{"openapi":"3.1.0","info":{"title":"reef public API","version":"1.0.0","description":"A read-only window onto **reef's biotech entity graph** — resolved companies, researchers,\npapers, patents, trials, and funding, each carrying its provenance.\n\n**Base URL** `https://api.reef.bio/v1` · all endpoints are `GET`, return JSON, and need **no\nauth** in this preview tier (anonymous, rate-limited per IP).\n\n### Query patterns\n* **Type-ahead** — `GET /autocomplete?q=&kind=` returns lean `{id,name,kind,slug}` suggestions;\n  the entry point for resolving a name to an entity.\n* **Search / browse** — `GET /entities?q=&kind=&limit=&offset=&sort=`. With `q`, results are\n  relevance-ranked; without it you browse the whole graph. `sort` ∈ `recent` (default), `name`,\n  `prominence` (most-connected first), `momentum` (heating-up first). For deep, stable paging\n  pass the previous page's `next_cursor` back as `after` (**keyset pagination** — never skips or\n  repeats as the graph grows); `total` is returned on the first page only.\n* **Signals** — every record carries a `signals` block: `prominence` (0–100 per-kind\n  connectivity percentile), `momentum` (−10…+10 recent-vs-prior activity), `rank_in_kind`,\n  `degree`; `null` for entities with no edges. Honest-now/uncalibrated, recomputed daily.\n* **Probability of success** — `trial` records carry a `pos` block: a phase-conditioned\n  likelihood-of-approval (`probability`, `phase`, `basis`) — an uncalibrated industry base-rate\n  prior with an explicit caveat, `null` where there's no usable phase.\n* **Filter by mechanism** — `GET /entities?target=&modality=&mechanism=&therapeutic_area=`\n  filters the graph *by biology* (combinable with `q`/`kind`). Valid values come from `/facets`.\n* **Canonical ids** — every record's `moa` block carries `target_id` (Open Targets Ensembl) +\n  `target_symbol` (HGNC) and `disease_id` (EFO/MONDO) + `disease_label`. Filter on the stable id\n  with `?target_id=` / `?disease_id=` (exact join keys, interoperable with the bio-ontology\n  ecosystem) and group by them via `/aggregate?field=target_id`.\n* **Products** — `kind=product` is the engineered/offered thing a company makes or sells (spans\n  all of synbio, not just drugs). Each carries a `product` block (`family`, open `categories`\n  tags, cross-company `uid`). Filter with `?family=` (therapeutic / platform_service /\n  physical_product / data_software) and group via `/aggregate?field=product_family`.\n* **Pick fields** — add `?fields=id,name,moa,…` to any `/entities` query to return only the\n  top-level keys you want.\n* **Aggregate** — `GET /aggregate?field=&kind=&target=…` returns group-by-field counts\n  (`kind`, `target`, `modality`, `mechanism`, `therapeutic_area`, `platform_type`, `source`) —\n  e.g. companies per platform, patents per target within a modality.\n* **Incremental sync** — `GET /changes?since=<ISO8601>` then page forward with `after=<cursor>`.\n  Each row's `op` is `upsert` or `merged` (a folded duplicate — treat as a delete/redirect),\n  so a downstream copy stays consistent including deletions.\n* **One entity** — `GET /entities/{id}` (full record + per-field provenance; supports `ETag` /\n  `If-None-Match` → `304`; a merged duplicate `301`s to the survivor). Stable links:\n  `GET /entities/by-slug/{kind}/{slug}`.\n* **Walk the graph** — `GET /entities/{id}/edges` (one hop; also grouped into `by_relation`\n  cards) and `/traverse?depth=&relations=`.\n* **Discover** — `GET /schema` is the data dictionary (kinds, fields, mechanism facets,\n  aggregate fields, relation types); `GET /facets?kind=` lists valid MoA filter values\n  (target/modality/mechanism/therapeutic_area); `GET /stats` is coverage.\n* **Intelligence** — analytics over the graph: `GET /whitespace` (target×modality crowding\n  map), `GET /concentration?target=…` (IP held by which assignees/inventors),\n  `GET /people/rank?target=…` (researchers by recent output), `GET /funding/analytics`\n  (capital-flow trends), and per-company `GET /entities/{id}/dossier` (science diligence),\n  `…/comparables` (mechanism peers), `…/collaborators` (a researcher's co-authorship network).\n  `GET /calendar?from=&to=&type=` is the catalyst calendar — dated milestones (trial data\n  read-outs today; approvals/PDUFA to follow), each linking to its subject.\n  Outputs are confidence-gated and carry honesty caveats; they're triage, not legal/valuation.