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VepricovVepricov/claude-brainlab/skills/citation-verification/SKILL.md

citation-verification

Skill35 starsChanged 2 months agoMITView on GitHub

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.

11 other projects use a version of this, 1 of them edited.

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We split this skill into the rules it gives an agent

21 rules. 0 are common, 18 are distinctive, and 3 are very specific to this project.

  • 0

    Common

    Most of the 7 edited versions we read keep these.

  • 18

    Distinctive

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

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

    line 36
  2. Distinctive:

    Search for the paper via WebSearch each time a citation is needed

    line 38
  3. Distinctive:

    Add to bibliography only after verification passes

    line 40
  4. Distinctive:

    Check citation count (abnormally low counts may indicate issues)

    line 53
  5. Distinctive:

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

    line 66
  6. Distinctive:

    Use WebSearch to access the paper PDF

    line 68
  7. Distinctive:

    Search for relevant keywords

    line 69
  8. Distinctive:

    Try different queries: - Use different keyword combinations

    line 139
  9. Very specific:

    Mark as pending: - Use [CITATION NEEDED] marker

    line 141
  10. Distinctive:

    Update information: - Use the most accurate version

    line 148
  11. Distinctive:

    Use WebSearch to find: - Verify every citation through WebSearch

    line 156
  12. Distinctive:

    Confirm on Google Scholar: - Verify paper existence on Google Scholar

    line 157
  13. Distinctive:

    Verify promptly: - Verify when adding citations, don't wait until finished

    line 158
  14. Distinctive:

    Don't guess: - If you can't find the paper, don't fabricate information

    line 162
  15. Very specific:

    Mark clearly: - Use [CITATION NEEDED] to mark explicitly

    line 163
  16. Distinctive:

    Confirm venue: - Verify conference/journal name is correct

    line 171
  17. Distinctive:

    Verify claims: - When citing specific claims, confirm they exist in the paper

    line 172
  18. Distinctive:

    Not marking unverifiable citations

    line 180
  19. Distinctive:

    Search every citation with WebSearch

    line 183
  20. Distinctive:

    Verify claims (if needed)

    line 197
  21. Very specific:

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

    line 200

“Common” is measured: kept by at least 6 in 10 of the 7 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
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SKILL.md

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 WebSearch and Google Scholar.

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 WebSearch and Google Scholar:

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. Google Scholar Verification

Why Google Scholar:

  • Most comprehensive academic literature coverage
  • Provides citation count (credibility indicator)
  • Directly provides BibTeX format
  • Free and no API required

Verification steps:

  1. WebSearch query: "site:scholar.google.com [paper title] [first author]"
  2. Confirm the paper appears in results
  3. Check citation count (abnormally low counts may indicate issues)
  4. Click "Cite" to get BibTeX

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
    ↓
WebSearch to find the paper
    ↓
Google Scholar to verify existence
    ↓
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

Handling Verification Failures

If the paper cannot be found on Google Scholar:

  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
  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.

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