paper-self-review

paper-self-review is a skill for Claude Code from Galaxy-Dawn/claude-scholar. It costs 68 tokens per session (1,170 once invoked), scanned A, original, MIT.

A checklist for reviewing a research paper before submission, covering its structure, reasoning, citations, and claims.

In plain words
What is it for?
Use it to audit a paper's completeness, check whether evidence supports its claims, and prepare it for submission.
Why use it?
It helps find missing sections, unsupported conclusions, citation problems, and gaps between the research question, method, results, and claims.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the claude-scholar plugin — 45 skills, 34 commands, 6 agents, 5 hooks shipped together

Good fit Use it to audit a paper's completeness, check whether evidence supports its claims, and prepare it for submission.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/galaxy-dawn/claude-scholar/paper-self-review
About the project

Claude Scholar is a semi-automated research assistant for academic research and software development, supporting literature review, coding, experiments, reporting, writing, and project knowledge management. Computer science and AI researchers use it across the research workflow with several coding-agent platforms; the catalogue contains its skills, commands, agents, hooks, plugin, and instruction.

Galaxy-Dawn/claude-scholar · 5,431 stars · on GitHub

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Galaxy-Dawn/claude-scholar --skill paper-self-review
Clone the repo
git clone --depth 1 https://github.com/Galaxy-Dawn/claude-scholar

Made for: Claude Code.

Or install claude-scholar, the plugin that ships this one along with the rest of its 45 skills, 34 commands, 6 agents, 5 hooks.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for paper-self-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/galaxy-dawn/claude-scholar/paper-self-review/github.svg)](https://agentmods.dev/skills/galaxy-dawn/claude-scholar/paper-self-review)
Your own site
<a href="https://agentmods.dev/skills/galaxy-dawn/claude-scholar/paper-self-review"><img src="https://agentmods.dev/badge/skills/galaxy-dawn/claude-scholar/paper-self-review/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for paper-self-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/galaxy-dawn/claude-scholar/paper-self-review"><img src="https://agentmods.dev/badge/skills/galaxy-dawn/claude-scholar/paper-self-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 68 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,170 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 13 May 2026
  • Snyk pass 13 May 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00068 $0.01170
Opus 5 $0.00034 $0.00585
Sonnet 5 $0.00014 $0.00234
Haiku 4.5 $0.00007 $0.00117

Measured 8d ago against content hash e9c0040db739, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

paper-self-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/paper-self-review/SKILL.md · 162 lines

How it starts

The opening of the file, as written. The whole thing — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Paper Self-Review

A systematic paper quality checking tool that helps researchers conduct comprehensive self-review before submission.

Core Features

1. Structure Review

Check whether all sections of the paper are complete and conform to academic standards:

  • Does the Abstract include problem, method, results, and contributions?
  • Does the Introduction clearly articulate research motivation and background?
  • Is the Method detailed enough to be reproducible?
  • Do the Results sufficiently support the conclusions?
  • Does the Discussion address limitations and future work?

2. Logic Consistency Check

Verify the logical coherence of the paper:

  • Do research questions match the methodology?
  • Does the experimental design support the research hypotheses?
  • Are result interpretations reasonable?
  • Are conclusions supported by evidence?

3. Citation Completeness

Check the completeness and accuracy of citations:

  • Are all citations present in the references?
  • Is the reference format consistent?
  • Are key related works cited?
  • Do citations accurately reflect the original content?

4. Research Claim Audit

Check whether the paper's claims are supported by the available evidence:

  • Are the main claims supported by results, citations, or analysis artifacts?
  • Are speculative observations clearly marked as tentative?
  • Does the paper avoid stronger wording than the evidence allows?
  • Are negative results, limitations, and missing baselines presented honestly?
  • Do conclusions stay inside the tested scope?

This audit does not replace results-analysis for statistics or citation-verification for bibliographic verification. It checks whether paper claims correctly use the available evidence.

5. Figure/Table Quality

Evaluate the quality and effectiveness of figures and tables:

  • Do all figures/tables have clear titles and captions?
  • Do figures/tables support the text narrative?
  • Are figures/tables clear and readable?
  • Do formats comply with journal/conference requirements?

Read the full file on GitHub · 162 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 162 lines · 68 tokens per session scan A e9c0040db739

Subscribe to this mod's changes

paper-self-review is a skill published in the GitHub repository Galaxy-Dawn/claude-scholar (5,431 stars, last pushed 15d ago), licensed MIT. It adds 68 tokens to every session and 1,170 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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