PDFs in your workflow is burning around your 3xtokens , save them for free using Microsoft's Markitdown

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pdf markdown token-efficiency microsoft markitdown ai-workflow cost-saving

Summary

Microsoft's Markitdown tool converts PDFs to markdown, saving tokens and cost when feeding documents to AI models like Claude, but requires caution with scanned PDFs, charts, and complex tables.

A raw PDF often goes through two "doors" at once: it's rasterized to an image (you pay image tokens) *and* text-extracted (you pay text tokens). On Claude an image is \~(w×h)/750 ≈ 1,500 tokens/page; the actual text is only \~700–900. So a 10-page doc is \~23k tokens as a PDF vs \~8k as markdown — and markdown usually reads *more* accurately too. Easiest fix is Microsoft's MarkItDown — `pip install 'markitdown[all]'` then `markitdown report.pdf -o report.md`. One line and your doc takes the cheap door. Catch: don't convert blindly. Scanned PDFs (MarkItDown won't OCR by default — add the `markitdown-ocr` plugin or you get hallucinated numbers), charts (the trend lives in pixels), and gnarly tables (its basic extraction can scramble them — reach for Docling/Marker) are where the text door throws away your answer. For a free detailed article just dm or comment
Original Article

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