A sophisticated vision analysis skill that uses the GLM-4.6V model to interpret images, diagrams, and videos through simple CLI commands.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install zai-vision
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 zai-vision using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
zai-vision is a powerful multi-modal extension for Openclaw Skills designed to give AI agents a pair of eyes. By leveraging the advanced GLM-4.6V model, this skill enables programmatic analysis of visual assets ranging from static screenshots and technical diagrams to short video clips. It is built to handle complex visual reasoning tasks that standard LLMs cannot, such as identifying UI components in a mockup or diagnosing system errors from a screen capture.
This skill is particularly valuable for developers building automated testing or documentation pipelines. By integrating zai-vision into your Openclaw Skills workspace, you gain the ability to transform raw visual data into structured insights, facilitating better decision-making for autonomous agents and streamlining technical workflows.
To get started with this vision skill, install the SDK and configure your environment:
pip install zai-sdk
export ZAI_API_KEY='your-api-key'
You can then run an analysis directly from the CLI:
python3 /root/clawd/zai-vision/scripts/vision_analyze.py screenshot.png "Describe this UI"
The skill processes visual inputs and generates descriptive outputs. It supports the following parameter schema for refined control:
| Parameter | Type | Default | Description |
|---|---|---|---|
--model |
String | glm-4.6v | The vision model used for inference |
--max-tokens |
Integer | 2000 | Maximum response length |
--temperature |
Float | 0.5 | Controls randomness (0.0 for factual) |
--json |
Boolean | false | Returns structured JSON output |
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