Document intelligence

Turn any PDF or image URL into structured data - metadata, extracted text, sliced page ranges, OCR for scanned docs, decoded barcodes / QR codes - without falling back to a vision LLM guess. Built for the messy 30% of documents where pdf-to-markdown alone returns nothing useful.

When to use this pack

An agent gets a PDF link from a webhook (invoice, contract, receipt, regulatory filing) or an image URL (shipping label, scanned form, photographed ticket) and needs to extract structured fields deterministically. content-extraction handles the easy path; document-intel adds metadata inspection, page slicing, OCR fallback for scanned PDFs, embedded barcode / QR decoding, and PDF reassembly for downstream sharing.

Tools in this pack

All 7 run inside the single $0.024 call above. Each is also callable on its own if you only need one part.

• PDF info POST /api/pdf-info Inspect a PDF without downloading the whole thing into your model: page count, title, author, subject, creator, producer, creation/modification dates, encryption flag, and byte size. Body: {"url":"https://…/file.pdf"}.
• PDF to Markdown POST /api/pdf-to-markdown Convert a PDF to clean markdown: headings, paragraphs, and bullets reconstructed from the text layer - ready to drop into a model's context. Body: {"url":"https://…/file.pdf"}.
• Extract / split PDF pages POST /api/pdf-extract-pages Pull a subset of pages into a new PDF (split). Body: {"url":"https://…/file.pdf","pages":"1-3,5"}. Returns the new PDF as base64.
• Image OCR POST /api/image-ocr Extract text from an image (PNG/JPEG): returns the full text, overall confidence (0-100), and per-line bounding boxes. Send either {image: base64} or {url: 'https://…'}. Pure-CPU Tesseract via tesseract.js - no upstream API, no keys. Default lang 'eng'; pass 'lang' (ISO 639-2) for others.
• Barcode / QR decode POST /api/barcode-decode Decode a barcode or QR code from an image. Send a base64 PNG or JPEG (or a data: URL); returns the decoded text and the symbology. Reads QR, DataMatrix, and 1D barcodes (EAN/UPC/Code39/Code128/ITF/Codabar). Deterministic, no network, no model.
• Merge PDFs POST /api/pdf-merge Combine several PDFs into one, in order. Body: {"urls":["https://…/a.pdf","https://…/b.pdf"]}. Returns the merged PDF as base64 plus page count and size.
• Images to PDF POST /api/images-to-pdf Combine PNG/JPEG images into a single PDF, one image per page. Body: {"urls":["https://…/1.png","https://…/2.jpg"]}. Returns the PDF as base64.

Bought one at a time, these 7 tools cost $0.026 together; the pack is that sum less a 10% bundle discount, rounded up to the $0.001 settlement floor, which is $0.024.

Workflow

1. Start with pdf-info - confirms the URL actually serves a PDF (some webhooks lie about content-type), returns the page count for scoping, and surfaces flags like `encrypted` so you don't waste a pdf-to-markdown call that will fail. Skip only if you already know the document's shape.
2. Run pdf-to-markdown for the happy path. Digital-native PDFs - invoices generated by accounting software, Word/Google-Docs exports, EDGAR filings - come back as clean markdown in one call. This handles ~70% of real-world PDF intake; the next steps are for the other 30%.
3. If the document is long (>20 pages) and you only need a slice - the signature page on a contract, the line-item table on an invoice, an appendix from a research report - call pdf-extract-pages with the page range first. Then run pdf-to-markdown on the extracted slice. Cheaper, faster, and the smaller payload reduces noise downstream.
4. If pdf-to-markdown returns <50 characters of text, the PDF is a raster (a scanned document, a photo-of-a-receipt PDF, or a contract that was printed and re-scanned). Fall back to image-ocr - feed it the rendered page image. Tesseract-grade OCR is deterministic and surfaces the text that pdf-to-markdown couldn't.
5. For invoices, shipping labels, event tickets, and packaging, the high-value structured payload is often encoded in a barcode or QR code rather than visible text. Run barcode-decode on the page image - it returns the raw payload (shipping tracking numbers, EAN/UPC product codes, base64 / JWT ticket payloads). Feed JWT-shaped payloads to the decode-blob pack for further unwrapping.
6. Use pdf-merge when you've extracted slices from multiple PDFs and want to combine them into a single artifact - building a deal package (term sheet + signature page + appendix), or stitching a multi-vendor invoice export back together for accounting.
7. Use images-to-pdf when the source material was a set of phone photos (receipts, whiteboard captures, scanned pages handed to you out-of-order) and you need to wrap them into one shareable PDF - either as the final deliverable or as the input to a re-run of this same pipeline at higher quality.

Arguments

What one call returns

A JSON object with pack, args, steps, summary; steps holds one entry per tool (pdf-info, pdf-to-markdown, pdf-extract-pages, image-ocr, barcode-decode, pdf-merge, images-to-pdf), each with its own result or error. Full example on the API page.

Call it directly

Any x402 client pays the 402 and gets the whole workflow back in one response. With the agent402-client SDK (npm i agent402-client, an ES module):

import { Agent402 } from "agent402-client";
// payFetch: an x402-wrapped fetch your wallet signs (@x402/fetch).
// Tools on the free tier need no options: new Agent402() pays them by proof-of-work.
// an existing prepaid credits key also works: new Agent402({ creditsKey })
const client = new Agent402({ fetch: payFetch });
const result = await client.call("skill-document-intel", {"url":"https://agent402.tools/fixtures/sample-invoice.pdf"});

Run it in Claude

claude mcp add agent402 -s user -- npx -y agent402-mcp@latest

Then paste this prompt into Claude:

Process this invoice with Agent402: https://agent402.tools/fixtures/sample-invoice.pdf. (1) Run pdf-info to confirm it's a PDF, get the page count, check the `encrypted` flag. (2) If not encrypted, call pdf-to-markdown with the URL. (3) Inspect the returned markdown - if it has <50 chars of text, the PDF is scanned: call pdf-extract-pages to get each page as an image, then run image-ocr on each. (4) If you still can't find a tracking number after parsing the OCR text, run barcode-decode on page 1 to surface an embedded QR / barcode payload. (5) Return a single JSON object: {invoiceNumber, totalAmount, vendor, lineItems, trackingNumber, source: "pdf-to-markdown" | "image-ocr" | "barcode-decode"} - populate `source` based on which extraction path actually produced the data. Budget ≤ $0.05 per document; all of these tools are wallet-only (paid per call).

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