claudegoodies
Skill

ocr-and-documents

From NousResearch

Extract text from PDFs/scans (pymupdf, marker-pdf).

Facts

Repository
NousResearch/hermes-agent
Status
Actively maintained
Last commit
Source file
skills/productivity/ocr-and-documents/SKILL.md

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The instructions Claude Code reads when this skill runs.

# PDF & Document Extraction

For DOCX: use `python-docx` (parses actual document structure, far better than OCR).
For PPTX: see the `powerpoint` skill (uses `python-pptx` with full slide/notes support).
This skill covers **PDFs and scanned documents**.

## Step 1: Remote URL Available?

If the document has a URL, **always try `web_extract` first**:

```
web_extract(urls=["https://arxiv.org/pdf/2402.03300"])
web_extract(urls=["https://example.com/report.pdf"])
```

This handles PDF-to-markdown conversion via Firecrawl with no local dependencies.

Only use local extraction when: the file is local, web_extract fails, or you need batch processing.

## Step 2: Choose Local Extractor

| Feature | pymupdf (~25MB) | marker-pdf (~3-5GB) |
|---------|-----------------|---------------------|
| **Text-based PDF** | ✅ | ✅ |
| **Scanned PDF (OCR)** | ❌ | ✅ (90+ languages) |
| **Tables** | ✅ (basic) | ✅ (high accuracy) |
| **Equations / LaTeX** | ❌ | ✅ |
| **Code blocks** | ❌ | ✅ |
| **Forms** | ❌ | ✅ |
| **Headers/footers removal** | ❌ | ✅ |
| **Reading order detection** | ❌ | ✅ |
| **Images extraction** | ✅ (embedded) | ✅ (with context) |
| **Images → text (OCR)** | ❌ | ✅ |
| **EPUB** | ✅ | ✅ |
| **Markdown output** | ✅ (via pymupdf4llm) | ✅ (native, higher quality) |
| **Install size** | ~25MB | ~3-5GB (PyTorch + models) |
| **Speed** | Instant | ~1-14s/page (CPU), ~0.2s/page (GPU) |

**De
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