talent Who actually works on this.
189k researchers and 168k profiles written by a model from public pages — education, career, representative work, open source — with Scholar metrics fetched at request time.
updated 2026-10-14 · search 2 credits · free sample: Federica Sarro
What it answers
Find a person
A name is looked up, not embedded: pinyin works, and Hongjin / Hong Jin / Hong-Jin all match.
Find a kind of person
Organisation, title, area, h-index and years active are filters, not guesses.
Read the evidence
Every claim in a profile keeps the page it was taken from.
Three calls
Straight from the gateway’s own self-description — these are the calls it suggests first.
Look someone up by name
POST /v1/talent/search {"query": "Federica Sarro"} Find people matching criteria
POST /v1/talent/search {"query": "具身智能", "filters": {"org": "清华大学", "role": "教授", "min_h_index": 30}} Read one person
GET /v1/talent/read/7870 Narrow it — org · role · area · location · min_h_index · active_since
What it will not do
Profiles are written from public pages and can be stale; Scholar numbers are rendered live and flagged when they are not fresh.
- People with has_profile=false carry only name/affiliation-level data; level=full (and its sections) returns 404.
- Profile content has a daily quota counted in distinct people read per day (talent:profiles; per-plan numbers are in the self-description's quotas): re-reading the same person is free, card / brief and search are not capped. Over the limit returns 429 quota_exceeded with used_today and resets_at. Contact us for a talent:bulk key for volume or offline use (it lifts the scholar_live quota too).
- Common usage is in quickstart: search to look people up or filter them, read (default level=detail) to read one in a single call; other facets via extra=, a human-readable page via format=html; filters marked advanced are there when you need them.
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