> ## Documentation Index
> Fetch the complete documentation index at: https://docs.forestreet.com/llms.txt
> Use this file to discover all available pages before exploring further.
# List event groups
>
Retrieves groups of events that refer to the same real-world occurrence, for every group
updated in the last 24 hours. Each item in `data` is one group, given as the list of its
events. The events have the same shape as the ones returned by List events.
**Subscription Endpoint**
This endpoint has a special subscription requirement. Your API Key needs to be
subscribed to this endpoint in order to access it; otherwise it will return a 403
Forbidden error. Please contact Forestreet support to get subscribed.
Events built from proprietary data are kept separate from events built from public data,
so the same occurrence can appear as several events. An event group links them together.
Each event's `providers` field shows which data providers it was built from. A group may
hold a single event when no other event was found to match it.
Groups are sorted by when they were last updated, most recent first, and the events within
a group by when they were created, oldest first. Unlike List events, the events in a group
are not filtered by impact scores.
## OpenAPI
````yaml get /v2/events-monitor/event-groups
openapi: 3.0.0
info:
title: Forestreet API
version: 1.0.0
description: API documentation for Forestreet API
servers:
- url: http://localhost:4000
description: Local server
- url: https://rest-dev.forestreet.com
description: Development server
security:
- apiKeyAuth: []
- bearerAuth: []
- sessionIdQuery: []
tags: []
paths:
/v2/events-monitor/event-groups:
get:
tags:
- Events Monitor
summary: List event groups
description: |2-
Retrieves groups of events that refer to the same real-world occurrence, for every group
updated in the last 24 hours. Each item in `data` is one group, given as the list of its
events. The events have the same shape as the ones returned by List events.
**Subscription Endpoint**
This endpoint has a special subscription requirement. Your API Key needs to be
subscribed to this endpoint in order to access it; otherwise it will return a 403
Forbidden error. Please contact Forestreet support to get subscribed.
Events built from proprietary data are kept separate from events built from public data,
so the same occurrence can appear as several events. An event group links them together.
Each event's `providers` field shows which data providers it was built from. A group may
hold a single event when no other event was found to match it.
Groups are sorted by when they were last updated, most recent first, and the events within
a group by when they were created, oldest first. Unlike List events, the events in a group
are not filtered by impact scores.
parameters:
- schema:
type: integer
minimum: 1
maximum: 25
default: 10
description: >-
Number of items per page, default is 10, minimum is 1, maximum is
25.
required: false
description: >-
Number of items per page, default is 10, minimum is 1, maximum is
25.
name: pageSize
in: query
- schema:
type: integer
minimum: 1
default: 1
description: Current page number, default is 1.
required: false
description: Current page number, default is 1.
name: page
in: query
responses:
'200':
description: >-
The response containing pagination metadata, and an array of zero or
more event groups, each an array of events.
content:
application/json:
schema:
type: object
properties:
meta:
type: object
properties:
totalItems:
type: number
description: >-
Total number of items for the returned dataset after
filtering.
totalPages:
type: number
description: >-
Total number of pages for the returned dataset after
filtering.
currentPage:
type: number
description: Current page number.
pageSize:
type: number
description: Number of items per page.
unfilteredTotalItems:
type: number
description: >-
Total number of items for the original dataset before
filtering.
unfilteredTotalPages:
type: number
description: >-
Total number of pages for the original dataset before
filtering.
required:
- totalItems
- totalPages
- currentPage
- pageSize
description: >-
Schema for pagination metadata, including total items,
total pages, current page, and page size.
example:
totalItems: 123
totalPages: 13
currentPage: 1
pageSize: 10
unfilteredTotalItems: 196
unfilteredTotalPages: 20
data:
type: array
items:
type: array
items:
type: object
properties:
_id:
type: string
description: Unique identifier for the event
example: 69e5bfcd21aab5bcbb62eae4
title:
type: string
description: >-
Title of the event.
This is generated by LLM based on any available
contents of the referenced Observations, such as
their titles and summaries. It is meant to be a
concise and human-readable summary of the event,
as though it is written by a journalist having
been given the same Observation data.
example: >-
China Sees Greater Integration Between Trade and
Investment, Creating New Opportunities
summary:
type: string
description: >
Summary of the event.
This is generated by LLM based on any available
contents of the referenced Observations, such as
their titles and summaries. It is to be an
executive summary of the event, capturing the key
details and significance of the event in a few
sentences for a C-suite audience.
