A PDF is a set of drawing instructions, and the text a reader sees is one layer of it — sometimes present, sometimes not, never the whole. What a model is handed instead is a decision, paid for on every page, and these notes are for someone deciding what to demand of a document pipeline before any model sees a page, not someone deciding whether to buy one.
A page pays twice on Claude, as image and as text. What conversion to Markdown removes on sixteen public documents, counted with the vendor's counter, and what it cannot keep.
Paper 002Conversion removes a flat page-image charge. The 64% first published was counted with a proxy tokenizer on a private corpus; re-counted properly, the number moved down.
Paper 003Open research on reading what is in a picture rather than the glyphs on it, and what a claim about a drawing needs before it reaches a model.
Paper 004Where converted text should live, what repetition makes compressible, why a recorded property is not a promise, and a ledger of what is open.
A PDF handed natively to Claude is billed for a picture of each page and for the text lifted off it — a feature before it is a cost (platform.claude.com/docs/en/build-with-claude/pdf-support, read 11 September 2026). Converting those pages to Markdown with crunch 0.1.0 removes 53% of the tokens — a mean over sixteen public PDFs, 861 pages, counted with Anthropic's own count_tokens on Claude Opus 5, Sonnet 5 and Fable 5.1, per document 11.1% to 73.1%. That 53% corrects a 64% published before it, counted with another vendor's tokenizer on a private corpus. Conversion is not free of loss — a merged cell is flattened — and what is in a picture rather than printed on it is open research here, not a result.
Every figure here is reproducible from a published artefact or a named party's dated statement; a hypothesis is called one. The method came from crunch.md, a Digital One product: the corpus is public and the native column can be re-counted by anyone holding the manifest and a key; the engine's repository is not. Deliberately absent: prices, plans and tiers, and deployment internals. The open directions in Papers 003 and 004 are not settled here; everything else is here in full, because a measurement you cannot re-run is a measurement you cannot check. The GDPR appears only as a measured document, and where a paper turns on jurisdiction it says why a technical property matters. These notes are not legal analysis, they are not advice, and where a legal question is genuinely unsettled the papers say so rather than resolving it in passing.
These notes are contributed under CC BY 4.0: quote them, reproduce them and build on them, with attribution, a link to the licence and an indication of any changes. The Foundation is an entity in formation; no public-benefit (ANBI) status is claimed at this time.