pdf-process-mineru

What This Skill Does

The pdf-process-mineru skill is a powerful document conversion engine designed for OpenClaw agents. Leveraging the robust MinerU framework, it enables agents to transform complex PDF files into machine-readable formats like Markdown and structured JSON. Unlike simple text extractors, this tool excels at preserving the semantic integrity of documents by identifying and formatting formulas, tables, and image placements. Whether you are dealing with academic papers, technical documentation, or financial reports, this skill provides a high-fidelity pipeline for turning static visual documents into searchable, editable, and data-rich content.

Installation

To integrate this skill into your environment, run the following command in your OpenClaw terminal: clawhub install openclaw/skills/skills/baokui/pdf-parser-mineru

Ensure that your environment meets the dependencies required by MinerU, including necessary OCR engines, to take full advantage of the advanced layout analysis features.

Use Cases

1. Research & Academic Analysis: Quickly convert dense research papers into Markdown to feed into LLMs for summarization, synthesis, or querying specific formulas and data points.
2. Financial Reporting: Extract complex tables from annual PDF reports into structured JSON format for automated spreadsheet ingestion or database population.
3. Knowledge Base Automation: Batch process legacy PDF manuals into clean Markdown files to update enterprise documentation portals with minimal manual formatting effort.
4. Data Extraction: Programmatically pull data from scanned documents by leveraging the hybrid OCR engines that MinerU provides.

Example Prompts

1. "Please convert the PDF located at /docs/annual_report.pdf to Markdown and save the output to /reports/analysis/, ensuring you capture all the tables."
2. "Can you process pages 10 through 20 of /research/physics_paper.pdf using the pipeline backend and give me the JSON representation of the layout?"
3. "Convert /manuals/system_guide.pdf into Markdown format, make sure you enable both formula and table recognition so the output is accurate."

Tips & Limitations

• Backend Selection: The hybrid-auto-engine is suitable for most general tasks. If you are processing documents with very complex layouts, try the vlm-auto-engine for superior visual comprehension.
• Performance: High-resolution OCR and layout analysis are computationally expensive. Processing very long PDFs can take significant time; consider using the start_page and end_page parameters for granular tasks.
• Output Integrity: While MinerU is highly accurate, verify complex nested tables after conversion, as highly non-standard document formatting can occasionally lead to structural artifacts.