\n\nErrors use `{\"error\":{\"code\",\"message\"}}`. Every response carries `X-RateLimit-*`; GETs send\n`Cache-Control` + `ETag`. Coverage is partial and growing — check each record's `source`.\nA full how-to guide lives at https://api.reef.bio/docs.\n","contact":{"name":"reef","url":"https://reef.bio"}},"servers":[{"url":"https://api.reef.bio","description":"production"}],"tags":[{"name":"Entities","description":"Search, browse, and fetch entities (the core records)."},{"name":"Graph","description":"Walk relationships: one-hop edges and bounded multi-hop traversal."},{"name":"Discovery","description":"Coverage and the valid mechanism-of-action filter values."}],"paths":{"/v1/stats":{"get":{"tags":["Discovery"],"summary":"Coverage by kind","description":"Live per-kind entity counts — the explorer's honest coverage header.","operationId":"stats_v1_stats_get","responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}}}}},"/v1/facets":{"get":{"tags":["Discovery"],"summary":"Valid MoA filter values","description":"Available MoA facet values + counts (trusted enrichment only) — so callers pick\nvalid target/modality/area filters before querying.\n\n`kind` is required (a 400, not a 500): without it, facet_counts() runs 4 unbounded\nGROUP BYs across the whole entity table instead of one kind's slice, which sat right at\nthe DB statement-timeout boundary and intermittently 500'd with a bare, undocumented\nerror (#712) — the same class of problem /v1/schema's `relations` field already hit once\nfor a similar unfiltered aggregate (see that field's comment). No cross-kind facet\nlisting is a documented use case, so removing the unbounded path outright is safer than\ntrying to make it reliably fast.","operationId":"facets_v1_facets_get","parameters":[{"name":"kind","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Kind"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/v1/schema":{"get":{"tags":["Discovery"],"summary":"Data dictionary","description":"Self-describing data dictionary: entity `kinds` + counts, the selectable\n`entity_fields` (for `?fields=`), the `moa_facets` you can filter `/entities` by\n(values via `/facets`), and the `relations` that edges use. One call to learn what's\nqueryable.","operationId":"schema_v1_schema_get","responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}}}}},"/v1/aggregate":{"get":{"tags":["Discovery"],"summary":"Group-by counts over the graph","description":"Count entities grouped by one `field` (see `aggregate_fields` in `/schema`), optionally\nnarrowed by `kind` and the MoA filters. Answers \"how many companies per platform_type\",\n\"patents per target within modality=antibody\", etc. MoA/platform groupings are\nconfidence-gated (trusted enrichment only). Returns `{field, filters, buckets:[{value,count}]}`.","operationId":"aggregate_v1_aggregate_get","parameters":[{"name":"field","in":"query","required":true,"schema":{"type":"string","title":"Field"}},{"name":"kind","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Kind"}},{"name":"target","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Target"}},{"name":"modality","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Modality"}},{"name":"mechanism","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Mechanism"}},{"name":"therapeutic_area","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Therapeutic Area"}},{"name":"limit","in":"query","required":false,"schema":{"type":"integer","default":50,"title":"Limit"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/v1/changes":{"get":{"tags":["Discovery"],"summary":"Change feed (incremental sync)","description":"Entities changed at/after a watermark, oldest-first — the downstream-sync feed. Pass\n`since=<ISO 8601>` for the first call, then echo back `next_cursor` as `after` to walk\nforward without gaps or repeats. Each row carries `op`: `upsert` (created/updated) or\n`merged` (a duplicate folded into `merged_into` — treat as a delete/redirect of `id`).