Turn a folder of papers into one context window.
Drop the PDFs, your notes, and the data. FileConcat pulls the text out of every paper right in your browser, packs it into one document, and shows you the token count so you know it fits ChatGPT, Claude, or Gemini before you paste.
- Nothing is uploaded
- Token count shown before you paste
- PDFs, notes, and data
Drag your reading folder here
Papers, notes, and data. Read in a second.
Know it fits before you paste.
The hard part of reading with a model is not the reading, it is the budget. FileConcat counts the tokens as it bundles, so you see whether the whole pile lands in one window before you ever paste it.
Counted locally, with the same tokenizer the models use
From a reading pile to a prompt.
- 1
Drop the reading folder
Papers, notes, and datasets together. Nested folders are fine.
- 2
Every file becomes text
PDFs are extracted, notes and data pass straight through, boilerplate is dropped.
- 3
One document, counted up front
You get a single file, with the token count up front so you know whether it lands in one window.
One pile, three kinds of file.
A literature review is rarely just PDFs. Your notes and your numbers go in the same bundle, so the model reasons over the reading and the evidence at once.
Papers
PDFborn-digital preprints and journal PDFs
Notes
MD · TXTyour reading notes and outlines
Data
CSV · JSON · XLSXresults tables and small datasets
Scanned and heavy two-column PDFs read poorly
Text is pulled from the PDF layer, not from the pixels. A scan with no text layer comes through flagged as empty rather than dropped, and a dense two-column layout can arrive out of order. There is no OCR step yet.
A review folder, packed and counted.
Three papers, a note file, and a results table go in. One document comes out, labeled as documents, with the token count already known.
attention-survey/
├── papers/
│ ├── vaswani-2017.pdf
│ ├── devlin-2019.pdf
│ └── brown-2020.pdf
├── notes.md
└── benchmarks.csv<documents project="attention-survey">
<summary>
This is a packed snapshot of a set
of documents, assembled by
fileconcat.com.
File count: 5.
</summary>
...