citation-management

To extract metadata and generate BibTeX, supply a DOI or PMID to fetch authors, titles, and journals from PubMed and CrossRef. The skill outputs clean, properly formatted BibTeX entries with correct capitalization and page numbers.

Yes, you can automate literature review bibliography maintenance across Google Scholar and arXiv. Multi-database search scripts discover citations, extract metadata, detect duplicates, and build reproducible bibliographies spanning multiple sources.

The best way to validate DOIs and format citations for manuscript preparation is using automated verification scripts. These check DOI validity, handle formatting errors, and produce clean BibTeX entries ready for integration into manuscript drafts.

BibTeX formatting fails when pulling metadata from multiple scholarly databases due to inconsistent capitalization, missing page numbers, or invalid DOIs. Automated extraction with error handling validates entries and standardizes formatting across Google Scholar, PubMed, CrossRef, and arXiv.

Yes, you need specific Python dependencies to run scholarly metadata extraction scripts. The required packages include requests for API calls, scholarly for Google Scholar queries, and python-dotenv for environment configuration.

Yes, this citation management approach works for end-to-end literature workflows. It supports the complete process from multi-database search and metadata extraction to DOI validation, BibTeX generation, and bibliography maintenance for literature reviews.