paddleocr-doc-parsing
Parse documents using PaddleOCR's API.
Best use case
paddleocr-doc-parsing is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Parse documents using PaddleOCR's API.
Teams using paddleocr-doc-parsing should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/paddleocr-doc-parsing/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How paddleocr-doc-parsing Compares
| Feature / Agent | paddleocr-doc-parsing | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Parse documents using PaddleOCR's API.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# PaddleOCR Document Parsing
Parse images and PDF files using PaddleOCR's API. Supports multiple document parsing algorithms with structured output.
## Key Features
- **Multi-format support**: PDF and image files (JPG, PNG, BMP, TIFF)
- **Layout analysis**: Automatic detection of text blocks, tables, formulas
- **Multi-language**: Support for 110+ languages
- **Structured output**: Markdown format with preserved document structure
## Setup
1. Obtain credentials from the [PaddleOCR official website](https://www.paddleocr.com). Click the “API” button, choose the desired algorithm (e.g., PP-Structure, PaddleOCR-VL-1.5), and copy the API URL and the access token.
2. Set environment variables:
```bash
export PADDLEOCR_API_URL="https://your-endpoint-here"
export PADDLEOCR_ACCESS_TOKEN="your_access_token"
```
## Usage Examples
### Run Script
```bash
# Parse local image
{baseDir}/paddleocr_parse.sh document.jpg
# Parse local PDF file
{baseDir}/paddleocr_parse.sh -t pdf document.pdf
# Parse document from URL
{baseDir}/paddleocr_parse.sh -t pdf https://example.com/document.pdf
# Output to stdout (default)
{baseDir}/paddleocr_parse.sh document.jpg
# Save output to file
{baseDir}/paddleocr_parse.sh -o result.json document.jpg
```
### Response Structure
```json
{
"logId": "unique_request_id",
"errorCode": 0,
"errorMsg": "Success",
"result": {
"layoutParsingResults": [
{
"prunedResult": [...],
"markdown": {
"text": "# Document Title\n\nParagraph content...",
"images": {}
},
"outputImages": [...],
"inputImage": "http://input-image"
}
],
"dataInfo": {...}
}
}
```
**Important Fields:**
- **`prunedResult`** - Contains detailed layout element information including positions, categories, etc.
- **`markdown`** - Stores the document content converted to Markdown format with preserved structure and formatting.
## Quota Information
See official documentation: https://ai.baidu.com/ai-doc/AISTUDIO/XmjclapamRelated Skills
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