How do I install the Extracting PDF Text skill?

Run npx skillmds add tools-only/extracting-pdf-text in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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Is Extracting PDF Text free to use?

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Who published Extracting PDF Text?

tools-only (@tools-only) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Extracting PDF Text by tools-only — Agent Skill

Name: Extracting PDF Text
Rating: 4.2 (5 reviews)
Author: tools-only

Extracting PDF Text

Extract text from PDFs for LLM consumption. Use when processing PDFs for RAG, document analysis, or text extraction. Supports API services (Mistral OCR) and local tools (PyMuPDF, pdfplumber). Handles text-based PDFs, tables, and scanned documents with OCR.

tools-only 1e318dc 3 files · 6.7 KB Updated Sep 8, 2026 7 repo stars

File contents

Extracting PDF Text for LLMs

This skill provides tools and guidance for extracting text from PDFs in formats suitable for language model consumption.

Quick Decision Guide

PDF Type	Best Approach	Script
Simple text PDF	PyMuPDF	`scripts/extract_pymupdf.py`
PDF with tables	pdfplumber	`scripts/extract_pdfplumber.py`
Scanned/image PDF (local)	pytesseract	`scripts/extract_with_ocr.py`
Complex layout, highest accuracy	Mistral OCR API	`scripts/extract_mistral_ocr.py`
End-to-end RAG pipeline	marker-pdf	`pip install marker-pdf`

Recommended Workflow

Try PyMuPDF first - fastest, handles most text-based PDFs well
If tables are mangled - switch to pdfplumber
If scanned/image-based - use Mistral OCR API (best accuracy) or local OCR (free but slower)

Local Extraction (No API Required)

PyMuPDF - Fast General Extraction

Best for: Text-heavy PDFs, speed-critical workflows, basic structure preservation.

uv run scripts/extract_pymupdf.py input.pdf output.md

The script outputs markdown with preserved headings and paragraphs. For LLM-optimized output, it uses pymupdf4llm which formats text for RAG systems.

pdfplumber - Table Extraction

Best for: PDFs with tables, financial documents, structured data.

uv run scripts/extract_pdfplumber.py input.pdf output.md

Tables are converted to markdown format. Note: pdfplumber works best on machine-generated PDFs, not scanned documents.

Local OCR - Scanned Documents

Best for: Scanned PDFs when API access is unavailable.

uv run scripts/extract_with_ocr.py input.pdf output.txt

Requires: pytesseract, pdf2image, and Tesseract installed (brew install tesseract on macOS).

API-Based Extraction

Mistral OCR API

Best for: Complex layouts, scanned documents, highest accuracy, multilingual content, math formulas.

Pricing: ~1000 pages per dollar (very cost-effective)

export MISTRAL_API_KEY="your-key"
uv run scripts/extract_mistral_ocr.py input.pdf output.md

Features:

Outputs clean markdown
Preserves document structure (headings, lists, tables)
Handles images, math equations, multilingual text
95%+ accuracy on complex documents

For detailed API options and other services, see references/api-services.md.

Output Format Recommendations

For LLM consumption, markdown is preferred:

Preserves semantic structure (headings become context boundaries)
Tables remain readable
Compatible with most RAG chunking strategies

For detailed comparisons of local tools, see references/local-tools.md.

---name: extracting-pdf-textdescription: Extract text from PDFs for LLM consumption. Use when processing PDFs for RAG, document analysis, or text extraction. Supports API services (Mistral OCR) and local tools (PyMuPDF, pdfplumber). Handles text-based PDFs, tables, and scanned documents with OCR.---# Extracting PDF Text for LLMsThis skill provides tools and guidance for extracting text from PDFs in formats suitable for language model consumption.## Quick Decision Guide| PDF Type | Best Approach | Script ||----------|--------------|--------|| Simple text PDF | PyMuPDF | `scripts/extract_pymupdf.py` || PDF with tables | pdfplumber | `scripts/extract_pdfplumber.py` || Scanned/image PDF (local) | pytesseract | `scripts/extract_with_ocr.py` || Complex layout, highest accuracy | Mistral OCR API | `scripts/extract_mistral_ocr.py` || End-to-end RAG pipeline | marker-pdf | `pip install marker-pdf` |## Recommended Workflow1. **Try PyMuPDF first** - fastest, handles most text-based PDFs well2. **If tables are mangled** - switch to pdfplumber3. **If scanned/image-based** - use Mistral OCR API (best accuracy) or local OCR (free but slower)## Local Extraction (No API Required)### PyMuPDF - Fast General ExtractionBest for: Text-heavy PDFs, speed-critical workflows, basic structure preservation.```bashuv run scripts/extract_pymupdf.py input.pdf output.md```The script outputs markdown with preserved headings and paragraphs. For LLM-optimized output, it uses `pymupdf4llm` which formats text for RAG systems.### pdfplumber - Table ExtractionBest for: PDFs with tables, financial documents, structured data.```bashuv run scripts/extract_pdfplumber.py input.pdf output.md```Tables are converted to markdown format. Note: pdfplumber works best on machine-generated PDFs, not scanned documents.### Local OCR - Scanned DocumentsBest for: Scanned PDFs when API access is unavailable.```bashuv run scripts/extract_with_ocr.py input.pdf output.txt```Requires: `pytesseract`, `pdf2image`, and Tesseract installed (`brew install tesseract` on macOS).## API-Based Extraction### Mistral OCR APIBest for: Complex layouts, scanned documents, highest accuracy, multilingual content, math formulas.**Pricing**: ~1000 pages per dollar (very cost-effective)```bashexport MISTRAL_API_KEY="your-key"uv run scripts/extract_mistral_ocr.py input.pdf output.md```Features:- Outputs clean markdown- Preserves document structure (headings, lists, tables)- Handles images, math equations, multilingual text- 95%+ accuracy on complex documentsFor detailed API options and other services, see [references/api-services.md](references/api-services.md).## Output Format RecommendationsFor LLM consumption, markdown is preferred:- Preserves semantic structure (headings become context boundaries)- Tables remain readable- Compatible with most RAG chunking strategiesFor detailed comparisons of local tools, see [references/local-tools.md](references/local-tools.md).

Frequently asked questions