This field is meant for user consumption, and may
not be comprehensive enough for NLP processing.
The following fields are designed for NLP
processing:
- `vectorIndex.anchorText`
- `eventSearchKeywords`
example: >-
China's foreign trade sector is increasingly
integrating trade and investment functions, a
trend noted by state broadcaster coverage
highlighting evolving policy and market
structures. This integration can foster deeper
value-chain links, encourage inward and outbound
investment tied to trade flows, and create
procurement opportunities for multinational firms
seeking integrated supply-and-investment
strategies. For trading companies and investors,
integrated approaches can streamline cross-border
operations, facilitate production localization and
affect supplier selection and partnership models.
The narrative indicates potential opportunities
for firms to leverage investment to secure market
access, though the story does not provide
quantitative data or named project examples.
vectorIndex:
type: object
properties:
anchorText:
type: string
nullable: true
description: >-
An "anchor text" is a snippet of text that is
used as a reference point for the vector
index. It serves as a concise representation
of the content of the event, stripped of any
named entities or non-embeddable content,
reducing an event to a simple vector that
captures the core essence of what happened.
This allows for efficient similarity searches for similar events regardless of the specific entities involved, enabling users to find events that are similar in nature even if they involve different companies, people, or other entities.
example: >-
a government narrative promoting closer
alignment of trade and investment to spur
commercial opportunities
embeddings:
type: array
nullable: true
items:
type: number
description: >-
An array of numbers representing the vector
embeddings of the event's content.
embeddingsModelName:
type: string
nullable: true
description: >-
The name of the model used to generate the
embeddings.
required:
- anchorText
eventSearchKeywords:
type: array
items:
type: object
properties:
keyword:
type: string
nullable: true
propertySource:
type: string
nullable: true
enum:
- inferred
- explicit
- null
description: >-
Whether the property was inferred by LLM or
explicitly extracted from its content.
Currently only `inferred` is supported, but
we may add `explicit` in the future for
properties that are directly extracted from
text rather than inferred through LLM
reasoning.
required:
- keyword
- propertySource
description: >-
A list of keywords that are likely to be relevant
for searching for contextual information regarding
this event. They are also useful in finding more
reportings of the same event. These are extracted
from the event's content and can be used as search
terms to find additional information about the
event, such as news articles, reports, or other
relevant documents. They can be used for further
context buiding as well as event grouping.
example:
- keyword: China foreign trade
propertySource: inferred
- keyword: investment
propertySource: inferred
- keyword: trade-investment integration
propertySource: inferred
- keyword: supply chain
propertySource: inferred
- keyword: market access
propertySource: inferred
relevantEntities:
type: array
items:
type: object
properties:
name:
type: string
nullable: true
entityType:
type: string
nullable: true
enum:
- company
- category
- country
- location
- hierarchical_category
- supplier
- null
description: The type of the relevant entity.
propertySource:
type: string
nullable: true
enum:
- inferred
- explicit
- null
description: >-
Whether the property was inferred by LLM or
explicitly extracted from its content.
Currently only `inferred` is supported, but
we may add `explicit` in the future for
properties that are directly extracted from
text rather than inferred through LLM
reasoning.
required:
- name
- entityType
- propertySource
description: >-
A list of entities relevant to the event. Each
entity includes its name, type, and the source of
the property.
These are inferred from the article contents as
free text, and is not guaranteed to match the
Beroe Data Hub taxonomy.
For taxonomic matching to Beroe Data Hub entities,
please refer to the `taxonomicMatches` field,
which providesdetailed information on how the
event's contents map to specific entities in
ourtaxonomy, along with the rationale and
confidence level of each match.
example:
- name: Trade and Investment Integration
entityType: category
propertySource: inferred
- name: Supply Chain Localization
entityType: category
propertySource: inferred
- name: China
entityType: country
propertySource: inferred
timestamps:
type: object
properties:
published:
type: string
nullable: true
format: date-time
recordedStart:
type: string
nullable: true
format: date-time
recordedEnd:
type: string
nullable: true
format: date-time
projectedStart:
type: string
nullable: true
format: date-time
projectedEnd:
type: string
nullable: true
format: date-time
description: >-
Timestamps relevant to the event. The key
indicates the type of the timestamp.
All values must be in UTC and in ISO 8601 format.
