An integrated AI-powered toolkit for video understanding, precision editing, audio extraction, and visual enhancement.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install byted-mediakit-tools
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install byted-mediakit-tools using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Volcengine AI MediaKit Tools is a sophisticated suite of media processing capabilities powered by Volcengine's AI infrastructure. As a core component of the Openclaw Skills ecosystem, it enables developers to automate complex audio and video tasks through a unified interface. From generating natural language descriptions of video content using AI models to performing high-precision duration trimming and frame-rate interpolation, this skill bridges the gap between raw media files and actionable, high-quality assets.
The tool is designed for high-performance environments where reliability and scalability are paramount. It supports both synchronous operations for quick analysis and robust asynchronous workflows for heavy-duty media transformations, ensuring that AI agents can handle large-scale media processing pipelines without timeouts or execution bottlenecks.
To get started with these Openclaw Skills, configure your credentials and environment variables in the .env file:
# Required: Volcengine AMK API Key
AMK_API_KEY=your_amk_api_key
AMK_ENV=prod
# Optional: Required only for Video Understanding features
ARK_API_KEY=your_ark_api_key
ARK_MODEL_ID=doubao-seed-1-8
Next, initialize the Python environment and install dependencies:
cd <SKILL_DIR>/scripts
python3 -m venv .venv
source .venv/bin/activate
pip install -U pip
pip install -r requirements.txt
The skill produces structured JSON responses to facilitate easy integration into automated workflows. The primary data points include:
| Attribute | Description |
|---|---|
task_id |
A unique identifier for tracking asynchronous processing jobs. |
play_url |
A temporary URL provided for downloading the processed media output. |
status |
Current lifecycle state of the task (pending, completed, failed, or canceled). |
request_id |
A unique reference ID for logging and backend troubleshooting. |
task_type |
The specific media operation performed (e.g., extract-audio, enhance-video). |
choices |
Nested content returned during synchronous AI video understanding tasks. |
--no-wait flag allowing agents to submit tasks and poll for results later via query_task.Loading
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