Which source domains AI answer engines cite, by buyer category and question shape.
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Return one category's question shapes (best tools, how buyers choose, comparisons, top lists, problem-first research, is it worth it, news) and the evidence state of each: published with rates, collecting, or not collectable.
Category key from mri_list_categories, e.g. cybersecurity.
Return one category's question shapes (best tools, how buyers choose, comparisons, top lists, problem-first research, is it worth it, news) and the evidence state of each: published with rates, collecting, or not collectable.
| Argument | Type | Description |
|---|---|---|
| category* | string | Category key from mri_list_categories, e.g. cybersecurity. |
{
"type": "object",
"required": [
"category"
],
"properties": {
"category": {
"type": "string",
"description": "Category key from mri_list_categories, e.g. cybersecurity."
}
},
"additionalProperties": false
}Ranked source domains that AI answer engines cite for one category and question shape, with citation rate (share of monitored answer runs citing the domain), rank, percentile and source role (editorial publication, vendor-owned, analyst research, community, academic/government, market database, wire distribution). Use to answer 'which publications/sources does ChatGPT or Perplexity cite for <category>' or 'where should a <category> brand earn coverage to be cited by AI'.
| Argument | Type | Description |
|---|---|---|
| limit | integer | |
| offset | integer | |
| category* | string | Category key, e.g. cybersecurity. |
| source_role | string | Optional filter, e.g. editorial_media for publications only, vendor_owned, analyst_research, community_social. |
| question_shape* | string | Buyer question pattern: best_x (best X tools), how_choose (how to choose), is_x_worth (is it worth it), news_topic (recent news), problem_first (how to solve a problem), top_list (top platforms), x_vs_y (A vs B). |
{
"type": "object",
"required": [
"category",
"question_shape"
],
"properties": {
"limit": {
"type": "integer",
"default": 25,
"maximum": 100,
"minimum": 1
},
"offset": {
"type": "integer",
"default": 0,
"minimum": 0
},
"category": {
"type": "string",
"description": "Category key, e.g. cybersecurity."
},
"source_role": {
"type": "string",
"description": "Optional filter, e.g. editorial_media for publications only, vendor_owned, analyst_research, community_social."
},
"question_shape": {
"enum": [
"best_x",
"how_choose",
"is_x_worth",
"news_topic",
"problem_first",
"top_list",
"x_vs_y"
],
"type": "string",
"description": "Buyer question pattern: best_x (best X tools), how_choose (how to choose), is_x_worth (is it worth it), news_topic (recent news), problem_first (how to solve a problem), top_list (top platforms), x_vs_y (A vs B)."
}
},
"additionalProperties": false
}For one domain or URL, return how often AI answer engines cite it: overall citation rate, which engines cite it, confidence tier, rank among all cited domains and within its source role, and per-category segment rates. Use to answer 'does ChatGPT/Perplexity cite <site>' or 'how authoritative is <publication> as an AI source'.
| Argument | Type | Description |
|---|---|---|
| domain* | string | A domain (techcrunch.com) or any URL on it. |
{
"type": "object",
"required": [
"domain"
],
"properties": {
"domain": {
"type": "string",
"description": "A domain (techcrunch.com) or any URL on it."
}
},
"additionalProperties": false
}List every Machine Relations Index category (e.g. cybersecurity, fintech, enterprise-software, ai-visibility-geo) with the question shapes that have published citation rates, plus the source-role vocabulary. Call this first to get a valid category key.
No arguments.
{
"type": "object",
"properties": {},
"additionalProperties": false
}