A powerful tool for generating SRT subtitles, translating audio, and burning hardcoded captions into videos using specialized Hebrew and English AI models.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install video-subtitles
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install video-subtitles 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 Video Subtitles?
This skill provides a professional-grade transcription and subtitling solution designed to streamline the creation of accessible video content. By integrating specialized AI models like ivrit.ai for top-tier Hebrew transcription and OpenAI Whisper for English, it ensures that every word is captured with high precision within the framework of Openclaw Skills.
Beyond simple text generation, the skill manages complex formatting tasks such as movie-style line breaks and timestamp synchronization. It offers users the flexibility to generate standalone SRT files, embed soft subtitles, or hardcode (burn) text directly into video files, making them perfect for social media sharing where external subtitle files are not supported.
Video Subtitles Use Cases
- Creating highly accurate SRT subtitle files for accessibility and SEO optimization.
- Translating Hebrew video content into English subtitles for international audiences.
- Hardcoding subtitles directly into videos for seamless playback on platforms like WhatsApp or Instagram.
- Generating text-based transcripts from long-form audio or video files for documentation.
- Enhancing video content workflows with the automated features provided by Openclaw Skills.
How Video Subtitles Works
- The user executes the transcription script with a source video or audio file.
- The system automatically detects the spoken language or utilizes a forced model (ivrit.ai for Hebrew or Whisper for English).
- Speech is processed into text segments with precise start and end timestamps.
- If the translation flag is set, the skill translates the segments into the target language.
- The final output is formatted into SRT, plain text, or hardcoded into a new video file using ffmpeg logic.
Video Subtitles Setup
To get started, ensure you have the uv package manager and ffmpeg-full installed on your system.
# Install required system dependencies
brew install ffmpeg-full
# Run the transcription script (models download automatically on first use)
./scripts/generate_srt.py path/to/video.mp4 --srt --burn
Video Subtitles Data Schema & Taxonomy
| Output Format | Filename Pattern | Description |
|---|---|---|
| Plain Text | stdout | Direct transcript text printed to the terminal. |
| SRT File | input_name.srt | SubRip subtitle file generated alongside the source. |
| Subtitled Video | input_name_subtitled.mp4 | A copy of the video with subtitles hardcoded into the image. |
| Embedded Subs | input_name.mp4 | Video file with soft-coded subtitle tracks. |
Video Subtitles Advanced Features
- Intelligent line-splitting logic that restricts subtitles to 42 characters per line for maximum readability.
- Support for the high-performance ivrit.ai model, providing the industry's best Hebrew transcription within Openclaw Skills.
- Automatic model management that handles the downloading and caching of approximately 3GB of AI model data.
- Comprehensive CLI flags for forcing specific languages, output paths, and translation directions.
SKILL.md
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