\nThis is how a consumer keeps a local copy consistent, including deletions. One of `since`\nor `after` is required. Returns `{since, count, next_cursor, changes}`.","operationId":"changes_v1_changes_get","parameters":[{"name":"since","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Since"}},{"name":"after","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"After"}},{"name":"limit","in":"query","required":false,"schema":{"type":"integer","default":100,"title":"Limit"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/v1/autocomplete":{"get":{"tags":["Discovery"],"summary":"Type-ahead entity suggestions","description":"Fast type-ahead: lean `{id, name, kind, slug}` suggestions for a partial query,\noptionally scoped to a `kind`. The entry point for resolving a name to an entity before\na lookup/search. Empty `q` returns no suggestions.","operationId":"autocomplete_v1_autocomplete_get","parameters":[{"name":"q","in":"query","required":false,"schema":{"type":"string","default":"","title":"Q"}},{"name":"kind","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Kind"}},{"name":"limit","in":"query","required":false,"schema":{"type":"integer","default":10,"title":"Limit"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/v1/entities":{"get":{"tags":["Entities"],"summary":"Search, filter, or browse entities","description":"Search / filter / browse the graph.\n\n- **Mechanism filters** (`target`, `modality`, `mechanism`, `therapeutic_area`) and\n  **canonical-id filters** (`target_id` = Open Targets Ensembl, `disease_id` = EFO/MONDO):\n  filter the graph by biology (index-backed, trusted enrichment only). The id filters are\n  exact, stable join keys (see each record's `moa.target_id` / `moa.disease_id`). Combinable\n  with `q` and `kind`; the relevance window is capped, `offset` pages within it.\n- **Product filter** (`family`): restrict to a product family (`therapeutic`,\n  `platform_service`, `physical_product`, `data_software`). Each `product` record carries a\n  `product` block (`family`, open `categories` tags, cross-company `uid`).\n- **Technology filter** (`technology`): restrict to entities with an `employs` edge to a\n  matching `technology` entity (e.g. `technology=CRISPR-Cas9`) — a many-to-many method/\n  platform axis, distinct from `modality` (a drug's therapeutic form). See `/entities/{id}/\n  edges` on a `technology`-kind entity to see everything linked to it directly.\n- **Query** `q` (no MoA filter): relevance-ranked (FTS + optional vector), capped window.\n  `sort` is ignored (relevance wins).\n- **Browse** (no `q`, no MoA filter): full-graph pagination. Prefer **keyset** — pass the\n  `next_cursor` from the previous page as `after` for stable, unbounded paging that never\n  skips or repeats as the graph grows. `offset` still works for shallow paging.\n  `sort` is `recent` (updated_at desc, default), `name`, `prominence` (most-connected\n  first), or `momentum` (heating-up first). The `prominence`/`momentum` sorts return only\n  entities that have a computed signal (i.e. have live edges). `total` is returned on the\n  first page only (omitted while paging with `after`, to keep deep paging cheap).\n- `fields`: comma-separated top-level keys to return (e.g. `id,name,moa`); default = all.\nReturns `{query, kind, filters, count, total, offset, limit, next_offset, next_cursor, results}`.","operationId":"search_v1_entities_get","parameters":[{"name":"q","in":"query","required":false,"schema":{"type":"string","default":"","title":"Q"}},{"name":"kind","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Kind"}},{"name":"target","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Target"}},{"name":"modality","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Modality"}},{"name":"mechanism","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Mechanism"}},{"name":"therapeutic_area","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Therapeutic Area"}},{"name":"target_id","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Target Id"}},{"name":"disease_id","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Disease Id"}},{"name":"family","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Family"}},{"name":"technology","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Technology"}},{"name":"fields","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Fields"}},{"name":"limit","in":"query","required":false,"schema":{"type":"integer","default":25,"title":"Limit"}},{"name":"offset","in":"query","required":false,"schema":{"type":"integer","default":0,"title":"Offset"}},{"name":"after","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"After"}},{"name":"sort","in":"query","required":false,"schema":{"type":"string","default":"recent","title":"Sort"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/v1/search":{"post":{"tags":["Entities"],"summary":"Predicate search (AND-list of field filters)","description":"Structured search: an AND-list of `{field, operator, value}` predicates over indexed columns\n(the allowlist in the field description). Keyset-paginated (`after` → `next_cursor`), `sort` ∈\nrecent|name|prominence|momentum. The richer, programmatic complement to GET /entities.","operationId":"predicate_search_v1_search_post","requestBody":{"content":{"application/json":{"schema":{"$ref":"#/components/schemas/_SearchBody"}}},"required":true},"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/v1/export":{"get":{"tags":["Entities"],"summary":"Bulk export a filtered slice (NDJSON/CSV stream)","description":"Stream a filtered slice of the graph as NDJSON (default) or CSV for warehouse/bulk consumers.