# PDF To Md

> Convert PDF to Markdown so Claude can read it natively in conversations. Three-tier engine: pymupdf4llm (fast, default), marker-pdf (--quality, Apple MPS-accelerated for scanned/equations), docling (--best, IBM, top accuracy on academic/enterprise PDFs). Auto-extracts images. Use when the user pastes a PDF path, asks "read this paper", "convert this PDF", "summarize this report", or whenever a .pdf needs to enter context.

- Skill: `phy041/pdf-to-md` (Agent Skill, multi-file: 4 files)
- Install (CLI): `npx skillmds@latest add phy041/pdf-to-md`
- Raw SKILL.md: https://api.skillmd.com/api/skills/phy041/pdf-to-md/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Docs & Writing
- Author: PHY041 (https://skillmd.com/u/phy041)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/phy041/pdf-to-md

---


# PDF → Markdown

## When to use

Whenever a `.pdf` file appears in the conversation and the user wants Claude to read, summarize, quote, or operate on its contents. Native `Read` tool can open small PDFs but truncates large ones and loses table structure — this skill produces a clean `.md` you can read fully and grep.

## How to invoke

One command does everything (auto-installs missing deps on first run):

```bash
python3 ~/.claude/skills/pdf-to-md/bin/convert.py <path-to-pdf>
```

**Output:** writes `<same-dir>/<same-name>.md` next to the PDF, plus an `<same-name>_images/` folder if images are extracted.

**Common flags:**
- `--quality` — force the marker-pdf engine (use for scanned PDFs, academic papers with equations, or when the fast engine output looks sparse)
- `--out <path>` — override output path
- `--engine pymupdf4llm|marker` — pick engine explicitly
- `--no-images` — skip image extraction

After conversion, `Read` the produced `.md`.

## Engine selection (auto)

| PDF type | Engine | Why |
|----------|--------|-----|
| Native (most modern PDFs, has selectable text) | `pymupdf4llm` | <30s install, no models, fastest, ~520 pages/sec |
| Scanned (no extractable text detected) | auto-fallback to `marker-pdf` | Has OCR + layout model |
| Heavy LaTeX / complex tables | use `--quality` to force `marker-pdf` | LLM-optimized table + equation extraction |

The script auto-detects scanned PDFs (text density check) and switches engines without user intervention.

## First-run gotchas (tell the user)

- **pymupdf4llm:** installs in ~15s, no model download. Just works.
- **marker-pdf:** first run downloads ~2GB of models from HuggingFace. Subsequent runs are fast. If on slow wifi, warn the user before triggering `--quality`.
- **Apple Silicon:** both tools have prebuilt wheels — no compilation needed.

## Examples

```bash
# Quick read — fast engine, default output
python3 ~/.claude/skills/pdf-to-md/bin/convert.py ~/Downloads/paper.pdf

# Academic paper with equations — force quality engine
python3 ~/.claude/skills/pdf-to-md/bin/convert.py ~/Downloads/paper.pdf --quality

# Custom output path, no images
python3 ~/.claude/skills/pdf-to-md/bin/convert.py report.pdf --out /tmp/report.md --no-images
```

## What this skill does NOT do

- Does not handle Office docs (use `markitdown` or pandoc for `.docx`/`.pptx`)
- Does not call cloud APIs (LlamaParse, Mistral OCR) — pure local. Add a flag later if bulk volume requires it.
- Does not transcribe handwritten PDFs (Tesseract-grade OCR only).