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wtf is paper-review-and-digest?

drpwchen/paper-review-and-digest — explained in plain English

Analysis updated 2026-05-18

31PythonAudience · researcherComplexity · 3/5Setup · moderate

TL;DR

Two Claude Code skills that appraise whether an academic paper can be trusted and help a reader quickly absorb its content, using deterministic Python checks alongside the AI's judgment.

Mindmap

mindmap
  root((repo))
    What it does
      Appraises paper trust
      Digests paper content
      Deterministic GRADE scoring
    Tech stack
      Python
      Claude Code
      CrossRef API
    Use cases
      Journal club review
      Citation verification
      Fast content absorption
    Audience
      Researchers
      Physicians

Code map

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Why would anyone build with this?

REASON 1

Run a journal-club-style appraisal of a paper's evidence quality, risk of bias, and citation accuracy.

REASON 2

Get a fast, layered digest of a paper's content ending in self-test recall questions.

REASON 3

Verify that a paper's references are real and correctly cited using the CrossRef check.

REASON 4

Combine with the author's other tools to discover, fetch, and then review a research paper.

What's in the stack?

PythonClaude CodeCrossRef API

How it stacks up

drpwchen/paper-review-and-digest0xsero/tailscale-mullvad-toggleafspies/clawdmoji
Stars313131
LanguagePythonPythonPython
Setup difficultymoderateeasyeasy
Complexity3/52/52/5
Audienceresearcherdevelopergeneral

Figures from each repo's GitHub metadata at analysis time.

How do you spin it up?

Difficulty · moderate Time to first run · 30min

Requires Claude Code plus copying and filling in a configuration file, core scoring needs no network, but the CrossRef reference check does.

Not sufficiently specified in the provided material.

Wtf does this do

This project provides two skills for Claude Code, Anthropic's coding assistant tool, that are meant to help someone properly read a single academic paper. One skill, paper-review, judges whether a paper can be trusted. The other, paper-digest, helps a reader absorb what the paper actually says. It was built by a practicing physician for real journal-club and clinical use, then shared more broadly. The paper-review skill performs a detailed appraisal: it checks the credibility of the journal and the track record of the authors, verifies references against the live CrossRef database to catch fake or mismatched citations, checks for bias using a method chosen based on the type of study, and computes a GRADE certainty rating, which is a standard way of scoring how trustworthy a body of medical evidence is. A key design choice is that the language model only makes judgment calls, while separate small Python scripts do the actual math and logic. One script recalculates the final GRADE score from the model's individual ratings rather than trusting the model's own summary, and another script checks whether the model's reasoning contains logical leaps, such as treating a single study as proven or treating an indirect measurement as if it proved a direct clinical benefit. The paper-digest skill instead focuses on helping someone learn the paper's content quickly, offering three layers of detail and ending with self-test questions. It refuses to produce a digest if it cannot access the paper's full text, so it will not generate a summary based only on the abstract. The README describes this as the reading step in a three-part pipeline: a separate tool called paper-radar discovers and ranks papers, another tool called paper-fetch downloads their full text, and this project appraises and digests them. The two Python scripts here have no external dependencies and run with the standard Python library only, with no installation or network access required for the scoring itself, though the CrossRef reference check does require internet access. To use it, someone places the paper-review and paper-digest folders into their Claude Code skills directory, copies an example configuration file, and fills in any optional settings, since the core functionality works without extra configuration. The author describes this as a one-time reference implementation rather than an actively maintained product. It is explicitly not medical advice and does not replace reading the paper directly.

Yoink these prompts

Prompt 1
Walk me through installing the paper-review and paper-digest skills in Claude Code.
Prompt 2
Explain how the deterministic GRADE recompute script differs from asking a model to grade evidence directly.
Prompt 3
Run /paper-review on this paper's DOI and explain the risk-of-bias findings in plain language.
Prompt 4
Run /paper-digest on this paper and summarize the three layers of detail it produces.
Prompt 5
Explain what the argument-gap linter catches that a plain semantic read of a paper would miss.

Frequently asked questions

wtf is paper-review-and-digest?

Two Claude Code skills that appraise whether an academic paper can be trusted and help a reader quickly absorb its content, using deterministic Python checks alongside the AI's judgment.

What language is paper-review-and-digest written in?

Mainly Python. The stack also includes Python, Claude Code, CrossRef API.

What license does paper-review-and-digest use?

Not sufficiently specified in the provided material.

How hard is paper-review-and-digest to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is paper-review-and-digest for?

Mainly researcher.

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