\nKeyset-streamed in chunks (each chunk stays under the statement timeout); capped at `max` rows.\nLean columns only (id, kind, name, slug, target, modality, product_family, updated_at).","operationId":"export_v1_export_get","parameters":[{"name":"kind","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Kind"}},{"name":"family","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Family"}},{"name":"format","in":"query","required":false,"schema":{"type":"string","pattern":"^(ndjson|csv)$","default":"ndjson","title":"Format"}},{"name":"max","in":"query","required":false,"schema":{"type":"integer","maximum":50000,"minimum":1,"default":50000,"title":"Max"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/v1/entities/by-slug/{kind}/{slug}":{"get":{"tags":["Entities"],"summary":"Get one entity by stable slug","description":"Resolve a stable human URL (kind + slug) to an entity — for shareable explorer\nlinks. Picks the active (non-merged) row; newest wins on the rare slug collision.","operationId":"get_entity_by_slug_v1_entities_by_slug__kind___slug__get","parameters":[{"name":"kind","in":"path","required":true,"schema":{"type":"string","title":"Kind"}},{"name":"slug","in":"path","required":true,"schema":{"type":"string","title":"Slug"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/v1/entities/{entity_id}":{"get":{"tags":["Entities"],"summary":"Get one entity (with provenance)","description":"One entity with full provenance. A merged duplicate 301s to the surviving winner\nso a tombstone never serves as live data. Supports ETag / If-None-Match (304).","operationId":"get_entity_v1_entities__entity_id__get","parameters":[{"name":"entity_id","in":"path","required":true,"schema":{"type":"string","title":"Entity Id"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/v1/entities/{entity_id}/edges":{"get":{"tags":["Graph"],"summary":"One-hop relationships","description":"One-hop relationships (both directions), live edges only.\n\nReturns the flat `edges` list plus `by_relation` — the same edges grouped into typed\n\"related cards\" (`{relation: {count, edges}}`) — and `relation_counts`, the data shape\nthe explorer's neighbor view uses.","operationId":"edges_v1_entities__entity_id__edges_get","parameters":[{"name":"entity_id","in":"path","required":true,"schema":{"type":"string","title":"Entity Id"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/v1/entities/{entity_id}/similar":{"get":{"tags":["Graph"],"summary":"Look-alike entities (semantic + lexical)","description":"Entities most similar to this one — a dense embedding (cosine) leg fused with a lexical\nname leg by RRF. `kind` narrows to a type (e.g. similar companies). Falls back to lexical\nwhen embeddings aren't available. Similarity is a discovery signal, not an assertion of\nequivalence.","operationId":"similar_v1_entities__entity_id__similar_get","parameters":[{"name":"entity_id","in":"path","required":true,"schema":{"type":"string","title":"Entity Id"}},{"name":"kind","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Kind"}},{"name":"limit","in":"query","required":false,"schema":{"type":"integer","default":10,"title":"Limit"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/v1/entities/{entity_id}/traverse":{"get":{"tags":["Graph"],"summary":"Multi-hop graph walk","description":"Bounded multi-hop walk from an entity (depth/fan-out/visited capped). `relations`\nis an optional comma-separated allowlist of edge relations to follow.","operationId":"traverse_v1_entities__entity_id__traverse_get","parameters":[{"name":"entity_id","in":"path","required":true,"schema":{"type":"string","title":"Entity Id"}},{"name":"depth","in":"query","required":false,"schema":{"type":"integer","default":2,"title":"Depth"}},{"name":"relations","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Relations"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/v1/whitespace":{"get":{"tags":["Intelligence"],"summary":"Target × modality crowding map","description":"The crowding/whitespace matrix: for each target×modality cell, trusted entity counts by\nkind (paper/patent/trial/company/approval) plus a per-cell `coverage` (trusted / all-tagged).