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PDF Processing Pro

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anbeime
PDF Processing Pro

综合办公文员与软件开发工程师当需要批量处理PDF表单、提取表格或进行OCR识别时,使用内置脚本一键完成自动化提取与数据校验,彻底告别繁琐的手动录入,让复杂文档工作流高效、稳健落地。

Overview

Publisheranbeime
Repositoryskill
Skill namePDF Processing Pro
Stars
6.9K
Forks
645
Bundled files
4
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by anbeime on GitHub. Read the source before you install it.

Installation

Install the PDF Processing Pro AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/anbeime/skill.git /tmp/skill
mkdir -p .claude/skills
cp -r /tmp/skill/skills/pdf-processing-pro/pdf-processing-pro .claude/skills/anbeime-pdf-processing-pro
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable PDF Processing Pro in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads PDF Processing Pro on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so PDF Processing Pro is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

PDF Processing Pro

Production-ready PDF processing toolkit with pre-built scripts, comprehensive error handling, and support for complex workflows.

Quick start

Extract text from PDF

python
import pdfplumber

with pdfplumber.open("document.pdf") as pdf:
    text = pdf.pages[0].extract_text()
    print(text)

Analyze PDF form (using included script)

bash
python scripts/analyze_form.py input.pdf --output fields.json
# Returns: JSON with all form fields, types, and positions

Fill PDF form with validation

bash
python scripts/fill_form.py input.pdf data.json output.pdf
# Validates all fields before filling, includes error reporting

Extract tables from PDF

bash
python scripts/extract_tables.py report.pdf --output tables.csv
# Extracts all tables with automatic column detection

Features

✅ Production-ready scripts

All scripts include:

  • Error handling: Graceful failures with detailed error messages
  • Validation: Input validation and type checking
  • Logging: Configurable logging with timestamps
  • Type hints: Full type annotations for IDE support
  • CLI interface: --help flag for all scripts
  • Exit codes: Proper exit codes for automation

✅ Comprehensive workflows

  • PDF Forms: Complete form processing pipeline
  • Table Extraction: Advanced table detection and extraction
  • OCR Processing: Scanned PDF text extraction
  • Batch Operations: Process multiple PDFs efficiently
  • Validation: Pre and post-processing validation

Advanced topics

PDF Form Processing

For complete form workflows including:

  • Field analysis and detection
  • Dynamic form filling
  • Validation rules
  • Multi-page forms
  • Checkbox and radio button handling

See FORMS.md

Table Extraction

For complex table extraction:

  • Multi-page tables
  • Merged cells
  • Nested tables
  • Custom table detection
  • Export to CSV/Excel

See TABLES.md

OCR Processing

For scanned PDFs and image-based documents:

  • Tesseract integration
  • Language support
  • Image preprocessing
  • Confidence scoring
  • Batch OCR

See OCR.md

Included scripts

Form processing

analyze_form.py - Extract form field information

bash
python scripts/analyze_form.py input.pdf [--output fields.json] [--verbose]

fill_form.py - Fill PDF forms with data

bash
python scripts/fill_form.py input.pdf data.json output.pdf [--validate]

validate_form.py - Validate form data before filling

bash
python scripts/validate_form.py data.json schema.json

Table extraction

extract_tables.py - Extract tables to CSV/Excel

bash
python scripts/extract_tables.py input.pdf [--output tables.csv] [--format csv|excel]

Text extraction

extract_text.py - Extract text with formatting preservation

bash
python scripts/extract_text.py input.pdf [--output text.txt] [--preserve-formatting]

Utilities

merge_pdfs.py - Merge multiple PDFs

bash
python scripts/merge_pdfs.py file1.pdf file2.pdf file3.pdf --output merged.pdf

split_pdf.py - Split PDF into individual pages

bash
python scripts/split_pdf.py input.pdf --output-dir pages/

validate_pdf.py - Validate PDF integrity

bash
python scripts/validate_pdf.py input.pdf

Common workflows

Workflow 1: Process form submissions

bash
# 1. Analyze form structure
python scripts/analyze_form.py template.pdf --output schema.json

# 2. Validate submission data
python scripts/validate_form.py submission.json schema.json

# 3. Fill form
python scripts/fill_form.py template.pdf submission.json completed.pdf

# 4. Validate output
python scripts/validate_pdf.py completed.pdf

Workflow 2: Extract data from reports

bash
# 1. Extract tables
python scripts/extract_tables.py monthly_report.pdf --output data.csv

# 2. Extract text for analysis
python scripts/extract_text.py monthly_report.pdf --output report.txt

Workflow 3: Batch processing

python
import glob
from pathlib import Path
import subprocess

# Process all PDFs in directory
for pdf_file in glob.glob("invoices/*.pdf"):
    output_file = Path("processed") / Path(pdf_file).name

    result = subprocess.run([
        "python", "scripts/extract_text.py",
        pdf_file,
        "--output", str(output_file)
    ], capture_output=True)

    if result.returncode == 0:
        print(f"✓ Processed: {pdf_file}")
    else:
        print(f"✗ Failed: {pdf_file} - {result.stderr}")

Error handling

All scripts follow consistent error patterns:

python
# Exit codes
# 0 - Success
# 1 - File not found
# 2 - Invalid input
# 3 - Processing error
# 4 - Validation error

# Example usage in automation
result = subprocess.run(["python", "scripts/fill_form.py", ...])

if result.returncode == 0:
    print("Success")
elif result.returncode == 4:
    print("Validation failed - check input data")
else:
    print(f"Error occurred: {result.returncode}")

Dependencies

All scripts require:

bash
pip install pdfplumber pypdf pillow pytesseract pandas

Optional for OCR:

bash
# Install tesseract-ocr system package
# macOS: brew install tesseract
# Ubuntu: apt-get install tesseract-ocr
# Windows: Download from GitHub releases

Performance tips

  • Use batch processing for multiple PDFs
  • Enable multiprocessing with --parallel flag (where supported)
  • Cache extracted data to avoid re-processing
  • Validate inputs early to fail fast
  • Use streaming for large PDFs (>50MB)

Best practices

  1. Always validate inputs before processing
  2. Use try-except in custom scripts
  3. Log all operations for debugging
  4. Test with sample PDFs before production
  5. Set timeouts for long-running operations
  6. Check exit codes in automation
  7. Backup originals before modification

Troubleshooting

Common issues

"Module not found" errors:

bash
pip install -r requirements.txt

Tesseract not found:

bash
# Install tesseract system package (see Dependencies)

Memory errors with large PDFs:

python
# Process page by page instead of loading entire PDF
with pdfplumber.open("large.pdf") as pdf:
    for page in pdf.pages:
        text = page.extract_text()
        # Process page immediately

Permission errors:

bash
chmod +x scripts/*.py

Getting help

All scripts support --help:

bash
python scripts/analyze_form.py --help
python scripts/extract_tables.py --help

For detailed documentation on specific topics, see:

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the PDF Processing Pro AI skill do?

综合办公文员与软件开发工程师当需要批量处理PDF表单、提取表格或进行OCR识别时,使用内置脚本一键完成自动化提取与数据校验,彻底告别繁琐的手动录入,让复杂文档工作流高效、稳健落地。

Why use PDF Processing Pro on TypingMind?

Because you install it once and use it with any model. PDF Processing Pro is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install PDF Processing Pro in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/anbeime/skill/tree/main/skills/pdf-processing-pro/pdf-processing-pro. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use PDF Processing Pro?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with PDF Processing Pro?

As many as you like. As long as a model supports skills, you can use PDF Processing Pro with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the PDF Processing Pro AI skill free?

It is published on GitHub by anbeime. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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