Radarkit

Every project this key can reach: the project id every other tool needs (24 hex characters), the brand website, the AI models tracked, the number of active prompts and the next scheduled run. Call this first. Costs 1 API credit.

list_projects

The prompts a project tracks: id, text, topic, when each was last asked and the current status per AI model (completed, pending, processing, hold). Oldest first, at most 50 per call; follow next_cursor while has_more is true. Filter by topic_id to see one topic. Costs 1 API credit per call.

list_prompts

The brands and sites AI answers recommended, answer by answer: one row per recommended domain per answer with its position in the list (1 = first). Newest first, at most 50 per call; follow next_cursor. Filter by prompt_id or domain (for example the brand's own domain to see where it ranks). Dates YYYY-MM-DD, at most 31 days. For totals use get_competitors. Costs 1 API credit per call.

list_rankings

AI answers RadarKit collected for a project: one row per prompt, model and day with brand mention, position, sentiment, whether the model searched the web and which queries it ran, and how many competitors it named. Newest first, at most 50 rows per call; follow next_cursor while has_more is true. Dates are YYYY-MM-DD, at most 31 days per call. Set include_content to true to get each answer as Markdown, cut to max_content_chars; that costs 2 API credits instead of 1. To analyse many full answers use estimate_export and create_export instead of paging.

list_responses

The web pages AI answers cited or consulted for a project: one row per source per answer with the URL, domain, whether it was cited (linked in the answer) and its citation rank. Newest first, at most 50 per call; follow next_cursor. Filter by prompt_id, domain or cited. Dates YYYY-MM-DD, at most 31 days. For "which sites matter most" use top_source_domains instead. Costs 1 API credit per call.

list_sources

The topics of a project with how many prompts each one holds. Topics group prompts; you need a topic_id to add prompts. Costs 1 API credit.

list_topics

One project: name, website, region, timezone, the AI models it tracks, active prompt count and next scheduled run. Costs 1 API credit.

get_project

The web searches AI models ran behind the scenes to answer a prompt (query fanout): one row per answer that searched, with the list of search queries. Useful to see what the model thinks the question is really about and which phrasings to target. Newest first, at most 50 per call; follow next_cursor. Dates YYYY-MM-DD, at most 31 days. Costs 1 API credit per call.

get_query_fanout

One AI answer in full: the answer as Markdown (cut to max_content_chars), plus everything RadarKit extracted from it — the sources it cited or consulted, the competitors it named, the domains it ranked with their positions, and any shopping tiles. Use a response id from list_responses. Costs 2 API credits.

get_response

Restart a content article run that failed or was cancelled (get_content_run shows retryable: true). The run keeps its article and spends no new content credit; costs 1 API credit. Refused with RUN_NOT_RETRYABLE for runs that are still processing or already completed.

retry_content_run

Ask every tracked AI model this prompt right now instead of waiting for the project's next scheduled run. Costs 1 API credit plus 1 realtime credit from the project owner's balance (see realtime_credits_remaining in the result). Refused with PROMPT_PROCESSING while a run for that prompt is in flight, and with INSUFFICIENT_REALTIME_CREDITS when the owner has none — do not retry either. New answers appear in list_responses a few minutes later.

run_prompt_now

How AI answers talk about the brand when they mention it: counts and shares of positive, mixed and negative answers, overall and per model, for a 31-day window. Same scope as the Overview's Sentiment card (only answers that mention the brand). Costs 2 API credits.

get_sentiment

Which websites AI answers lean on most for a project: domains ranked by how often they were used, with their share of all source mentions, how many times they were actually cited, how many prompts they appeared for, which models used them, when they were last seen, and whether each is the brand, a configured competitor or another site. At most 50 domains per call, from a 31-day window. Costs 2 API credits.

top_source_domains

How visible the brand is in AI answers, day by day: the share of tracked prompt-and-model combinations whose answer mentioned the brand (visibility, 0 to 100), the brand score, and how often the brand appeared at the top, middle or bottom with positive, mixed or negative sentiment. One row per model per day plus an "all" row across every model; summary is the average over the window. Dates are YYYY-MM-DD, up to 366 days per call. Costs 1 API credit.

get_visibility

How often AI models ran a web search before answering, and what they searched for: the share of answers that searched, then per prompt the distinct search queries with how many times each was seen and the average number of queries per search. Pass prompt_id for one prompt (the Web Search card on its page) or leave it out for every active prompt (the Query Fanout table), most queries first. Dates YYYY-MM-DD, at most 31 days. Costs 2 API credits.

get_web_search