Get PDF metadata instantly — page count, file size, document type, and whether it has tables. No extraction performed. Use this first to decide which tool to call next: convert_pdf for full text, analyze_pdf for quality audit, or extract_structured for tables.

Convert a PDF to AI-readable Markdown. Automatically detects the PDF type and picks the best extraction method. Returns confidence score and warnings when extraction is limited.

Quick PDF triage — classify type and audit page quality without full extraction. Returns page count, type detection, per-page quality breakdown, and estimated extraction difficulty. Much cheaper than convert_pdf for initial assessment.

Convert all PDFs in a directory to Markdown. Returns a summary with per-file results.

Extract structured data from a PDF — tables as JSON, key-value pairs, and optionally map to a JSON schema. Returns tables with headers/rows, detected key-value pairs with auto-normalization (dates, amounts, rates), and schema-mapped output if a schema is provided.

Stream extraction events for a PDF as NDJSON.

Use for large documents (100+ pages) where waiting for the full extraction is impractical. The response body is newline-delimited JSON with one object per line:

{"type":"classified","data":{"page_count":N,"page_types":[...]}}
{"type":"page","data":{"page_num":0,"text":"...","confidence":0.92,...}}
{"type":"warning","data":{"message":"..."}}        (zero or more)
{"type":"complete","data":{"total_confidence":0.94,"ocr_pages":[...],...}}

The first event is always classified; the last is always complete. Each page event arrives as soon as that page is extracted, including OCR re-extraction in standard/high quality modes.

Audit an extraction of a PDF for silently-dropped pages — the failure where an extractor returns nothing for a page that has real text while reporting success. Pass extracted_text with another engine's output (Reducto, Mistral OCR, LlamaParse, Docling, an in-house parser — as JSON, Markdown, or plain text) to certify THAT engine against the source PDF; omit it to have pdfmux extract the document itself and certify its own read. Returns the per-page audit — each page marked usable / silently-empty / recovered / review / unverifiable — the "N of M pages silently dropped" headline, and an overall PASS/REVIEW/FAIL verdict with a tamper-evident signature. Reuses pdfmux's own audit pass as the ground truth.