\nDense cells are crowded; gaps across active rows+cols are whitespace. Confidence-gated.","operationId":"whitespace_v1_whitespace_get","parameters":[{"name":"therapeutic_area","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Therapeutic Area"}},{"name":"limit_targets","in":"query","required":false,"schema":{"type":"integer","default":20,"title":"Limit Targets"}},{"name":"limit_modalities","in":"query","required":false,"schema":{"type":"integer","default":12,"title":"Limit Modalities"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/v1/concentration":{"get":{"tags":["Intelligence"],"summary":"IP concentration by assignee / inventor","description":"Who holds the patents in a mechanism cell: top assignee companies + top inventors by\ndistinct patent count. Needs at least one of target/modality/therapeutic_area. Triage, not\na freedom-to-operate or legal opinion.","operationId":"concentration_v1_concentration_get","parameters":[{"name":"target","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Target"}},{"name":"modality","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Modality"}},{"name":"therapeutic_area","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Therapeutic Area"}},{"name":"limit","in":"query","required":false,"schema":{"type":"integer","default":15,"title":"Limit"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/v1/patents/landscape":{"get":{"tags":["Intelligence"],"summary":"Patent landscape / FTO-triage for a mechanism cell","description":"The composite patent landscape for a mechanism cell: assignee + inventor IP concentration\nand recency-decayed inventor KOLs in one call. **Requires** at least one of\ntarget/modality/therapeutic_area (an unfiltered graph-wide scan would exceed the public read\nbudget). Reads the RAW GLOBAL graph (no tenant overlay). Triage, not a freedom-to-operate or\nlegal opinion. Assignee/inventor rows are lean entity refs — resolve each via its `_links.self`\nfor the full record. For the target×modality crowding map, call `/v1/whitespace`.","operationId":"patents_landscape_v1_patents_landscape_get","parameters":[{"name":"target","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Target"}},{"name":"modality","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Modality"}},{"name":"therapeutic_area","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Therapeutic Area"}},{"name":"limit","in":"query","required":false,"schema":{"type":"integer","default":15,"title":"Limit"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/v1/funding/analytics":{"get":{"tags":["Intelligence"],"summary":"Capital-flow analytics","description":"Funding activity over a trailing window: totals, by-month, by-type, and top recipients.\nDeal count is the complete signal; summed $ covers grant awards only (SEC Form D reports no\namount).","operationId":"funding_analytics_v1_funding_analytics_get","parameters":[{"name":"months","in":"query","required":false,"schema":{"type":"integer","default":12,"title":"Months"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/v1/people/rank":{"get":{"tags":["Intelligence"],"summary":"Rank researchers (KOLs) by recent output","description":"Researchers ranked by recency-decayed output (authored papers + invented patents),\noptionally scoped to a mechanism. Each carries a rising-star signal (recent vs older).","operationId":"people_rank_v1_people_rank_get","parameters":[{"name":"target","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Target"}},{"name":"modality","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Modality"}},{"name":"therapeutic_area","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Therapeutic Area"}},{"name":"limit","in":"query","required":false,"schema":{"type":"integer","default":20,"title":"Limit"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/v1/people/experts":{"get":{"tags":["Intelligence"],"summary":"Expert finder — top KOLs + their institutions for a cell","description":"The top researchers for a mechanism cell (recency-decayed output) WITH their institutions\nand a transparent tier, plus the institutions that recur most among them. **Requires** at\nleast one of target/modality/therapeutic_area. 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