Not all events will have all types of timestamps;
the presence of each timestamp depends on the
available information for that event.
example:
published: '2026-04-20T05:38:41.505Z'
recordedStart: '2026-04-19T14:03:00.073Z'
references:
type: array
items:
type: object
properties:
_id:
type: string
description: Unique identifier for the observation
example: 69e5b8d17a3ce8b7e8505aa5
title:
type: string
description: >-
Title of the observation.
For news articles, this will typically be
the native title of the article from the
publisher.
example: >-
China’s foreign trade, investment
integration generates greater opportunities
url:
type: string
description: >-
URL of the observation, if it was sourced
and scraped from the internet.
example: >-
https://www.globaltimes.cn/page/202604/1359275.shtml
required:
- _id
- title
description: >-
A list of observations that are referenced by the
event. Each observation includes its title and URL
(if available). These are the specific pieces of
content that the LLM used as source material to
generate the event's title and summary.
providers:
type: array
items:
type: string
default: []
description: >-
The data providers the event was built from, such
as `public_news_search`.
Public and proprietary data are never mixed within
one event: an event is built either from public
providers only, or from a single proprietary
provider. Events created before this field was
introduced have an empty list, and were all built
from public news.
example:
- public_news_search
lastUpdated:
type: string
nullable: true
format: date-time
description: >-
The last updated timestamp of the Event, in UTC
and ISO 8601 format. This indicates when the Event
was last updated in our system, which can be
different from the timestamps of the underlying
Observations. It is useful for understanding the
recency of creation and mutation of the Event
information.
example: '2026-04-20T05:38:42.448Z'
taxonomicMatches:
type: object
properties:
affectedDatapoints:
type: array
items:
type: object
properties:
name:
type: string
description: >-
The matched procurement datapoint from
the Beroe taxonomy.
subject:
type: string
nullable: true
description: >-
The specific subject of the datapoint as
mentioned in the source articles, e.g.
`crude oil`, `semiconductors`, `shipping
services`. Null when no specific subject
was identified.
direction:
type: string
nullable: true
enum:
- up
- down
- fluctuate
- unknown
- null
description: >-
The direction of change, or null if the
direction could not be determined, or
for old legacy data that hasn't been
backfilled with direction.
quantity:
type: object
nullable: true
properties:
operator:
type: string
enum:
- '>'
- <
- '>='
- <=
- '='
- '~'
- range
description: >-
The comparison operator for the
quantified change. Single-value
operators (>, <, >=, <=, =, ~) expect
one entry in `values`; `range` expects
two (lower bound, upper bound).
values:
type: array
items:
type: number
description: >-
Numeric values for the operator. One
value for point operators (>, <, >=, <=,
=, ~); two values [lower, upper] for
`range`.
unit:
type: string
description: >-
Unit of the change, e.g. `%`, `USD`,
`barrels`.
required:
- operator
- values
- unit
description: >-
The quantified magnitude of the change,
if one was extractable from the source
articles.
example:
operator: '>'
values:
- 10
unit: '%'
required:
- name
- subject
- direction
- quantity
description: >-
An exact match of a procurement datapoint
from the Beroe taxonomy, together with the
direction and optional quantified magnitude
of the change.
example:
name: Unit Price
subject: crude oil
direction: up
quantity:
operator: '>'
values:
- 10
unit: '%'
example:
- name: Net Supply
subject: null
direction: down
quantity: null
- name: Unit Price
subject: crude oil
direction: up
quantity:
operator: '>'
values:
- 10
unit: '%'
description: >-
Taxonomic matches of the event's affected
datapoints to our pre-defined taxonomy in
Beroe Data Hub.
This provides a structured way to understand
the specific datapoints that are affected by
the event, which can be useful for filtering
and analyzing events based on their impact on
specific aspects of the supply chain.
The generation of these affected datapoints
are not tied to specific alert types or
impacted entities; rather, they are generated
based on the overall content of the event;
downstream consumers should not assume that
the affected datapoints and alert types /
impacted entities are mapped to each other
directly.
alertTypes:
type: array
items:
type: object
properties:
name:
type: string
description: >-
The name of the matched item. This is
the canonical name of the item in our
system, such as a company name or a
category name.
mappedFrom:
type: string
description: >-
The original text from the event's
content that was mapped to this item.
This is the actual text snippet that was
found in the event's content and matched
to the canonical item name.
method:
type: string
nullable: true
description: >-
The method used to determine the match.
This could be a specific NLP technique,
a rule-based approach, or a machine
learning model. It provides context on
how the match was derived.
similarity:
type: number
nullable: true
description: >-
A numerical score between 0 and 1
indicating the confidence level of the
match, with 1 being a perfect match.
