Each table is emitted as compact cols + rows arrays instead of one labeled object per field. Same data, far fewer repeated keys, so it uses noticeably fewer tokens, which helps it fit an AI context window. Leave it off for the more human-readable object-per-field format.
How to use it — and why it matters for Quickbase + AI
Quickbase can export an App Summary as a PDF: a full description of your app's tables, fields, field types, constraints, relationships, roles, and features. It is the closest thing to a schema dump that Quickbase gives you. The problem is the PDF is noisy and token-heavy, so pasting it raw into an AI wastes context and confuses the model. pdf2data cleans it up and structures it.
In your app: Settings → App management → App Summary, then print/save it as a PDF.
It is parsed in your browser. PDF.js reads the page layout; nothing is sent anywhere.
Get clean text, or switch to Structured JSON and select just the tables that matter to trim tokens.
Copy or download, then paste into Claude, ChatGPT, or your IDE agent as schema context.
Your schema stays on your machine
An App Summary can describe your entire data model, which is often sensitive. pdf2data is a fully client-side tool: the PDF is read and parsed entirely in this browser tab using self-hosted PDF.js. Your PDF and its parsed schema are never uploaded. The only thing we collect is the contact information you type when you download the structured JSON (first name, last name, company, email), so we know who is using the tool and can help if you want it. Clean text export and copy are completely free. Your details are remembered in this browser so you are not asked again. You can confirm the rest yourself: open your browser's Network tab and watch that the PDF itself is never sent.