- name
- vision-helper
- description
- Analyze images using local or cloud vision models via Ollama. Use when you need to identify screenshots, analyze UI elements, read image content, or perform OCR. Triggers on: "analyze image", "screenshot", "what's in this image", "OCR", "识图", "看图", "截图识别".
📸 Vision Helper — Image Analysis
Analyze images using vision models via Ollama, with extended timeout support for cloud-based models.
Why Not Use the Built-in image Tool?
The built-in image tool has limited timeout settings that cause failures with cloud vision models (which often need 40–120 seconds). This skill calls the Ollama API directly with a 180-second timeout, supporting both local and cloud models reliably.
It also bypasses the built-in tool's file path restrictions, allowing analysis of images from any readable directory.
Usage
Basic
# Analyze an image (default: English description)
python3 <skill-dir>/scripts/analyze_image.py <image_path>
# With a custom prompt
python3 <skill-dir>/scripts/analyze_image.py <image_path> "Is this a chess game? Describe the board state"
# With a specific model
python3 <skill-dir>/scripts/analyze_image.py <image_path> "Describe content" kimi-k2.5:cloud<skill-dir>resolves to your OpenClaw skill installation directory, typically~/.openclaw/workspace/skills/vision-helper/.
In Conversation
When you need to analyze an image, use the exec tool:
exec: python3 <skill-dir>/scripts/analyze_image.py /path/to/image.png "What do you see?"Important: Set exec timeout to 120–180 seconds, as cloud vision models are slow.
Screenshot + Analysis Workflow
Option A: Browser screenshot → analyze
1. browser(action="screenshot") → get screenshot path (MEDIA: xxx)
2. exec("<skill-dir>/scripts/analyze_image.py <screenshot_path> 'Describe this UI'")
3. Act on the analysis resultOption B: Desktop screenshot → analyze
macOS:
1. exec("screencapture -x /tmp/screen.png")
2. exec("<skill-dir>/scripts/analyze_image.py /tmp/screen.png 'Describe the desktop'")Linux:
1. exec("gnome-screenshot -f /tmp/screen.png")
— or —
exec("import /tmp/screen.png") # ImageMagick
— or —
exec("scrot /tmp/screen.png")
2. exec("<skill-dir>/scripts/analyze_image.py /tmp/screen.png 'Describe the desktop'")Option C: Game/App UI → analyze → act
1. Screenshot the current screen
2. Use vision-helper to identify UI elements, buttons, text
3. Execute clicks/input based on the analysisEnvironment Variables
| Variable | Default | Description |
|---|---|---|
VISION_MODEL | gemma4:31b | Default vision model |
VISION_TIMEOUT | 180 | Request timeout in seconds |
OLLAMA_API_URL | http://localhost:11434/api/chat | Ollama API endpoint |
Supported Models
| Model | Vision | Speed | Recommendation |
|---|---|---|---|
gemma4:31b | ✅ | Local, fast | ⭐ Primary (privacy, no API needed) |
kimi-k2.6:cloud | ✅ | 40–120s | 🔬 Advanced (high quality, cloud) |
kimi-k2.5:cloud | ✅ | 40–90s | Alternative cloud option |
qwen3.5:cloud | ✅ | 30–60s | Fast cloud recognition |
qwen3.5:397b-cloud | ✅ | 40–90s | High quality cloud |
gemma4:31b | ✅ | Local, fast | Privacy-first (runs offline) |
Note: Cloud models require the model to be available in your Ollama instance. Use VISION_MODEL env var to switch.
FAQ
Q: Can I use the built-in image tool instead?
A: It works for local models but will time out on cloud vision models. Always prefer this skill's script for reliable results.
Q: What image formats are supported?
A: PNG, JPG, JPEG, GIF, WebP, BMP, TIFF, SVG. Maximum file size: 20 MB.
Q: Where should I save screenshots?
A: Any readable directory works — /tmp/, your workspace, etc. This script has no path restrictions.
Q: How do I use a Chinese prompt?
A: Pass it as the second argument: python3 <skill-dir>/scripts/analyze_image.py /tmp/img.png "请描述这张图片的内容"
Automation Ideas
- Game automation: Screenshot → analyze game state → decide next action
- Browser verification: Screenshot → verify page loaded correctly
- Desktop monitoring: Periodic screenshots → detect changes
- UI testing: Screenshot → verify rendered output
- OCR: Extract text content from images