GetMint

Poll content generation progress after trigger_content_generation. Shows current phase, progress %, and any errors.

get_generation_status

SHOPPING leaderboard: brands ranked by how often they appear across the domain's shopping / product queries (Amazon, Google Shopping, and other product surfaces). This is the SHOPPING surface only — for the answer-engine brand-mention ranking on a topic (LLM chat answers), use `get_topic_mentions` instead. Returns an empty list for domains that have no shopping queries configured.

get_top_shopping_brands

Fetch a single tracked topic by ID with its configuration (prompts, LLM models, markets). `name` is the stored label; `displayName` is what the topic is shown as and what its competition prompts compare brands on, and `competitionSubject` overrides that subject when set. Both are absent when unset, in which case `name` is used.

get_topic

Recent competition runs for a topic, newest first: the latest 10 analyses, each with its `reportDate`, YOUR brand `averageScore` (0-100 competition score), `scoreVariation` and `availableModels`. Limits: takes no date and cannot reach analyses older than those 10, so it is not a monthly history; it returns no per-competitor scores. For competitor visibility use get_topic_visibility.

get_topic_competition

Brand-mention leaderboard for a topic: every brand — YOUR brand AND each tracked competitor — ranked by how often LLMs name it when answering the topic prompts. This is the "share of voice by brand" / most-mentioned-brands ranking (use it to compare mention share across brands, e.g. GetMint vs Profound vs Peec AI vs Otterly). Returns `mentions` (`[{ mention, count, percentage }]`, sorted by count DESC, where `mention` is the brand name and `percentage` is its 0-100 share of all mentions), `mentionsDetailed` (per-model `{ mention, modelId, count }`), and pagination (`total`, `page`, `limit`, `totalPages`). Present each `percentage` with a "%". Limits: returns totals for one window, with no time series and no rolling average. Omitting `startDate`/`endDate` covers the last 6 months up to now, so for month-by-month figures call it once per month with that month as `startDate`/`endDate`. Never present figures from an unfiltered call as belonging to a specific month. Each share is cumulative over the window it was called with, for your brand and for competitors.

get_topic_mentions

Quick headline for a topic, YOUR brand only: `summary.averageVisibilityScore` and `summary.averageCompetitionScore` (0-100, averaged over the topic analyses of the last 30 days), report counts, `lastAnalyzed`, `analysisRange`, and `trends` (improving / declining / stable). Limits: the 30-day window is fixed and takes no date; it returns no competitor figures and no sentiment; the average is a single value, not a rolling series. For competitor scores use get_topic_visibility.

get_topic_summary

Visibility report for a topic: how often LLMs mention YOUR brand AND each tracked competitor when answering the topic prompts. Returns `visibilityScore` (your brand, 0-100 percentage), `scoreVariation` (change vs the previous period, in percentage points; 0 = no change), `competitors` (each `{ name, visibilityScore }`, ranked highest-first — use this to compare your brand against competitors like Profound, Peec AI, Otterly), `modelBreakdown` (per-model visibility), `topMentions`, `totalPromptsTested`, `totalAnswers` (answers the scores are computed from). Every score is a 0-100 percentage — present it with a "%". Limits: returns totals for one window, with no time series and no rolling average. Omitting `startDate`/`endDate` covers the last 6 months up to now, so for month-by-month figures call it once per month with that month as `startDate`/`endDate`. Never present figures from an unfiltered call as belonging to a specific month. `dateRange` (`{ start, end }`) gives the first and last analysis dates the scores cover — quote it so the user knows the period.

get_topic_visibility

List content briefs for a domain with pagination. Use this as the starting point to discover briefIds before calling other tools.

list_briefs

List every domain accessible to the authenticated organization. Typically the first call an agent makes — all other insights tools require a domainId.

list_domains

Paginated list of INDIVIDUAL citations — the exact source URLs LLMs cite, item by item (not just the aggregated domains from get_domain_explorer_aggregated). Each row carries `link` (the exact cited URL), `linkDomain`, the analysis type, and the model. Use the filters (the array filters take a list of strings) to drill from a domain to its exact pages: pass `topicName: ["US - GEO - Transactionnel"]` to scope to a topic (use the exact name from list_topics), `linkDomain: ["reddit.com"]` to list the exact Reddit threads, `linkDomain: ["youtube.com"]` for the exact videos, or `linkDomain: ["g2.com"]` to find the exact page to target for a mention. `searchQuery` substring-matches the PROMPT/QUERY text that produced the citation (not the cited URL — use `linkDomain` for that). HARD LIMIT: results are always scoped to the LAST 1 MONTH (the citation set is huge; a wider window would time out) — page through with `page`/`pageSize` rather than expecting a longer history.

list_explorer_citations

List every tracked topic attached to a domain.

list_topics

Enqueue article generation for a brief whose document has been finalized. Consumes CONTENT_GENERATION credits (scaled by word count). Returns immediately (202); poll with get_generation_status. If the brief's metadata.brandKitId is set, generation applies the kit's tone, pronoun, style flags, author persona, and blocklist (blocked words/competitors are rewritten out during the polish step).

trigger_content_generation