Build multi-step AI content creation pipelines combining image, video, audio, and text. Workflow examples: generate image -> animate -> add voiceover -> merg... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 866 次。

如何安装 Ai Content Pipeline?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install ai-content-pipeline」即可一键安装,无需额外配置。

Ai Content Pipeline 是免费的吗?

是的,Ai Content Pipeline 完全免费(开源免费),可自由下载、安装和使用。

Ai Content Pipeline 支持哪些平台?

Ai Content Pipeline 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Ai Content Pipeline?

由 Ömer Karışman(@okaris)开发并维护,当前版本 v0.1.5。

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