citation-assistant

name	citation-assistant
user-invocable	true
description	Add verified citations to academic papers and proposals. Use when working on LaTeX documents that need citations, finding papers for a specific section, verifying existing citations, or when user mentions "cite", "citation", "references", "bibliography", or asks to find related work. Supports Semantic Scholar API, Exa MCP, and DOI-based BibTeX retrieval. Never hallucinate citations. Invoke with "citation-assistant" or "citation-assistant [section]".

Citation Assistant

Add verified citations to academic LaTeX documents. Identify citation gaps, search for relevant papers, verify their existence, and add properly formatted BibTeX entries.

CRITICAL: No Hallucinated Citations

All citations MUST be real, verified papers. Hallucinated or fabricated citations are absolutely not tolerated - they constitute academic misconduct and can result in paper rejection or retraction.

• NEVER generate BibTeX from memory
• ALWAYS verify papers exist via API or web search before citing
• If you cannot verify a paper, mark it as [CITATION NEEDED] - do NOT guess
• When in doubt, leave it out

Context

• Bibliography files: !'find . -maxdepth 3 -name "*.bib" 2>/dev/null | head -20 || echo "No .bib files found"'
• LaTeX sections: !'grep -rh "\\section{" *.tex 2>/dev/null | head -20 || echo "No .tex files found"'

Invocation

citation-assistant                     # Ask user which section needs citations
citation-assistant [section]           # Add citations to specified section (e.g., "introduction", "related work")
citation-assistant verify              # Verify all existing citations in the document

Workflow

1. Identify Target Section

When invoked:

• If section argument provided: Read that section from the LaTeX file
• If no argument: Use AskUserQuestion to ask "Which section needs citations?"
  • Offer sections found in the document (scan for \section{...})

2. Identify Citation Gaps

Read the section and identify:

• Claims without citations
• Broad claims with insufficient citations (single citation for major claims)
• Methods/techniques missing original paper references
• Comparisons to prior work without references

List gaps to user before searching - Show each claim and why it needs a citation.

3. Search for Papers

For each gap, use multiple search methods to ensure broad coverage:

1. Check existing bibliography first - Search the project's .bib file(s)

2. Search using ALL available tools (not just one):

   • Exa MCP (if available) - semantic search, good for conceptual queries
   • Semantic Scholar API - comprehensive academic database
   • Web search - catches recent preprints and non-indexed papers

   Run searches in parallel when possible. Different tools have different coverage - a paper missing from one source may appear in another.

3. Aggregate and deduplicate results - Merge results from all sources

4. Verify each paper exists in 2+ sources before citing

5. Fetch BibTeX via DOI - Never generate from memory

4. Add Citations

• Append new entries to .bib file
• Insert citation commands matching the document's style (\cite{}, \citep{}, \citet{}, etc.)
• Report what was added

Citation Rules

Situation	Action
Found paper, got DOI	Fetch BibTeX via DOI, add citation
Found paper, no DOI	Use arXiv BibTeX or construct from verified metadata
Cannot verify paper	Mark as [CITATION NEEDED], inform user
"I think there's a paper about X"	Search first, never guess

Never hallucinate citations. If verification fails at any step, mark the citation as needing manual verification.

BibTeX Format

@article{author2024keyword,
  title={Title with {Acronyms} Protected},
  author={Last, First and Last2, First2},
  journal={arXiv preprint arXiv:XXXX.XXXXX},
  year={2024}
}

@inproceedings{author2024conf,
  title={Title Here},
  author={Last, First},
  booktitle={Proceedings of NeurIPS},
  year={2024}
}

• Key format: author_year_keyword
• Protect acronyms with braces: {LLM}, {GPU}, {BERT}
• Use and between authors

Python Environment

When running Python code for citation lookups:

1. Create a virtual environment if needed: uv venv
2. Activate it: source .venv/bin/activate
3. Install dependencies: uv add semanticscholar requests

Never use the system Python directly.

APIs

See references/apis.md for Semantic Scholar and DOI lookup code.

Output

For each citation added, report:

1. The claim being supported
2. Paper title and authors
3. Why this paper is relevant
4. The BibTeX key added