This is particularly relevant for
matches determined through NLP
techniques, where there may be some
degree of uncertainty.
rationale:
type: string
nullable: true
description: >-
The rationale behind the match,
providing additional context or
explanation for why the match was made.
required:
- name
- mappedFrom
- method
- similarity
- rationale
description: >-
A fuzzy match result using NLP or LLM
techniques to a pre-defined list of values.
example:
name: Logistics and Supply Chain
mappedFrom: supply chain dependency
method: llm
similarity: 1
rationale: >-
Directly refers to supply chain logistics
and dependencies
example:
- name: Geopolitical and Trade
mappedFrom: geopolitical risk
method: llm
similarity: 1
rationale: >-
The candidate covers geopolitical risks
affecting trade and diplomatic relations.
- name: Logistics and Supply Chain
mappedFrom: supply chain dependency
method: llm
similarity: 1
rationale: >-
Directly refers to supply chain logistics
and dependencies
description: >-
Taxonomic matches of the event's alert types
to our pre-defined taxonomy in Beroe Data Hub.
This provides a structured way to understand
the types of alerts that need to be evaluated
and raised for this event.
The generation of these alert types are not
tied to specific affected datapoints; rather,
they are generated based on the overall
content of the event; downstream consumers
should not assume that the alert types and
datapoints are mapped to each other directly.
impactedEntities:
type: array
items:
type: object
properties:
name:
type: string
description: >-
The name of the impacted entity, such as
a company, category, country, or
location name.
example: Trade Finance Services
entityType:
type: string
enum:
- company
- category
- country
- location
- hierarchical_category
- supplier
description: The type of the relevant entity.
mappedFrom:
type: string
description: >-
The original text from the event's
content that was mapped to this impacted
entity.
example: >-
trade and investment integration:
Strategies that coordinate cross-border
trade flows with inward or outward
investment decisions.
levels:
type: array
nullable: true
items:
type: string
description: >-
The hierarchical levels of the impacted
entity, such as address, or different
levels of a hierarchical category, if
applicable.
example:
- Industry
- Sector
- Sub-sector
impact:
type: object
properties:
likelihood:
type: number
description: >-
The likelihood of the impact occurring,
on a scale from 0 to 3.
severity:
type: number
description: >-
The severity of the impact if it occurs,
on a scale from 0 to 3.
rationale:
type: string
description: >-
The rationale for the assigned
likelihood and severity scores.
required:
- likelihood
- severity
- rationale
description: >-
An impact assessment.
The likelihood and severity scores are
typically assigned based on the content
of the event and the LLM's understanding
of the potential consequences. The
rationale provides additional context
for these scores, which can be useful
for users to understand the reasoning
behind the impact assessment.
example:
likelihood: 2
severity: 1
rationale: >-
Policy emphasis may encourage firms to
pursue combined trade/investment
approaches, creating commercial
opportunities.
identifiers:
type: array
items:
oneOf:
- type: object
properties:
scheme:
type: string
enum:
- duns
value:
type: string
description: The company's DUNS number.
example: '123456789'
required:
- scheme
- value
description: >-
A Dun & Bradstreet DUNS number
identifying a company.
description: >-
An identifier for the entity in an
external scheme, told apart by `scheme`.
Today the only scheme is `duns`, a
supplier's Dun & Bradstreet number. More
schemes may be added later, such as
location codes, so clients should skip
schemes they don't recognise.
description: >-
Identifiers for the entity in external
schemes, such as the DUNS number of a
supplier. Left out when none are known.
example:
- scheme: duns
value: '123456789'
required:
- name
- entityType
- mappedFrom
- impact
description: >-
Taxonomic matches of the event's impacted
entities to our pre-defined taxonomy in Beroe
Data Hub.
Supports company, category, country, and
location entities, which can be used for
filtering and analysis of events based on the
entities they impact.
example:
- name: Trade Finance Services
entityType: category
mappedFrom: >-
trade and investment integration:
Strategies that coordinate cross-border
trade flows with inward or outward
investment decisions.
impact:
likelihood: 2
severity: 1
rationale: >-
Policy emphasis may encourage firms to
pursue combined trade/investment
approaches, creating commercial
opportunities.
- name: Investment Management
entityType: category
mappedFrom: >-
trade and investment integration:
Strategies that coordinate cross-border
trade flows with inward or outward
investment decisions.
impact:
likelihood: 2
severity: 1
rationale: >-
Policy emphasis may encourage firms to
pursue combined trade/investment
approaches, creating commercial
opportunities.
