Convert PDF, Office, images, HTML, and URLs to Markdown. Use for document conversion, text extraction, OCR, web scraping, RAG pipelines. Triggers: "convert to markdown", "extract text", "read PDF", "scrape URL".
Scanned 2/12/2026
Install via CLI
openskills install majiayu000/claude-skill-registry---
name: document-to-markdown
description: Convert PDF, Office, images, HTML, and URLs to Markdown. Use for document conversion, text extraction, OCR, web scraping, RAG pipelines. Triggers: "convert to markdown", "extract text", "read PDF", "scrape URL".
license: MIT License. See LICENSE.txt for details.
compatibility: macOS, Python 3.10+, curl
metadata:
version: "1.0.0"
---
# Document to Markdown
Convert documents and URLs to clean Markdown for LLM/RAG use.
## Prerequisites (Auto-handled)
Before running any conversion, check and install dependencies if needed:
```bash
# Check if dependencies are installed, install if missing
pip show pymupdf4llm markitdown pyyaml > /dev/null 2>&1 || pip install -r ~/.claude/skills/document-to-markdown/requirements.txt
```
Run this check automatically before first use. Do not prompt user for installation.
## Quick Start
```bash
# Single file
python scripts/gateway.py --input <file_or_url> [--json]
# Batch processing
python scripts/gateway.py --input-dir <folder> --output-dir <out> [--recursive] [--parallel 4]
```
## Supported Inputs
| Type | Formats |
|------|---------|
| Documents | PDF, DOCX, PPTX, XLSX |
| Images | PNG, JPG, JPEG, WEBP, TIFF |
| Web | HTML (local), URLs (http/https) |
| Text | TXT, MD, CSV, JSON, XML |
## Key Options
| Option | Purpose |
|--------|---------|
| `--format human` | Clean, readable output (default) |
| `--format rag` | Structured output for LLM/RAG |
| `--json` | Structured output for agents |
| `--input-dir` | Batch process entire directory |
| `--output-dir` | Output directory for batch mode |
| `--recursive` | Include subdirectories in batch |
| `--parallel N` | Process N files concurrently |
| `--frontmatter` | Add YAML metadata header |
| `--pdf-backend marker` | For scanned PDFs (slow, 1.3GB models) |
| `--pdf-backend paddleocr` | For scanned PDFs + Chinese (fast, <10MB) |
| `--table-mode` | Enable table recognition (requires `paddlex[ocr]`) |
| `--use-gpu` | GPU acceleration for PaddleOCR |
| `--to-traditional` | Convert Simplified to Traditional Chinese |
| `--pages 1-10` | Convert specific pages only |
## Workflow
1. Check dependencies (auto-install if missing)
2. Run: `python scripts/gateway.py --input <path> --json`
3. Check JSON `success` field
4. If `warnings` present, consider switching backend
5. Read output file to present content to user
## Format Selection
Default: `--format human` (clean, readable for humans)
Use `--format rag` when user prompt mentions:
- "for RAG", "for LLM", "for embedding", "for AI"
- "vector database", "chunking", "indexing"
- "給 AI 讀", "餵給模型", "向量資料庫"
| Format | Output Style |
|--------|-------------|
| `human` | `## Title` / `Name (email)` / clean links |
| `rag` | `## **Title**` / `**Name** _email_` / full metadata |
## Conditional Logic
```
IF warning "Complex tables detected":
→ Retry with --pdf-backend marker (slower but better tables)
IF output is empty or very short:
→ Retry with --pdf-backend marker (for scanned PDFs)
IF URL timeout:
→ Increase --url-timeout or use --url-backend markitdown
IF OCR quality poor:
→ Specify --lang for correct language
```
## Output Format
Single file:
```json
{"success": true, "output_path": "doc.md", "backend_used": "pymupdf4llm"}
```
Batch:
```json
{"success": true, "total": 10, "converted": 9, "failed": 1, "results": [...]}
```
For backend details, see `references/backends.md`.
For troubleshooting, see `references/troubleshooting.md`.
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