---
name: pdf-verification-f225538ad289
description: Verify PDF page counts and file integrity programmatically using PyPDF2 after generation
---

# PDF Verification Skill

## Purpose

After generating PDF files, always verify page counts and file integrity programmatically before declaring task completion. This catches formatting issues, empty pages, and corrupted files early.

## When to Use

- After any PDF generation task
- When specific page counts are required
- Before marking a PDF-related task as complete

## Verification Steps

### 1. Install PyPDF2 (if needed)

```bash
pip install PyPDF2
```

### 2. Verify Page Count and Integrity

Use `run_shell` to execute a Python verification script:

```bash
python -c "
from PyPDF2 import PdfReader
import sys

def verify_pdf(filepath, expected_pages=None):
    try:
        reader = PdfReader(filepath)
        actual_pages = len(reader.pages)
        print(f'✓ {filepath}: {actual_pages} pages')
        
        if expected_pages and actual_pages != expected_pages:
            print(f'✗ Page count mismatch: expected {expected_pages}, got {actual_pages}')
            return False
        
        # Check file is not empty/corrupted
        if actual_pages == 0:
            print(f'✗ Empty PDF: {filepath}')
            return False
        
        return True
    except Exception as e:
        print(f'✗ Error reading {filepath}: {e}')
        return False

# Verify each PDF
results = []
results.append(verify_pdf('output.pdf', expected_pages=2))
print(f'All checks passed: {all(results)}')
sys.exit(0 if all(results) else 1)
"
```

### 3. Verify Multiple PDFs

For tasks with multiple PDFs, verify each one:

```bash
python -c "
from PyPDF2 import PdfReader

pdfs = {
    'listings.pdf': 2,
    'map.pdf': 1,
    'summary.pdf': 1
}

all_passed = True
for filepath, expected in pdfs.items():
    try:
        reader = PdfReader(filepath)
        actual = len(reader.pages)
        status = '✓' if actual == expected else '✗'
        print(f'{status} {filepath}: {actual}/{expected} pages')
        if actual != expected:
            all_passed = False
    except Exception as e:
        print(f'✗ {filepath}: {e}')
        all_passed = False

print(f'Verification: {\"PASSED\" if all_passed else \"FAILED\"}')
"
```

### 4. Check File Size (Optional)

Add file size validation to catch empty or near-empty files:

```bash
python -c "
import os
from PyPDF2 import PdfReader

filepath = 'output.pdf'
min_size = 1000  # minimum bytes

file_size = os.path.getsize(filepath)
if file_size < min_size:
    print(f'✗ File too small: {file_size} bytes')
else:
    reader = PdfReader(filepath)
    print(f'✓ {filepath}: {len(reader.pages)} pages, {file_size} bytes')
"
```

## Best Practices

1. **Verify immediately after generation** - Don't wait until the end of the task
2. **Check all required PDFs** - Verify each file meets specifications
3. **Fail fast** - If verification fails, regenerate before proceeding
4. **Log results** - Print verification results for debugging
5. **Set reasonable minimums** - Use file size checks to catch empty outputs

## Common Issues Caught

- Wrong page counts (extra blank pages, missing content)
- Corrupted or unreadable PDF files
- Empty PDFs (0 pages)
- Files that appear generated but contain no actual content

## Example Task Completion Check

```bash
# Final verification before marking task complete
python -c "
from PyPDF2 import PdfReader
import sys

required = {'listings.pdf': 2, 'map.pdf': 1}
passed = True

for f, pages in required.items():
    try:
        actual = len(PdfReader(f).pages)
        if actual != pages:
            print(f'FAIL: {f} has {actual} pages, expected {pages}')
            passed = False
    except Exception as e:
        print(f'FAIL: Cannot read {f}: {e}')
        passed = False

if passed:
    print('SUCCESS: All PDFs verified')
    sys.exit(0)
else:
    sys.exit(1)
"
```

---
Source attribution: AG064
Original project: https://github.com/AG064/OpenSpace/blob/ff671ef61ed6587c49bd54c81cdc751c0b99e363/gdpval_bench/skills/pdf-verification/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 ✨Data Intelligence Lab@HKU✨

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: AG064
Original project: https://github.com/AG064/OpenSpace/blob/ff671ef61ed6587c49bd54c81cdc751c0b99e363/gdpval_bench/skills/pdf-verification/SKILL.md
Attribution basis: Source repository record

Fields of work: Data & Analytics, Development & Engineering
Roles: Backend Developer, Data Analyst, QA / Test Engineer
Specialties: Backend, Cross Platform
Tools: Pypdf2
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 5e920590a170c0012953a1607267b6cbb1365efe2ce36dd2b3b57667625f8c5d