pdf

The pdf worker parses PDF documents on the machine. A PDF is not text: reading one with a file-reading function returns binary noise and spends the context on it, so every PDF goes through pdf::* instead. Parsing is local, needs no credential, and sends nothing anywhere.

Its first job is a routing decision. pdf::classify samples the document's content streams and answers whether the pages hold real characters or are photographs of pages, plus which individual pages cannot be read without a vision model and why. That verdict decides whether the rest of the work is worth doing at all, and it is what separates "this document is empty" from "this document is a scan".

Its second job is reading. Text-based documents convert to markdown that keeps the shape of the original, because headings, lists and tables are recovered from font sizes and page geometry rather than from any structure the file promises. Underneath that sit the positions themselves, for callers that need to know where text is and not only what it says.

This worker is called on demand. It registers no harness hook and injects nothing into any prompt, so a conversation that never touches a document never pays for it. Reach for it when one appears.

When to Use

• A conversation names a PDF path or hands one over: call pdf::classify before anything else. Never read a PDF with a file-reading function; it returns binary noise and spends the context on it.
• Read a document: pdf::to-markdown, narrowed with pages when it is long.
• Search or embed a document rather than read it: pdf::extract-text.
• Decide whether a document is worth sending to a vision model, and which of its pages: pdf::classify, then read pages_needing_ocr and ocr_reasons.
• A vision model located a region and you want the real characters rather than its transcription: pdf::extract-regions.
• Reason about layout, headings by size, or where a value sits on the page: pdf::extract-items.

Boundaries

• Nothing here rasterizes a page, so nothing here can OCR. Scanned and image-based documents are classified and routed, never read. Image content is reported as a placeholder with a real box and no pixels. document::ocr is where routed pages go when the document worker is installed: it renders them and reads them with a vision model, so it costs money per page. Hand it the pages_needing_ocr this worker named rather than the whole file.
• suspected_garbled_text in ocr_reasons means the text layer decodes to nonsense. Do not trust the extraction, whatever document_type says.
• Responses are capped. truncated: true with a much larger total_chars means you hold a fragment and must not answer from it. Narrow with pages rather than raising the cap: conversion cost scales with the document, so a page filter is faster as well as smaller. max_chars: 0 lifts the cap and belongs in a pipeline moving a document to storage, not in a call whose result lands in the conversation.
• Encrypted documents take a password on pdf::classify and pdf::to-markdown only. The other three cannot decrypt and say so.
• Page numbers are 1-indexed everywhere, in requests and responses.
• Coordinates differ by function and every response states which it used: pdf::extract-items reports PDF points from the bottom left, pdf::extract-regions takes boxes in PDF points from the top left. Assuming the wrong one returns text from the wrong end of the page with no error.

Functions

• pdf::classify — the routing call. Document type, confidence, page count, the 1-indexed pages needing OCR, and a machine-readable reason per page.
• pdf::to-markdown — markdown with headings, lists, links and tables recovered; optional page filter, per-page output, and a fidelity or compact profile.
• pdf::extract-text — plain text, no structure recovery. Cheaper than markdown when the result will be searched or embedded.
• pdf::extract-items — every positioned run of characters with its box, font, size, and recovered bold, italic, underline and strikeout.
• pdf::extract-regions — the text, or a markdown table, inside given boxes on given pages.