What problem does it solve?
It helps you quickly locate relevant academic work and obtain rich, open citation-graph metadata (including affiliations, funding, and open-access status) beyond arXiv or Semantic Scholar coverage.
Core Features & Use Cases
- Open academic graph search: Retrieves comprehensive paper records from OpenAlex, including citation connectivity and detailed metadata.
- Metadata-rich filtering: Narrows results by year ranges, work type (article/preprint/etc.), open-access availability, minimum citation counts, and sort order.
- Use case: You need a grounded set of candidate papers for a literature section that includes institutional affiliations, funding sources, and open-access availability, not just titles and abstracts.
- Cross-reference ready: Returns identifiers like DOI and OpenAlex ID so you can follow up with other skills (e.g., Semantic Scholar context or arXiv details).
Quick Start
Ask for open citation and affiliation-aware search results by saying: /openalex "machine learning for protein design" — max: 10 — sort: citations