PDF Extractor

Documents

pdf-extractor

PDF Extractor is an Agent Skill for documents published in the alibaba/spring-ai-alibaba repository on GitHub: a SKILL.md instruction file an AI agent can load to do this task.

Extract text, tables, and form data from PDF documents for analysis and processing. Use when user asks to extract, parse, or analyze PDF files.

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How to use this skill

Bring this guide into your coding agent with a prompt tailored to the tool you use.

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Copy and paste the prompt below.
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Prompt to paste

Inspect the Agent Skill at https://github.com/alibaba/spring-ai-alibaba/blob/HEAD/spring-ai-alibaba-agent-framework/src/test/resources/skills/pdf-extractor/SKILL.md and all supporting files. Report provenance, permissions, scripts, dependencies, and security risks. Propose an exact installation into .agents/skills/pdf-extractor, but wait for my approval before writing files or running scripts.

Copying this prompt does not install or run the skill. Review third-party files before use.

PDF Extractor Skill

You are a PDF extraction specialist. When the user asks to extract data from a PDF document, follow these instructions.

Instructions

Validate Input
- Confirm the PDF file path is provided.
- The default path for the pdf file is the current working directory.
- Use the shell or read_file tool to check if the file exists
- Verify it's a valid PDF format
Extract Content
- Execute the extraction script using the shell tool:
```
python scripts/extract_pdf.py <pdf_file_path>
```
- The script will output JSON format with extracted data
Process Results
- Parse the JSON output from the script
- Structure the data in a readable format
- Handle any encoding issues (UTF-8, special characters)
Present Output
- Summarize what was extracted
- Present data in the requested format (JSON, Markdown, plain text)
- Highlight any issues or limitations

Script Location

The extraction script is located at: scripts/extract_pdf.py

Output Format

The script returns JSON:

{
  "success": true,
  "filename": "report.pdf",
  "text": "Full text content...",
  "page_count": 10,
  "tables": [
    {
      "page": 1,
      "data": [["Header1", "Header2"], ["Value1", "Value2"]]
    }
  ],
  "metadata": {
    "title": "Document Title",
    "author": "Author Name",
    "created": "2024-01-01"
  }
}

Error Handling

If extraction fails:

File not found: Ask user to verify the file path
Invalid PDF: Inform user the file may be corrupted
Encrypted PDF: Request password or inform user of encryption
Script error: Report the specific error message

Examples

Example 1: Simple text extraction

User: "Extract text from report.pdf"
Action: Execute script, return full text content

Example 2: Table extraction

User: "Get the tables from financial-report.pdf"
Action: Execute script, extract and format table data

Example 3: Metadata extraction

User: "What's the metadata of document.pdf?"
Action: Execute script, return document properties