A high-precision document parsing skill that converts images into structured Markdown for better LLM comprehension.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install camscanner-image2markdown-office
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 camscanner-image2markdown-office using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
CamScanner Image to Markdown is a powerful document parsing engine designed to transform static images into machine-readable Markdown. By utilizing advanced OCR technology, this Openclaw Skills integration intelligently decomposes paragraphs and accurately recognizes complex tables, ensuring that the structured output maintains the original reading order.
This capability is essential for developers and researchers who need to feed visual data into large language models without losing context or formatting. By converting images first, users can empower their AI agents to handle screenshots, scanned documents, and photos with the same precision as text-based inputs.
Ensure you have curl and jq installed on your system to handle the API requests and JSON parsing. Use the following steps to verify your environment for Openclaw Skills integration:
# Verify dependencies
curl --version
jq --version
# Set the base URL for processing
BASE="https://ai-tools.camscanner.com"
The skill manages data through a temporary file ID system to ensure privacy and real-time processing. The following table describes the data flow:
| Data Type | Description |
|---|---|
| Input Formats | Standard images such as PNG, JPG, or screenshots. |
| Output Format | Structured .md (Markdown) files with preserved reading order. |
| Session Data | Temporary file_ids used for the upload-convert-download pipeline. |
| Metadata | Internal mapping of paragraphs, tables, and multiple element types. |
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