Agent skill

Citation Verification Guide

by Galaxy-Dawn in Galaxy-Dawn/claude-scholar

Reference guidance for checking every citation in academic writing against canonical sources such as DOI, arXiv, CrossRef and Semantic Scholar, to catch fake or wrong references.

MITAuto-check passedResearch & Science

Install Citation Verification Guide

skills CLI
$ npx skills add Galaxy-Dawn/claude-scholar --skill citation-verification -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Galaxy-Dawn/claude-scholar citation-verification --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Galaxy-Dawn/claude-scholar.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/citation-verification .claude/skills/citation-verification && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
citation-verification
GitHub stars
5.7k
Used in
2 other repos
Token cost
~1.9k tokens
SKILL.md length
817 words
Files
9 (incl. scripts, references)
Skills in repo
34
Repo updated
First seen
Licence
MIT

At a glance

Reference guidance for checking every citation in academic writing against canonical sources such as DOI, arXiv, CrossRef and Semantic Scholar, to catch fake or wrong references.

  • Works in 4 steps: Proactive Verification (Verify During… → Canonical Metadata Verification → Information Matching Verification → …
  • Checking that every reference in a paper draft is real
  • SKILL.md covers Core Problems, Verification Principles, Verification Workflow and Usage Guide, plus 2 more sections
  • Runs Python scripts from its folder

What it does

The core principle is to verify each citation while writing rather than afterwards, using programmatic or canonical scholarly sources first. The problems it targets are fake citations pointing at non-existent papers, mismatched authors, titles or years, inconsistent formatting and work that is referenced but not cited. It singles out AI-assisted writing, noting an error rate of about 40% for AI-generated citations, so every citation should be checked through a web search.

The authority order runs from the DOI or publisher page, then arXiv, CrossRef, Semantic Scholar and Zotero metadata imported from a verified identifier, with Google Scholar kept for manual discovery or fallback. The steps are to find an identifier, confirm title, first author, year, venue and identifier, and fetch BibTeX from a programmatic source. Items found only on Google Scholar are marked for manual verification. Titles may differ in small ways such as capitalization, and at least the first author must match.

Reference files cover API usage, common errors and verification rules, and the Python scripts api-clients.py, format-checker.py and verify-citations.py support the checks. The guide is meant to back an ml-paper-writing skill.

When your agent uses it

  • Checking that every reference in a paper draft is real
  • Fetching trustworthy BibTeX for a citation from its DOI or arXiv page
  • Auditing AI-generated citations for fabricated or mismatched entries
  • Deciding which source to trust when citation metadata disagree

Example prompts

  • “Verify every reference in references.bib against CrossRef and arXiv.”
  • “I got this citation from an AI assistant. Confirm the paper exists and the authors and year are right.”
  • “Pull the BibTeX for the Attention Is All You Need paper from arXiv and check the first author.”

Requirements

  • Network access to arXiv, CrossRef and Semantic Scholar
  • Python, for the bundled scripts

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Proactive Verification (Verify During Writing)
  2. Canonical Metadata Verification
  3. Information Matching Verification
  4. Claim Verification

What it can do on your machine

Read from SKILL.md and the folder at commit 9037873. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 4 files in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Citation Verification Guide loads about 1.9k tokens when it runs, and up to ~9.2k if it reads all its reference files. Until then it costs about 96 tokens; SKILL.md has 817 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~96
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~9.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from Galaxy-Dawn/claude-scholar at commit 9037873, republished under its MIT licence (© Galaxy-Dawn). 817 words, ~1,894 tokens.

Download SKILL.mdSave it as .claude/skills/citation-verification/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.
name
citation-verification
description
This skill provides reference guidance for citation verification in academic writing. Use when the user asks about "citation verification best practices", "how to verify references", "preventing fake citations", or needs guidance on citation accuracy. This skill supports ml-paper-writing by providing detailed verification principles and common error patterns.
tags
Research, Academic, Citation, Reference
version
0.1.0

Citation Verification Reference Guide

A reference guide for citation verification in academic paper writing, providing verification principles and best practices.

Core Principle: Proactively verify every citation during the writing process using programmatic or canonical scholarly sources first: arXiv, DOI/CrossRef, Semantic Scholar, publisher landing pages, and Zotero metadata. Google Scholar is useful for manual discovery, but it is not the canonical verification authority.

Core Problems

Citation issues in academic papers seriously impact research integrity:

  1. Fake citations - Citing non-existent papers (common issue with AI-generated citations)
  2. Incorrect information - Mismatched authors, titles, years, etc.
  3. Inconsistent formatting - Mixed citation formats
  4. Missing citations - Referenced but uncited work

These issues can lead to:

  • Paper rejection or retraction
  • Damage to academic reputation
  • Reviewers questioning research rigor

Special risk with AI-assisted writing: AI-generated citations have approximately 40% error rate; every citation must be verified via WebSearch.

