> ## Documentation Index > Fetch the complete documentation index at: https://docs.verseodin.com/llms.txt > Use this file to discover all available pages before exploring further. # List brands tracked in a universe (mentions + citations + ranking) > Synthesises a per-brand summary from the universe's history row — one entry per distinct brand drawn from `ai_visibility_ranking`, `ai_competitive_analysis`, and `geo_competitor_analysis`. The output **includes the universe owner's own brand AND every competitor**. Each row carries: - `brand_name` — display name (preserves case from source) - `trust_mentions` — count of prompts where the brand was mentioned - `share_of_voice` — share of total brand mentions in this universe (%) - `visibility_rank` — 1-indexed rank by mention frequency - `ai_coverage_pct` — % of prompts covering this brand (AI tab) - `geo_coverage_pct` — % of prompts citing this brand's domain - `geo_prompt_count` — count of prompts citing this brand's domain Sorted by `visibility_rank` ASC (rank 1 first), then `trust_mentions` DESC. If multiple history rows match the filters, the most recent one is used; the response includes the resolved `day` + `engine` so callers know exactly which row was consulted. ## OpenAPI ````yaml /openapi.yaml get /universes/{id}/brands openapi: 3.1.0 info: title: Verseodin API version: 1.0.0 description: | Read-only HTTP API for pulling Verseodin dashboard data: universes, history rows (per-day aggregates of brand visibility, citations, and mentions across AI search engines), and full prompt records including the AI's response text and cited URLs. The same key authorises the Verseodin Claude / MCP connector — one credential, two surfaces. servers: - url: https://verseodin.com/api/v1 description: Production security: - BearerAuth: [] paths: /universes/{id}/brands: get: tags: - Brands summary: List brands tracked in a universe (mentions + citations + ranking) description: | Synthesises a per-brand summary from the universe's history row — one entry per distinct brand drawn from `ai_visibility_ranking`, `ai_competitive_analysis`, and `geo_competitor_analysis`. The output **includes the universe owner's own brand AND every competitor**. Each row carries: - `brand_name` — display name (preserves case from source) - `trust_mentions` — count of prompts where the brand was mentioned - `share_of_voice` — share of total brand mentions in this universe (%) - `visibility_rank` — 1-indexed rank by mention frequency - `ai_coverage_pct` — % of prompts covering this brand (AI tab) - `geo_coverage_pct` — % of prompts citing this brand's domain - `geo_prompt_count` — count of prompts citing this brand's domain Sorted by `visibility_rank` ASC (rank 1 first), then `trust_mentions` DESC. If multiple history rows match the filters, the most recent one is used; the response includes the resolved `day` + `engine` so callers know exactly which row was consulted. operationId: listBrands parameters: - $ref: '#/components/parameters/UniverseId' - $ref: '#/components/parameters/Day' - $ref: '#/components/parameters/Engine' responses: '200': description: OK content: application/json: schema: type: object properties: data: type: array items: $ref: '#/components/schemas/BrandSummary' day: type: string format: date nullable: true engine: type: string nullable: true example: data: - brand_name: verseodin.com trust_mentions: 42 share_of_voice: 18.7 visibility_rank: 1 ai_coverage_pct: 32.5 geo_coverage_pct: 12 geo_prompt_count: 60 - brand_name: semrush.com trust_mentions: 25 share_of_voice: 11.2 visibility_rank: 2 ai_coverage_pct: 19.3 geo_coverage_pct: 7.4 geo_prompt_count: 37 - brand_name: tryprofound.com trust_mentions: 14 share_of_voice: 6.3 visibility_rank: 3 ai_coverage_pct: 11 geo_coverage_pct: 3.1 geo_prompt_count: 16 day: '2026-04-27' engine: chatgpt '400': $ref: '#/components/responses/BadRequest' '401': $ref: '#/components/responses/Unauthorized' '403': $ref: '#/components/responses/Forbidden' '404': $ref: '#/components/responses/NotFound' components: parameters: UniverseId: name: id in: path required: true schema: type: string format: uuid description: Universe UUID — see `GET /universes`. Day: name: day in: query required: false schema: type: string format: date description: >- Pin the query to a specific day (`YYYY-MM-DD`). Without this, returns the most recent day. Engine: name: engine in: query required: false schema: type: string enum: - chatgpt - gemini - grok - claude description: Filter to a single AI engine. Omit for all. schemas: BrandSummary: type: object description: | Synthesised per-brand summary built from the universe's latest history row. The response of `/universes/{id}/brands` is an array of these; `/universes/{id}/brands/{brand}` is one of them. properties: brand_name: type: string description: Display name (preserves casing from the source history JSON). example: verseodin.com trust_mentions: type: integer nullable: true description: >- Count of prompts where this brand was mentioned in the AI's answer. Drawn from `ai_visibility_ranking`. example: 42 share_of_voice: type: number nullable: true description: >- This brand's share of total brand mentions in the universe (percent). Drawn from `ai_visibility_ranking`. example: 18.7 visibility_rank: type: integer nullable: true description: >- 1-indexed rank among all brands by trust mention frequency. `1` is the most-mentioned brand. example: 1 ai_coverage_pct: type: number nullable: true description: >- Percentage of prompts that covered this brand (AI Visibility tab). Drawn from `ai_competitive_analysis`. example: 32.5 geo_coverage_pct: type: number nullable: true description: >- Percentage of prompts where the AI cited this brand's domain. Drawn from `geo_competitor_analysis`. example: 12 geo_prompt_count: type: integer nullable: true description: Count of prompts where this brand's domain was cited at least once. example: 60 day: type: string format: date nullable: true description: >- Day of the history row this summary was extracted from. Only present on the single-brand endpoint. example: '2026-04-27' engine: type: string nullable: true description: Engine of the history row this summary was extracted from. example: chatgpt Error: type: object required: - error properties: error: type: object required: - type - message properties: type: type: string enum: - authentication_error - permission_error - not_found - invalid_request_error - rate_limit_error - api_error description: Machine-readable error category. message: type: string description: Human-readable explanation. responses: BadRequest: description: Malformed request (bad UUID, bad date, etc.). content: application/json: schema: $ref: '#/components/schemas/Error' Unauthorized: description: Missing / invalid / revoked API key. content: application/json: schema: $ref: '#/components/schemas/Error' Forbidden: description: API key is valid but doesn't own the requested universe. content: application/json: schema: $ref: '#/components/schemas/Error' NotFound: description: Universe (or metric, or row) doesn't exist. content: application/json: schema: $ref: '#/components/schemas/Error' securitySchemes: BearerAuth: type: http scheme: bearer bearerFormat: vso_<48 hex chars> description: | Generate a key at `/dashboard/settings/api-keys`. Pass it as `Authorization: Bearer vso_xxx` on every request. ````