agentsclimarketplace

Pdf processing pro

Skill henriquescastilho/my-claude/.codex/vendor_imports/claude/marketplaces/claude-code-templates/cli-tool/components/skills/document-processing/pdf-processing-pro

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Install
npx -y skills add henriquescastilho/my-claude --skill pdf-processing-pro

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What its author says it does

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Production-ready PDF processing with forms, tables, OCR, validation, and batch operations. Use when working with complex PDF workflows in production environments, processing large volumes of PDFs, or requiring robust error handling and validation.

SKILL.md

6.9 KB, ~1.6k tokens by cl100k_base, as published. Nobody here has run it

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

import pdfplumber

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

Analyze PDF form (using included script)

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

Fill PDF form with validation

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

Extract tables from PDF

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

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

fill_form.py - Fill PDF forms with data

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

validate_form.py - Validate form data before filling

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

Table extraction

extract_tables.py - Extract tables to CSV/Excel

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

Text extraction

extract_text.py - Extract text with formatting preservation

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

Utilities

merge_pdfs.py - Merge multiple PDFs

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

split_pdf.py - Split PDF into individual pages

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

validate_pdf.py - Validate PDF integrity

python scripts/validate_pdf.py input.pdf

Common workflows

Workflow 1: Process form submissions

# 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

# 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

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:

# 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:

pip install pdfplumber pypdf pillow pytesseract pandas

Optional for OCR:

# 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:

pip install -r requirements.txt

Tesseract not found:

# Install tesseract system package (see Dependencies)

Memory errors with large PDFs:

# 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:

chmod +x scripts/*.py

Getting help

All scripts support --help:

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

For detailed documentation on specific topics, see:

Gives 0 of the 12 instructions most pdf office docs skills give in ~1.6k tokens

Counted across 636 of the 690 authors here whose files we hold, read 2026-08-07

  • extract text using pdfplumberin 89 of 636, across 23 files
  • create PDFs using reportlabin 83 of 636, across 16 files
  • read forms.md to fill out pdf formsin 80 of 636, across 13 files
  • OCR scanned PDFs using pytesseractin 77 of 636, across 10 files
  • merge or split PDFs using qpdfin 70 of 636, across 3 files
  • use excel formulas instead of hardcoded calculated valuesin 68 of 636, across 13 files
  • unpack edit xml and repack existing documentsin 63 of 636, across 8 files
  • document sources for hardcoded valuesin 61 of 636, across 9 files
  • write minimal python code without unnecessary commentsin 59 of 636, across 7 files
  • run the recalculation script after adding or modifying formulasin 59 of 636, across 7 files
  • fix all identified formula errors and recalculatein 58 of 636, across 6 files
  • format years as text stringsin 57 of 636, across 5 files

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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