- name: Strategy Consulting
entityType: category
mappedFrom: >-
trade and investment integration:
Strategies that coordinate cross-border
trade flows with inward or outward
investment decisions.
impact:
likelihood: 2
severity: 1
rationale: >-
Policy emphasis may encourage firms to
pursue combined trade/investment
approaches, creating commercial
opportunities.
required:
- affectedDatapoints
- alertTypes
- impactedEntities
description: >-
Taxonomic matches of the event's affected
datapoints, alert types, and impacted entities to
our pre-defined taxonomy in Beroe Data Hub.
Affected datapoints include the matched datapoint
name, optional subject, direction of change, and
optional quantified magnitude. Alert types and
impacted entities retain their matching metadata.
This provides a structured way to understand how
the event's contents relate to specific concepts
in our taxonomy, which can be useful for
filtering, searching, and analyzing events based
on these standardized categories.
required:
- _id
- title
- summary
- vectorIndex
- lastUpdated
description: >-
One event group: the events that report the same
real-world occurrence, oldest first.
description: >-
A list of event groups updated in the last 24 hours,
within the specified page and page size.
required:
- meta
- data
'400':
description: Invalid query parameters
content:
application/json:
examples:
QUERY_VALIDATION_FAILED:
value:
success: false
errorCode: QUERY_VALIDATION_FAILED
message: Invalid query parameters
schema:
type: object
properties:
success:
type: boolean
enum:
- false
errorCode:
type: string
enum:
- USER_NOT_CONFIRMED
- INVALID_CREDENTIALS
- INCOMPLETE_CREDENTIALS
- INVALID_SESSION_TOKEN
- FORCE_CHANGE_PASSWORD
- PASSWORD_RESET_REQUIRED
- PASSWORD_EXPIRED
- CODE_EXPIRED
- SESSION_EXPIRED
- UNAUTHORISED
- AUTHENTICATOR_ERROR
- SSO_ACCOUNT
- FORBIDDEN
- METHOD_NOT_ALLOWED
- INVALID_INPUT
- PATH_VALIDATION_FAILED
- QUERY_VALIDATION_FAILED
- BODY_VALIDATION_FAILED
- RESPONSE_VALIDATION_FAILED
- INVALID_OR_MALFORMED_JSON
- INTERNAL_SERVER_ERROR
- CONFIGURATION_ERROR
- SERVICE_UNAVAILABLE
- NOT_FOUND
- CONFLICT
- LIMIT_EXCEEDED
- REVIEW_ALREADY_PENDING
- REVIEW_NOT_PENDING
- REVIEW_PENDING
- REVIEW_INSUFFICIENT_DOMAINS
- QUOTA_EXCEEDED
- UNSUPPORTED_ENDPOINT_VERSION
- ENDPOINT_NOT_FOUND
- ENDPOINT_ALREADY_EXISTS
message:
type: string
detail:
type: object
additionalProperties:
nullable: true
required:
- success
- errorCode
'401':
description: Unauthorized access - API Key is missing or invalid
content:
application/json:
examples:
UNAUTHORISED:
value:
success: false
errorCode: UNAUTHORISED
message: Unauthorized access - API Key is missing or invalid
schema:
type: object
properties:
success:
type: boolean
enum:
- false
errorCode:
type: string
enum:
- USER_NOT_CONFIRMED
- INVALID_CREDENTIALS
- INCOMPLETE_CREDENTIALS
- INVALID_SESSION_TOKEN
- FORCE_CHANGE_PASSWORD
- PASSWORD_RESET_REQUIRED
- PASSWORD_EXPIRED
- CODE_EXPIRED
- SESSION_EXPIRED
- UNAUTHORISED
- AUTHENTICATOR_ERROR
- SSO_ACCOUNT
- FORBIDDEN
- METHOD_NOT_ALLOWED
- INVALID_INPUT
- PATH_VALIDATION_FAILED
- QUERY_VALIDATION_FAILED
- BODY_VALIDATION_FAILED
- RESPONSE_VALIDATION_FAILED
- INVALID_OR_MALFORMED_JSON
