> ## Documentation Index > Fetch the complete documentation index at: https://docs.peakmetrics.com/llms.txt > Use this file to discover all available pages before exploring further. # Available mention filters > Returns the available filters and their options for querying workspace data. When filtering other endpoints, use each filter's `key`=`value` in the query string. Enum filters use the format `key[]=value` repeated for each value. This endpoint returns all of the platform's filters, with filters that are not available for the workspace returning an empty `options` array. ## OpenAPI ````yaml /api/api_docs.yaml get /workspaces/{workspaceId}/available-filters openapi: 3.1.0 info: title: PeakMetrics API description: > The PeakMetrics API provides programmatic access to narrative intelligence data. Access millions of mentions across news, social media, and online platforms, enriched with custom AI-powered smart categories and over 50 metadata properties. The API enables you to identify, analyze, and act on emerging narratives in real-time. version: 2.0.0 servers: - url: https://api.peakmetrics.com description: Main (production) server security: - BearerAuth: [] tags: - name: Authorization - name: Workspaces - name: Folders - name: Channels - name: Custom Channels - name: Custom Enrichments description: > Custom enrichments let you push external context about mentions into PeakMetrics, attached to individual mentions and used alongside all other mention metadata across the platform. Once written, enrichment values feed into narrative analysis, workspace summaries, and notifications, and are available through the customer API and the MCP server. Your team manages its own custom enrichments through the API: create one with `POST /customEnrichments`, list them with `GET /customEnrichments`, rename one or replace its option list with `PUT /customEnrichments/{enrichmentId}`, retire one with `DELETE /customEnrichments/{enrichmentId}`, and push values for individual mentions with `PUT /mentions/customEnrichments`. paths: /workspaces/{workspaceId}/available-filters: get: tags: - Workspaces summary: Available mention filters description: > Returns the available filters and their options for querying workspace data. When filtering other endpoints, use each filter's `key`=`value` in the query string. Enum filters use the format `key[]=value` repeated for each value. This endpoint returns all of the platform's filters, with filters that are not available for the workspace returning an empty `options` array. parameters: - $ref: '#/components/parameters/WorkspaceId' responses: '200': description: A JSON object containing the available filters for the workspace. content: application/json: schema: type: object properties: channels: type: object description: Available channel filters for this workspace. properties: name: type: string example: Channels key: type: string example: channels options: type: array description: >- The channels enabled for this workspace. Empty if no channels are configured. items: type: object properties: name: type: string description: Human-readable channel name. example: News value: type: string description: >- The value to pass in the `channels` query parameter. example: news languages: type: object description: Available language filters. properties: name: type: string example: Languages key: type: string example: languages options: type: array description: Supported language options. items: type: object properties: name: type: string description: Human-readable language name. example: English value: type: string description: >- ISO 639-1 language code to pass in the `languages` query parameter. example: en bot_ratings: type: object description: > A social media account's likelihood of being automated. This filter returns an empty `options` array if the workspace does not have at least one supported social channel. Values are on a 7 point scale ranging from `very_unlikely` to `almost_certain`, with high-follower accounts indicated as `further_investigation`. properties: name: type: string example: Bot Detection key: type: string example: bot_ratings options: type: array description: > Bot detection rating levels, ordered from lowest to highest confidence. Empty if the workspace does not include any social media channels. items: type: object properties: name: type: string description: Human-readable rating label. example: Almost Certain value: type: string description: >- The value to pass in the `bot_ratings` query parameter. enum: - none - further_investigation - very_unlikely - unlikely - potential - likely - very_likely - almost_certain example: almost_certain smart_categories: type: object description: > Available Smart Category filters for this workspace. Smart Categories are custom AI-powered classifiers configured per workspace (e.g., sentiment models, topic classifiers, violent rhetoric detection). Each model is listed as a separate entry with its own set of classification options. The filter returns an empty `models` array if no Smart Categories are configured for the workspace. properties: name: type: string example: Smart Categories key: type: string example: smart_categories models: type: array description: > The Smart Category models configured for this workspace. Empty if no Smart Categories are configured. items: type: object properties: name: type: string description: Human-readable name of the Smart Category model. example: JP Morgan Sentiment enrichment_id: type: integer description: > The unique identifier of the Smart Category enrichment. Used as the first part of the composite `smart_categories` query parameter value. example: 244 options: type: array description: >- The classification labels available for this model. items: type: object properties: name: type: string description: Human-readable classification label. example: Positive value: type: string