Verification Principles

This skill provides verification principles based on canonical scholarly metadata and claim-level checking:

1. Proactive Verification (Verify During Writing)

Core idea: Verify immediately when adding a citation, rather than checking after writing is complete.

  • Search for the paper via WebSearch each time a citation is needed
  • Confirm the paper exists on Google Scholar
  • Add to bibliography only after verification passes
2. Canonical Metadata Verification

Preferred authority order:

  1. DOI / publisher landing page
  2. arXiv ID or arXiv landing page
  3. CrossRef
  4. Semantic Scholar
  5. Zotero metadata imported from a verified identifier
  6. Google Scholar only for manual discovery or fallback lookup

Verification steps:

  1. Find a DOI, arXiv ID, publisher URL, or verified Zotero item.
  2. Confirm title, first author, year, venue, and identifier.
  3. Fetch BibTeX from CrossRef, arXiv, publisher metadata, Zotero, or another programmatic source when possible.
  4. If only Google Scholar can find the item, mark it as manual verification and do not treat the BibTeX as final until metadata is checked elsewhere.
3. Information Matching Verification

Information that must match:

  • Title (minor differences allowed, e.g., capitalization)
  • Authors (at least the first author must match)
  • Year (±1 year difference allowed, considering preprints)
  • Publication venue (conference/journal name)
4. Claim Verification

Key principle: When citing a specific claim, you must confirm the claim actually appears in the paper.

  • Use WebSearch to access the paper PDF
  • Search for relevant keywords
  • Confirm the accuracy of the claim
  • Record the section/page where the claim appears

Verification Workflow

Integration into Writing Process
Need a citation during writing
    ↓
Find DOI / arXiv ID / publisher page / verified Zotero item
    ↓
Verify metadata with CrossRef / arXiv / Semantic Scholar / publisher / Zotero
    ↓
Confirm paper details
    ↓
Get BibTeX
    ↓
(If citing a specific claim) Verify the claim
    ↓
Add to bibliography

Key point: Verification is part of the writing process, not a separate post-processing step.

Usage Guide

Using with ml-paper-writing

The verification principles of this skill are integrated into the Citation Workflow of the ml-paper-writing skill.

Auto-trigger: Citation verification is automatically executed when writing papers with the ml-paper-writing skill.

Manual reference: Refer to this skill when you need detailed verification principles.

Verification Step Example

Scenario: Need to cite the Transformer paper

Step 1: WebSearch lookup
Query: "Attention is All You Need Vaswani 2017"
Result: Found multiple sources for the paper

Step 2: Google Scholar verification
Query: "site:scholar.google.com Attention is All You Need Vaswani"
Result: ✅ Paper exists, 50,000+ citations, NeurIPS 2017

Step 3: Confirm details
- Title: "Attention is All You Need"
- Authors: Vaswani, Ashish; Shazeer, Noam; Parmar, Niki; ...
- Year: 2017
- Venue: NeurIPS (NIPS)

Step 4: Get BibTeX
- Click "Cite" on Google Scholar
- Select BibTeX format
- Copy BibTeX entry

Step 5: Add to bibliography
- Paste into .bib file
- Use \cite{vaswani2017attention} in the paper
Show full SKILL.md (354 more words)Show less
Handling Verification Failures

If the paper cannot be verified through canonical sources:

  1. Check spelling - Is the title or author name correct?
  2. Try different queries - Use different keyword combinations
  3. Find alternative sources - Try arXiv, DOI, CrossRef, Semantic Scholar, publisher pages, or Zotero
  4. Mark as pending - Use [CITATION NEEDED] marker
  5. Notify the user - Clearly state the citation cannot be verified

If information doesn't match:

  1. Confirm the source - Did you find the correct paper?
  2. Check versions - Preprint vs. published version
  3. Update information - Use the most accurate version
  4. Record discrepancies - Note the reason for differences

Best Practices

Preventing Fake Citations
  1. Never generate citations from memory - AI-generated citations have 40% error rate
  2. Use WebSearch to find - Verify every citation through WebSearch
  3. Confirm on Google Scholar - Verify paper existence on Google Scholar
  4. Verify promptly - Verify when adding citations, don't wait until finished
Handling Verification Failures
  1. Don't guess - If you can't find the paper, don't fabricate information
  2. Mark clearly - Use [CITATION NEEDED] to mark explicitly
  3. Notify the user - Clearly state which citations cannot be verified
  4. Provide reasons - Explain why verification failed (not found, info mismatch, etc.)
Improving Verification Accuracy
  1. Complete queries - Include title, author, year
  2. Check citation count - Citation count on Google Scholar is a credibility indicator
  3. Confirm venue - Verify conference/journal name is correct
  4. Verify claims - When citing specific claims, confirm they exist in the paper
Common Pitfalls

❌ Wrong approach:

  • Generating BibTeX from memory
  • Skipping Google Scholar verification
  • Assuming a paper exists
  • Not marking unverifiable citations

✅ Correct approach:

  • Search every citation with WebSearch
  • Confirm on Google Scholar
  • Copy BibTeX from Google Scholar
  • Clearly mark unverifiable citations

Summary

Core Principle: Proactively verify every citation during the writing process using WebSearch and Google Scholar.