- INTERNAL_SERVER_ERROR
- CONFIGURATION_ERROR
- SERVICE_UNAVAILABLE
- NOT_FOUND
- CONFLICT
- LIMIT_EXCEEDED
- REVIEW_ALREADY_PENDING
- REVIEW_NOT_PENDING
- REVIEW_PENDING
- REVIEW_INSUFFICIENT_DOMAINS
- QUOTA_EXCEEDED
- UNSUPPORTED_ENDPOINT_VERSION
- ENDPOINT_NOT_FOUND
- ENDPOINT_ALREADY_EXISTS
message:
type: string
detail:
type: object
additionalProperties:
nullable: true
required:
- success
- errorCode
'403':
description: API Key not subscribed to this endpoint
content:
application/json:
examples:
FORBIDDEN:
value:
success: false
errorCode: FORBIDDEN
message: API Key not subscribed to this endpoint
schema:
type: object
properties:
success:
type: boolean
enum:
- false
errorCode:
type: string
enum:
- USER_NOT_CONFIRMED
- INVALID_CREDENTIALS
- INCOMPLETE_CREDENTIALS
- INVALID_SESSION_TOKEN
- FORCE_CHANGE_PASSWORD
- PASSWORD_RESET_REQUIRED
- PASSWORD_EXPIRED
- CODE_EXPIRED
- SESSION_EXPIRED
- UNAUTHORISED
- AUTHENTICATOR_ERROR
- SSO_ACCOUNT
- FORBIDDEN
- METHOD_NOT_ALLOWED
- INVALID_INPUT
- PATH_VALIDATION_FAILED
- QUERY_VALIDATION_FAILED
- BODY_VALIDATION_FAILED
- RESPONSE_VALIDATION_FAILED
- INVALID_OR_MALFORMED_JSON
- INTERNAL_SERVER_ERROR
- CONFIGURATION_ERROR
- SERVICE_UNAVAILABLE
- NOT_FOUND
- CONFLICT
- LIMIT_EXCEEDED
- REVIEW_ALREADY_PENDING
- REVIEW_NOT_PENDING
- REVIEW_PENDING
- REVIEW_INSUFFICIENT_DOMAINS
- QUOTA_EXCEEDED
- UNSUPPORTED_ENDPOINT_VERSION
- ENDPOINT_NOT_FOUND
- ENDPOINT_ALREADY_EXISTS
message:
type: string
detail:
type: object
additionalProperties:
nullable: true
required:
- success
- errorCode
'500':
description: Internal Server Error
content:
application/json:
examples:
INTERNAL_SERVER_ERROR:
value:
success: false
errorCode: INTERNAL_SERVER_ERROR
message: Internal Server Error
schema:
type: object
properties:
success:
type: boolean
enum:
- false
errorCode:
type: string
enum:
- USER_NOT_CONFIRMED
- INVALID_CREDENTIALS
- INCOMPLETE_CREDENTIALS
- INVALID_SESSION_TOKEN
- FORCE_CHANGE_PASSWORD
- PASSWORD_RESET_REQUIRED
- PASSWORD_EXPIRED
- CODE_EXPIRED
- SESSION_EXPIRED
- UNAUTHORISED
- AUTHENTICATOR_ERROR
- SSO_ACCOUNT
- FORBIDDEN
- METHOD_NOT_ALLOWED
- INVALID_INPUT
- PATH_VALIDATION_FAILED
- QUERY_VALIDATION_FAILED
- BODY_VALIDATION_FAILED
- RESPONSE_VALIDATION_FAILED
- INVALID_OR_MALFORMED_JSON
- INTERNAL_SERVER_ERROR
- CONFIGURATION_ERROR
- SERVICE_UNAVAILABLE
- NOT_FOUND
- CONFLICT
- LIMIT_EXCEEDED
- REVIEW_ALREADY_PENDING
- REVIEW_NOT_PENDING
- REVIEW_PENDING
- REVIEW_INSUFFICIENT_DOMAINS
- QUOTA_EXCEEDED
- UNSUPPORTED_ENDPOINT_VERSION
- ENDPOINT_NOT_FOUND
- ENDPOINT_ALREADY_EXISTS
message:
type: string
detail:
type: object
additionalProperties:
nullable: true
required:
- success
- errorCode
components:
securitySchemes:
apiKeyAuth:
type: apiKey
in: header
name: x-api-key
description: >-
Pass a static API key for every request, provided by your customer
support.
bearerAuth:
type: http
scheme: bearer
description: >-
Bearer token authentication, using a sessionId generated by `GET
/v2/auth/session`.
sessionIdQuery:
type: apiKey
in: query
name: sessionId
description: >-
Session ID passed as a query parameter for authentication, provided by
`GET /v2/auth/session`.
````
This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.