description: > The composite value to pass in the `smart_categories` query parameter, in the format `{enrichmentId}:{categoryKey}`. example: 244:c0 custom_enrichments: type: object description: > Available custom enrichment filters for this workspace. Custom enrichments are structured fields provisioned for your team that attach external context to mentions. Each provisioned custom enrichment is listed as a separate entry with its own set of recorded values. Returns an empty `models` array if no custom enrichments are available for this workspace. properties: name: type: string example: Custom Enrichments key: type: string example: custom_enrichments models: type: array description: > The custom enrichments provisioned for the authenticated team. Empty if no custom enrichments are provisioned. items: type: object properties: name: type: string description: Human-readable name of the custom enrichment. example: Disinformation Analysis enrichment_id: type: integer description: > The unique identifier of the custom enrichment. Used as the first part of the composite `custom_enrichments` query parameter value. example: 1681 options: type: array description: > The values recorded so far for this custom enrichment. New values may be added over time, so this list is not exhaustive of what may be filterable in the future. items: type: object properties: name: type: string description: Human-readable value. example: Substantiated value: type: string description: > The composite value to pass in the `custom_enrichments` query parameter, in the format `{enrichment_id}:{value}`. example: 1681:Substantiated mention_type: type: object description: > Available mention type filters. Contains separate sub-filters for `social_media`, `news`, and `podcasts`, each with their own key and options. Each sub-filter returns an empty `options` array if the workspace does not include the corresponding channel type. properties: name: type: string example: Mention Type social_media: type: object description: Filter by social media post type. properties: name: type: string example: Social Media Posts key: type: string example: mention_type.social_media options: type: array description: > The available social media post type options. Empty if the workspace does not include any social media channels. items: type: object properties: name: type: string description: Human-readable post type label. example: Original Posts value: type: string description: >- The value to pass in the `mention_type.social_media` query parameter. example: original_posts news: type: object description: Filter to news mention type. properties: name: type: string example: News Articles key: type: string example: mention_type.news options: type: array description: The available news type options. items: type: object properties: name: type: string description: Human-readable label. example: News value: type: string description: >- The value to pass in the `mention_type.news` query parameter. example: news podcasts: type: object description: Filter to podcast mention types. properties: name: type: string example: Podcasts key: type: string example: mention_type.podcasts options: type: array description: The available podcast type options. items: type: object properties: name: type: string description: Human-readable label. example: Podcasts value: type: string description: >- The value to pass in the `mention_type.podcasts` query parameter. example: podcasts publisher_geography: type: object description: > Available publisher geography filters. Primarily applicable to news mentions. Contains separate sub-filters for `country`, `region`, and `subregion`, each with their own key and options. All sub-filter `options` arrays are empty if the workspace does not include the `news` channel. properties: name: type: string example: Publisher Geography (News Only) source_country: type: object description: > Filter by the publisher's country of origin. Options are derived from the data present in the workspace and may vary. properties: name: type: string example: Source Country key: type: string example: publisher_geography.source_country options: type: array description: > Countries represented by news publishers in this workspace. Empty if no publisher geography data is available. items: type: object properties: name: type: string description: Human-readable country name. example: United States value: type: string description: >- The value to pass in the `publisher_geography.source_country` query parameter. example: United States source_region: type: object description: Filter by the publisher's geographic region. properties: name: type: string example: Source Region key: type: string example: publisher_geography.source_region options: type: array description: The available region options. items: type: object properties: name: type: string description: Human-readable region name. example: Americas value: type: string description: >- The value to pass in the `publisher_geography.source_region` query parameter. example: Americas source_sub_region: type: object description: Filter by the publisher's geographic subregion. properties: name: type: string example: Source Subregion key: type: string example: publisher_geography.source_sub_region options: type: array description: The available subregion options. items: type: object properties: name: type: string description: Human-readable subregion name. example: Northern America value: type: string description: >- The value to pass in the `publisher_geography.source_sub_region` query parameter. example: Northern America '404': description: Workspace not found or user does not have access. components: parameters: WorkspaceId: name: workspaceId in: path required: true schema: type: integer minimum: 1 description: The unique identifier for the workspace. securitySchemes: BearerAuth: type: http scheme: bearer bearerFormat: JWT ````