scholarly_search
ActiveTool of ai.dynamicfeed/dynamic-feed
Fact-check the published scholarly record via OpenAlex — METADATA ONLY, NO prices. `query` = free text/topic ("CRISPR gene editing") OR a DOI / doi.org URL for an exact-work lookup. `sort` = "relevance" (default) | "citations" | "newest" | "oldest". `limit` = max works (default 10, cap 25). Each work returns its citation count, open-access status + URL, publication venue + type, year/date, work type, lead authors (up to 5) + total author count + lead institution, references count, retraction flag, and the work's own OpenAlex record-update time. Spans 240M+ works across every publisher (journals, conferences, books, datasets, preprints), so it answers "does this paper exist / how cited is it / is it open access / where was it published / who wrote it" — which a training snapshot gets stale or hallucinates. DISTINCT from research_papers (arXiv preprints only, newest-first abstracts): different source (OpenAlex), cross-publisher, citation/OA/venue metadata — no abstracts, no full text. Source: OpenAlex (api.openalex.org, OurResearch), data is CC0 1.0 public domain; keyless (polite pool), ~6 h cache. HARD CONSTRAINT: every value is bibliometric metadata (a citation count, year, OA status, venue, author) — NEVER a market price, quote, or valuation. Every value is returned in an Ed25519-signed, provenance-stamped envelope (source and observation time) you can verify offline against /.well-known/keys, no account required.
Parameters schema
{
"type": "object",
"title": "scholarly_searchArguments",
"properties": {
"sort": {
"type": "string",
"title": "Sort",
"default": "relevance"
},
"limit": {
"type": "integer",
"title": "Limit",
"default": 10
},
"query": {
"type": "string",
"title": "Query",
"default": "large language models"
}
}
}Parent server
ai.dynamicfeed/dynamic-feed
1/7 registries