inno-reference-audit

Canonical Summary

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 citati...

Trigger Rules

Use this skill when the user request matches its research workflow scope. Prefer the bundled resources instead of recreating templates or reference material. Keep outputs traceable to project files, citations, scripts, or upstream evidence.

Resource Use Rules

• Read from references/ only when the current task needs the extra detail.
• Treat scripts/ as optional helpers. Run them only when their dependencies are available, keep outputs in the project workspace, and explain a manual fallback if execution is blocked.

Execution Contract

• Resolve every relative path from this skill directory first.
• Prefer inspection before mutation when invoking bundled scripts.
• If a required runtime, CLI, credential, or API is unavailable, explain the blocker and continue with the best manual fallback instead of silently skipping the step.
• Do not write generated artifacts back into the skill directory; save them inside the active project workspace.

Upstream Instructions

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.