A sophisticated document recognition skill using PaddleOCR-VL and DeepSeek-OCR to extract structured data and text from complex Chinese documents and images.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install china-doc-ocr
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 china-doc-ocr using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
China Doc OCR is a specialized tool designed for high-accuracy optical character recognition and structured data extraction from Chinese-language documents. By leveraging advanced models like PaddleOCR-VL-1.5 and DeepSeek-OCR, it provides developers with a seamless way to convert physical media into digital, editable formats. This skill is particularly optimized for the Chinese region, offering direct connections without requiring network proxies.
Whether you are dealing with scanned legal contracts, complex financial tables, or handheld photos of identification cards, this skill intelligently selects the best vision-language model to maintain structural integrity. It goes beyond simple text extraction by preserving Markdown hierarchies, tables, and bold formatting, making it an essential component of modern Openclaw Skills workflows.
To use this skill within Openclaw Skills, ensure you have an API key from SiliconFlow.
# 1. Register at cloud.siliconflow.cn
# 2. Create your API Key in the dashboard
# 3. Export the key to your environment
export SILICONFLOW_API_KEY='sk-xxxxxxxx'
# 4. (Optional) Install pypdf for multi-page PDF support
pip install pypdf
China Doc OCR organizes its output based on the specific extraction target:
| Document Type | Output Format | Key Metadata Fields |
|---|---|---|
| General Documents | Markdown | Headers, Lists, Bold text, Code blocks |
| Invoices | Structured Text | Invoice Number, Date, Buyer/Seller, Tax Rate, Total Amount |
| Tables | CSV/Markdown | Column headers, Cell values, Row alignment |
| Identity Cards | Structured Text | Name, ID Number, Address, Validity Period |
| Charts | Analysis | Data trends, Axis labels, Summary statistics |
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