pdf-extractor

namespace	aiwg
name	pdf-extractor
description	Extract text, tables, and images from PDF files. Use when converting PDF documentation, manuals, or reports to searchable text.
tools	Read, Write, Bash
platforms	["all"]

PDF Extractor Skill

Purpose

Single responsibility: Extract structured content (text, tables, images) from PDF files into organized, searchable formats. (BP-4)

Grounding Checkpoint (Archetype 1 Mitigation)

Before executing, VERIFY:

• PDF file exists and is readable (file <path> confirms PDF format)
• PDF is not corrupted (pdfinfo <path> returns metadata)
• Password known if encrypted
• Output directory is writable
• Required tools available (pdfplumber, pytesseract for OCR)

DO NOT proceed without verification. Inspect PDF metadata first.

Uncertainty Escalation (Archetype 2 Mitigation)

ASK USER instead of guessing when:

• PDF appears to be scanned (needs OCR) but OCR tools unavailable
• Multiple table formats detected - unclear which parser to use
• Password-protected but no password provided
• Image extraction quality unclear (resolution, format preferences)
• Language detection needed for OCR

NEVER assume PDF structure without inspection.

Context Scope (Archetype 3 Mitigation)

Context Type	Included	Excluded
RELEVANT	Target PDF, extraction options, output path	Other PDF files
PERIPHERAL	Similar PDF structure examples	Unrelated documents
DISTRACTOR	Previous extraction attempts	Other file formats

Workflow Steps

Step 1: Inspect PDF (Grounding)

# Check file type
file document.pdf

# Get PDF metadata
pdfinfo document.pdf

# Check page count
pdfinfo document.pdf | grep Pages

# Check if encrypted
pdfinfo document.pdf | grep Encrypted

Step 2: Determine Extraction Strategy

PDF Type	Detection	Strategy
Text-based	pdftotext produces readable text	Direct extraction
Scanned/Image	pdftotext produces empty/garbled	OCR required
Mixed	Some pages text, some images	Hybrid approach
Tables	Visual grid patterns	Table extraction mode
Forms	Interactive fields	Form field extraction

Step 3: Execute Extraction

Option A: With skill-seekers (if installed)

# Basic extraction
skill-seekers pdf --pdf document.pdf --name myskill

# With table extraction
skill-seekers pdf --pdf document.pdf --name myskill --extract-tables

# With OCR for scanned docs
skill-seekers pdf --pdf document.pdf --name myskill --ocr

# With parallel processing (large PDFs)
skill-seekers pdf --pdf document.pdf --name myskill --parallel --workers 8

# Password-protected
skill-seekers pdf --pdf document.pdf --name myskill --password "secret"

Option B: Manual extraction guidance

# Basic text extraction
pdftotext -layout document.pdf output.txt

# Extract with page markers
pdftotext -layout -eol unix document.pdf output.txt

# Extract images
pdfimages -all document.pdf images/

# OCR scanned PDF (requires tesseract)
pdftoppm document.pdf page -png
tesseract page-*.png output -l eng

Step 4: Validate Output

# Check extraction quality
head -100 output/<skill-name>/references/content.md

# Verify table extraction
grep -A 10 "| " output/<skill-name>/references/*.md

# Check image extraction
ls -la output/<skill-name>/assets/images/

Recovery Protocol (Archetype 4 Mitigation)

On error:

1. PAUSE - Stop extraction, preserve partial output
2. DIAGNOSE - Check error type:
   • File not found → Verify path
   • Password required → Ask user for password
   • Corrupt PDF → Try repair with qpdf --check
   • OCR failed → Check tesseract installation, language packs
   • Memory error → Process in chunks, reduce workers
3. ADAPT - Switch strategy based on diagnosis
4. RETRY - Resume with adapted approach (max 3 attempts)
5. ESCALATE - Ask user for guidance

Checkpoint Support

State saved to: .aiwg/working/checkpoints/pdf-extractor/

For large PDFs, extraction saves progress per chunk:

checkpoints/pdf-extractor/
├── document_metadata.json
├── pages_1-50.json
├── pages_51-100.json
└── current_position.json

Output Structure

output/<skill-name>/
├── SKILL.md              # Skill description with PDF summary
├── references/
│   ├── index.md          # Table of contents
│   ├── chapter_1.md      # Content by section
│   ├── chapter_2.md
│   └── tables.md         # Extracted tables
└── assets/
    └── images/           # Extracted images (if enabled)
        ├── page_1_fig_1.png
        └── page_5_chart_1.png

Configuration Options

{
  "name": "mymanual",
  "description": "Product manual documentation",
  "pdf_path": "docs/manual.pdf",
  "extract_options": {
    "chunk_size": 10,
    "min_quality": 6.0,
    "extract_images": true,
    "min_image_size": 150,
    "ocr_enabled": false,
    "ocr_language": "eng",
    "table_extraction": true
  },
  "categories": {
    "getting_started": ["introduction", "setup", 
       
       
  

Extraction Quality Metrics

Metric	Good	Acceptable	Poor
Text extraction rate	>95%	80-95%	<80%
Table accuracy	>90%	70-90%	<70%
Image quality	>300 DPI	150-300 DPI	<150 DPI
OCR confidence	>90%	70-90%	<70%

Troubleshooting

Issue	Diagnosis	Solution
Garbled text	Scanned PDF	Enable OCR mode
Missing tables	Complex layout	Use --extract-tables with pdfplumber
Poor OCR	Low resolution	Increase DPI, check language pack
Memory error	Large PDF	Use chunked extraction, reduce workers
Corrupt PDF	File damaged	Try qpdf --check or mutool clean

Dependencies

Required:

• Python 3.10+
• pdfplumber or pypdf

Optional (for advanced features):

• pytesseract + tesseract-ocr (for OCR)
• Pillow (for image processing)
• camelot-py (for complex tables)

References

• Skill Seekers PDF Support: https://github.com/jmagly/Skill_Seekers/blob/main/docs/PDF_MCP_TOOL.md
• REF-001: Production-Grade Agentic Workflows (BP-1, BP-4)
• REF-002: LLM Failure Modes (Archetype 1-4 mitigations)