Caption Generator by Image for Openclaw

An AI-powered video production skill that transforms static images into captioned 1080p MP4 clips using remote GPU rendering.

vcarolxhberger
v1.0.0
Apr 15, 2026
0
287
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install caption-generator-by-image

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install caption-generator-by-image using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is Caption Generator by Image?

Caption Generator by Image is a sophisticated tool within the Openclaw Skills ecosystem designed for content creators who need to move fast. It eliminates manual typing by using AI to analyze uploaded images—including JPG, PNG, WEBP, and GIF formats—and generating accurate subtitle overlays. The skill leverages remote GPU nodes for all rendering tasks, ensuring that your local machine's resources are preserved while producing high-quality video output.

By integrating this skill into your workflow, you can convert screenshots, product photos, or brand assets into ready-to-post video content simply by describing the desired result. The backend processes natural language instructions to handle complex tasks like aspect ratio adjustments, text placement, and background music integration, making it a comprehensive solution for automated video editing.

Caption Generator by Image Use Cases

  • Creating social media video clips from static product photos with automated captions.
  • Generating video subtitle overlays for technical screenshots or documentation visuals.
  • Batch processing multiple images to create a cohesive video series in a single session.
  • Rapidly iterating on video styles using natural language prompts instead of manual sliders.

How Caption Generator by Image Works

  1. The user uploads image files (up to 200MB) to the Openclaw Skills interface.
  2. The skill authenticates via a NEMO_TOKEN, creating a unique session for the project.
  3. User instructions are sent via a Server-Sent Events (SSE) stream to a remote GPU processing pipeline.
  4. The AI analyzes image content and generates a video timeline draft including text tracks and media segments.
  5. A cloud GPU node composites the layers, applies H.264 compression, and renders a 1080p MP4 file.
  6. The skill polls the rendering service and provides a direct download URL once the video is complete.

Caption Generator by Image Setup

To start using this skill, you need to ensure the processing backend can authenticate your requests. This is handled via the NEMO_TOKEN environment variable.

# If you have a token, set it in your environment
export NEMO_TOKEN="your_private_token"

If no token is found, the skill will automatically generate a temporary anonymous token with 100 free credits. The skill also requires configuration paths to be accessible at ~/.config/nemovideo/ for session persistence within the Openclaw Skills framework.

Caption Generator by Image Data Schema & Taxonomy

The skill manages video projects using a concise JSON draft schema to represent the timeline and tracks. Data is organized as follows:

Component Key Description
Tracks t An array of all media layers (video, audio, text).
Track Type tt Integer identifier: 0 for Video, 1 for Audio, 7 for Text.
Segments sg Individual media clips with duration defined in milliseconds (d).
Metadata m Additional properties like file source, quality settings, and format.
State draft The current synchronized version of the video project.

Caption Generator by Image Advanced Features

  • Multi-agent support for handling complex video editing workflows through natural language.
  • Remote GPU rendering pipeline that supports exports up to 1080x1920 resolution.
  • Real-time session state polling to recover and resume editing projects across different sessions.
  • Intelligent mapping of GUI-based instructions (like drag-and-drop or click) to API-driven edit commands.
  • Support for a wide range of file formats including MOV, AVI, WEBM, MKV, and various audio codecs.

SKILL.md


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