Key Steps:

  1. WebSearch to find the paper
  2. Google Scholar to verify existence
  3. Confirm details
  4. Get BibTeX
  5. Verify claims (if needed)
  6. Add to bibliography

Failure handling: When verification fails, mark as [CITATION NEEDED] and clearly notify the user.

Integration: The principles of this skill are integrated into the ml-paper-writing skill for automatic verification.

© Galaxy-Dawn, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 8 other files (scripts, references) in skills/citation-verification of Galaxy-Dawn/claude-scholar.

  • SKILL.md
  • references/README.md
  • references/api-usage.md
  • references/common-errors.md
  • references/verification-rules.md
  • scripts/README.md
  • scripts/api-clients.py
  • scripts/format-checker.py
  • scripts/verify-citations.py

Open the folder on GitHubat commit 9037873

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in Galaxy-Dawn/claude-scholar, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Citation Verification Guide next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Citation Verification Guide compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Citation Verification Guide this skillGalaxy-Dawn/claude-scholar5.7k2 repos~1.9kAutomated safety check: PassMIT
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Paper NavigatorAI4Scientist/nano-scientist128—~7.7kAutomated safety check: NotesNone
Social Science Paper Writingfakerqwq/social-science-paper-writing-skill382—~7kAutomated safety check: PassNone
Literature Reviewneflibata-feng/MyArxiv-Agent12620 repos~5.9kAutomated safety check: NotesMIT
Citation ManagementK-Dense-AI/claude-scientific-writer2.4k2 repos~3.9kAutomated safety check: NotesMIT

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Questions about Citation Verification Guide

What does Citation Verification Guide do?

Reference guidance for checking every citation in academic writing against canonical sources such as DOI, arXiv, CrossRef and Semantic Scholar, to catch fake or wrong references. The core principle is to verify each citation while writing rather than afterwards, using programmatic or canonical scholarly sources first. The problems it targets are fake citations pointing at non-existent papers, mismatched authors, titles or years, inconsistent formatting and work that is referenced but not cited.

When should I use Citation Verification Guide?

Citation Verification Guide fits situations like: checking that every reference in a paper draft is real; fetching trustworthy BibTeX for a citation from its DOI or arXiv page; auditing AI-generated citations for fabricated or mismatched entries; deciding which source to trust when citation metadata disagree.

How do I install Citation Verification Guide in Claude Code?

Run `npx skills add Galaxy-Dawn/claude-scholar --skill citation-verification -a claude-code`. Or copy the skill folder (skills/citation-verification in Galaxy-Dawn/claude-scholar) into .claude/skills/citation-verification in your project. Claude Code loads it when a task matches its description.

How do I install Citation Verification Guide in Codex?

Run `npx skills add Galaxy-Dawn/claude-scholar --skill citation-verification -a codex`. Or copy the skill folder (skills/citation-verification in Galaxy-Dawn/claude-scholar) into .agents/skills/citation-verification in your project. Codex loads it when a task matches its description.

Can I use Citation Verification Guide in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Galaxy-Dawn/claude-scholar --skill citation-verification -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/citation-verification, .gemini/skills/citation-verification, .github/skills/citation-verification and .opencode/skills/citation-verification in your project.

What does Citation Verification Guide need to run?

Going by SKILL.md and its folder, Citation Verification Guide needs Python for the scripts in its folder. Our summary lists: Network access to arXiv, CrossRef and Semantic Scholar; Python, for the bundled scripts.

Does Citation Verification Guide access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Citation Verification Guide safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Citation Verification Guide use?

Citation Verification Guide is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Citation Verification Guide use?

About 1.9k tokens (SKILL.md is roughly 7.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 7.3k tokens, read only when the agent opens those files.

What are the alternatives to Citation Verification Guide?

Skills that share tags, products or a category with Citation Verification Guide: Citation Verification (Light0305/Light-skills, 640 stars), Paper Navigator (AI4Scientist/nano-scientist, 128 stars), Social Science Paper Writing (fakerqwq/social-science-paper-writing-skill, 382 stars) and Literature Review (neflibata-feng/MyArxiv-Agent, 126 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Citation Verification Guide?

Galaxy-Dawn (a GitHub user) maintains it in Galaxy-Dawn/claude-scholar, which has 5,725 GitHub stars. The repository holds 34 skills in this directory. The repository was last updated on September 23, 2026.

Source: Galaxy-Dawn/claude-scholar on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.