| name | check-citations |
| description | Verify academic citations against CrossRef, Semantic Scholar, and OpenAlex. Detects AI-hallucinated references, chimeric citations, and suspicious patterns. |
| version | 1.0.0 |
| metadata | {"openclaw":{"requires":{"bins":["python3"]},"install":[{"kind":"uv","package":"requests"}],"emoji":"🔍","homepage":"https://github.com/PHY041/claude-skill-citation-checker"}} |
check-citations
Verify academic citations against CrossRef, Semantic Scholar, and OpenAlex. Detects AI-hallucinated references, chimeric citations (real title + wrong authors), and suspicious patterns before submission.
When to Use
- After writing or editing a
.bib file with AI assistance
- Before submitting a paper, thesis, or report
- When reviewing AI-generated literature sections
- As a CI/CD check in LaTeX manuscript pipelines
- When auditing existing bibliographies for dead or fabricated references
Background
- 6-55% of AI-generated citations are fabricated (varies by model/domain)
- 100+ hallucinated references found in NeurIPS 2025 accepted papers
- Universities increasingly treat fake citations as academic misconduct
- Three hallucination types: fully fabricated, chimeric (real title + wrong authors), modified real (slightly altered metadata)
Usage
Quick Check (Single File)
python scripts/citation_checker.py references.bib
Check All .bib Files in a Directory
python scripts/citation_checker.py path/to/report/
JSON Output (CI/CD Pipelines)
python scripts/citation_checker.py references.bib --json
Verbose Mode (Debug API Responses)
python scripts/citation_checker.py references.bib --verbose
How It Works
Cascading Multi-Source Verification
Each citation is checked against three independent databases:
| Source | Coverage | Strength |
|---|
| CrossRef | 140M+ DOI-registered works | Best for journal/conference papers with DOIs |
| Semantic Scholar | 200M+ papers | Best author disambiguation, arXiv coverage |
| OpenAlex | 240M+ works | Broadest coverage, fully open |
Verification logic:
- Found in 2+ sources with matching title → verified (high confidence)
- Found in 1 source only → suspicious (manual check recommended)
- Found in 0 sources → not_found (likely hallucinated)
Chimeric Detection
When a citation's title matches a real paper but the authors don't overlap at all, it's flagged as a possible chimeric hallucination — the most dangerous type because the title looks real on Google Scholar.
Red Flag Heuristics
- Invalid DOI format (doesn't start with
10.xxxx/)
- Suspiciously generic title patterns ("A Comprehensive Survey of...")
- Future publication year
- Missing author or year fields
- Single-word author names (incomplete metadata)
Exit Codes
| Code | Meaning |
|---|
| 0 | All citations verified |
| 1 | One or more citations not found |
| 2 | Suspicious citations only (no hard failures) |
Dependencies
pip install requests
No API keys required — uses free tiers of all three databases.
Accuracy (Tested)
| Category | Result | Description |
|---|
| Known-good | 9/10 (90%) | Famous ML papers (Vaswani, Devlin, Brown, He, etc.) |
| Known-bad | 10/10 (100%) | Fabricated papers with plausible titles |
| Chimeric | 5/5 (100%) | Real titles with wrong authors |
| False positive rate | 10% | 1 miss: unpublished tech report without DOI |
| False negative rate | 0% | No fake paper was ever verified |
The core guarantee: fake papers are never marked as real.
Limitations
- Papers without DOI that have many derivatives (e.g., BERT without DOI) may not be found via title search alone — always include DOIs when available
- Semantic Scholar free tier rate-limits at ~100 requests/5 minutes — batch verification is slower
- Cannot verify papers behind paywalls or not indexed in any of the three databases
- Book chapters, technical reports, and grey literature have lower coverage
Integration with LaTeX Workflows
Pre-commit Hook
#!/bin/bash
python scripts/citation_checker.py references.bib --json > /tmp/cite_check.json
NOT_FOUND=$(python3 -c "import json; d=json.load(open('/tmp/cite_check.json')); print(d['summary']['not_found'])")
if [ "$NOT_FOUND" -gt "0" ]; then
echo "BLOCKED: $NOT_FOUND unfound citations. Run 'python scripts/citation_checker.py references.bib --verbose' to investigate."
exit 1
fi
GitHub Actions
- name: Check citations
run: |
pip install requests
python scripts/citation_checker.py references.bib --json > citation_report.json
python -c "
import json, sys
r = json.load(open('citation_report.json'))
if r['summary']['not_found'] > 0:
print(f'FAIL: {r[\"summary\"][\"not_found\"]} citations not found')
sys.exit(1)
print(f'PASS: {r[\"summary\"][\"verified\"]} verified, {r[\"summary\"][\"suspicious\"]} suspicious')
"
