receipts

A hundred hallucinated citations made headlines at NeurIPS. The quieter problem is the citations that are real but wrong: the paper exists, and it doesn’t say what you claimed it said.

receipts is a small tool I built for a specific, unglamorous chore: making sure a manuscript’s citations actually match their sources before a reviewer, or a reader, finds out they don’t. It runs inside Claude Code, Anthropic’s terminal assistant, and it is open source under the MIT license.

The problem nobody counts

In early 2026, GPTZero reported 100 hallucinated citations across 51 papers at NeurIPS 2024. Those are the fake ones: references to work that does not exist. They are the easy case, because a reference either resolves or it doesn’t.

Nobody is counting the harder case: the real papers that don’t say what the author claims. Your manuscript says “Smith et al. achieved 99% accuracy on all benchmarks.” The actual paper says “we achieve 73% accuracy on the standard benchmark.” That isn’t fraud. It’s human memory, plus exhaustion, plus LLM assistance, adding up to systematic misquotation. receipts is built to catch it before your reviewers do.

What it does

Give it your paper. Give it the PDFs you cited. It reads both, then tells you what’s wrong. There is no upload and no web service: it works on the files in a folder on your machine, through Claude Code, for roughly $0.50 to $5 per paper.

For every citation it returns a verdict, and for anything that needs fixing it puts the exact manuscript sentence next to the exact source sentence, with the correction spelled out.

The three verdicts

Reference 1: ADJUST   (Srivastava et al., "Dropout", JMLR)

  Manuscript claims:
    "the optimal dropout probability is p=0.5 for ALL layers"

  Source states:
    "p=0.5 for hidden units and p=0.8 for input units"

  Assessment: NOT SUPPORTED

  Required correction:
    "p=0.5 for all layers"
        becomes
    "p=0.5 for hidden units, p=0.8 for input units"

How to run it

receipts installs as a command inside Claude Code and adds almost nothing to your context. You need Node.js and either an Anthropic API key or a Claude Pro/Max plan.

1. Install Claude Code. npm install -g @anthropic-ai/claude-code
2. Install the command. npx receiptscc, once. You’ll see a receipt banner when it works.
3. Set up a folder. Put your paper in a folder, with the PDFs you cited in a sources subfolder.
4. Run it. From that folder, start Claude Code with claude, then type /receipts.
5. Read the results. receipts writes a RECEIPTS.md file: a verdict for every citation, with the fixes.

thesis/
    my_paper.pdf          your manuscript (any name)
    sources/              the PDFs you cited
        smith_2020.pdf
        jones_2021.pdf
        chen_2019.pdf

Built to be cheap and light

The install footprint is 29 tokens: a 13-token command definition plus a 16-token verifier-agent template. That’s the entire permanent cost to your Claude Code context. The actual checking runs on Claude’s normal token budget, which is where the per-paper cost comes from, so you can run a cheap model on drafts and a stronger one on the final submission.

Approximate cost per paper, from the project README. Haiku for drafts, Opus for the final pass.

Why I built it

I’m an MD/PhD candidate, and I got tired of re-checking citations by hand at 2am before deadlines. The same discipline runs through my research on trustworthy clinical AI: a model’s output is only worth as much as what you can verify it against. receipts is that check, turned into one command, aimed at the moment where it’s cheapest to fix a mistake, before anyone else reads it.

receipts is an open-source research tool, not legal advice. You are responsible for having the right to upload and process the documents you check, including compliance with copyright, publisher terms, and institutional policy. The tool is provided “as is,” and its use is also subject to Anthropic’s terms of service.