← The evidence ledger
Evidence row 1222747
Observed , by probe.mcp/1.
- Kind
- mcp.tools
- About
- endpoint af3092d7-5007-456c-a250-da940dc0c8b3
- Recorded
- Previous row
- None: the first of its kind about this subject
- Body SHA-256
- 536fe2d9e70a765bd5512a732fc28db15d9f0f30234e23f3031f3d78fbb2dd48
- Leaf
- 0x41979ee2529f141dddf4fbe7e4d7e7d12fdcc343bcf095e2767d56792ca1b576
What was observed
{
"count": 7,
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{
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{
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},
{
"description": "Query the shared saved trend index without Product DNA. Maximum 1 credit(s); zero provider calls. Results rank explicit popularity or measured growth first, then US, UK, Canada and Australia, then Europe, alternating sources. data.brief groups the items into trending now, audience conversations, creative references, search demand and references, and names coverage gaps and next steps. Each item's evidence_class, uses and caution give what it supports and what it does not establish. Saves a result and debits credits when charged. The same request_id returns that saved result without a second charge; a new request_id is a new billable query.",
"inputSchema": {
"$schema": "http://json-schema.org/draft-07/schema#",
"additionalProperties": false,
"properties": {
"input": {
"additionalProperties": false,
"properties": {
"categories": {
"items": {
"enum": [
"COFFEE_BREWING",
"CONTENT_CREATION",
"CUSTOMER_DISCOVERY",
"SOFTWARE_DEVELOPMENT",
"PRODUCTIVITY",
"FITNESS",
"GARDENING",
"COOKING",
"SKINCARE",
"TRAVEL",
"AI",
"ECOMMERCE",
"FINANCE",
"EDUCATION",
"ENTERTAINMENT",
"SUSTAINABILITY",
"MARKETING",
"SALES",
"HEALTHCARE",
"HEALTH_WELLNESS",
"HOME_SERVICES",
"REAL_ESTATE",
"FASHION",
"BEAUTY",
"PETS",
"GAMING",
"PARENTING",
"AUTOMOTIVE",
"LEGAL",
"RESTAURANTS",
"SPORTS",
"CRYPTO",
"CAREERS",
"HOME_DECOR",
"WEDDINGS",
"OUTDOORS",
"PHOTOGRAPHY",
"CRAFTS_DIY",
"CYBERSECURITY",
"NONPROFIT",
"MUSIC_CREATION",
"DRINKS",
"GENERAL"
],
"type": "string"
},
"maxItems": 10,
"minItems": 1,
"type": "array"
},
"compare_to": {
"format": "date-time",
"pattern": "^(?:(?:\\d\\d[2468][048]|\\d\\d[13579][26]|\\d\\d0[48]|[02468][048]00|[13579][26]00)-02-29|\\d{4}-(?:(?:0[13578]|1[02])-(?:0[1-9]|[12]\\d|3[01])|(?:0[469]|11)-(?:0[1-9]|[12]\\d|30)|(?:02)-(?:0[1-9]|1\\d|2[0-8])))T(?:(?:[01]\\d|2[0-3]):[0-5]\\d(?::[0-5]\\d(?:\\.\\d+)?)?(?:Z))$",
"type": "string"
},
"content_types": {
"items": {
"enum": [
"VIDEO",
"CONVERSATION",
"SEARCH",
"ARTICLE"
],
"type": "string"
},
"maxItems": 4,
"minItems": 1,
"type": "array"
},
"country": {
"pattern": "^[A-Z]{2}$",
"type": "string"
},
"evidence_quality": {
"items": {
"enum": [
"ATTRIBUTED_METADATA",
"PERMITTED_TEXT",
"INSPECTED_MEDIA"
],
"type": "string"
},
"maxItems": 3,
"minItems": 1,
"type": "array"
},
"history_days": {
"maximum": 90,
"minimum": 1,
"type": "integer"
},
"language": {
"pattern": "^[a-z]{2}(?:-[A-Z]{2})?$",
"type": "string"
},
"limit": {
"default": 20,
"maximum": 100,
"minimum": 1,
"type": "integer"
},
"lookback_hours": {
"default": 72,
"maximum": 720,
"minimum": 1,
"type": "integer"
},
"observed_from": {
"format": "date-time",
"pattern": "^(?:(?:\\d\\d[2468][048]|\\d\\d[13579][26]|\\d\\d0[48]|[02468][048]00|[13579][26]00)-02-29|\\d{4}-(?:(?:0[13578]|1[02])-(?:0[1-9]|[12]\\d|3[01])|(?:0[469]|11)-(?:0[1-9]|[12]\\d|30)|(?:02)-(?:0[1-9]|1\\d|2[0-8])))T(?:(?:[01]\\d|2[0-3]):[0-5]\\d(?::[0-5]\\d(?:\\.\\d+)?)?(?:Z))$",
"type": "string"
},
"observed_market": {
"pattern": "^[A-Z]{2}$",
"type": "string"
},
"observed_to": {
"format": "date-time",
"pattern": "^(?:(?:\\d\\d[2468][048]|\\d\\d[13579][26]|\\d\\d0[48]|[02468][048]00|[13579][26]00)-02-29|\\d{4}-(?:(?:0[13578]|1[02])-(?:0[1-9]|[12]\\d|3[01])|(?:0[469]|11)-(?:0[1-9]|[12]\\d|30)|(?:02)-(?:0[1-9]|1\\d|2[0-8])))T(?:(?:[01]\\d|2[0-3]):[0-5]\\d(?::[0-5]\\d(?:\\.\\d+)?)?(?:Z))$",
"type": "string"
},
"platforms": {
"items": {
"enum": [
"TIKTOK",
"YOUTUBE",
"INSTAGRAM",
"FACEBOOK",
"X",
"REDDIT",
"GOOGLE",
"BING",
"AI_SEARCH",
"WEB",
"FORUM",
"GITHUB"
],
"type": "string"
},
"maxItems": 11,
"minItems": 1,
"type": "array"
},
"region": {
"maxLength": 100,
"minLength": 1,
"type": "string"
},
"signals": {
"items": {
"enum": [
"POPULAR_NOW",
"RISING",
"EMERGING",
"RECURRING_PROBLEM",
"SEARCH_INTEREST",
"CREATIVE_PATTERN",
"NEW_DEVELOPMENT",
"INSUFFICIENT_EVIDENCE"
],
"type": "string"
},
"maxItems": 8,
"minItems": 1,
"type": "array"
}
},
"type": "object"
},
"max_credits": {
"maximum": 1000,
"minimum": 0,
"type": "integer"
},
"request_id": {
"format": "uuid",
"pattern": "^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-8][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}|00000000-0000-0000-0000-000000000000|ffffffff-ffff-ffff-ffff-ffffffffffff)$",
"type": "string",
"x-mcp-header": "request-id"
}
},
"required": [
"request_id",
"max_credits",
"input"
],
"type": "object"
},
"name": "trendsfast_global_trends"
},
{
"description": "Rank evidence against confirmed project context or explicit temporary niche. Without product: maximum 3 credits and no new source research. A product needs the confirmed context_id: it first collects the brand's own sources fresh, then ranks through that product's lens: customers (Customers) 10 credits, niche (Trending) 25 credits, competitors (Competitors) 30 credits, formats (Formats) 20 credits, search (Search) 35 credits. A product on a typed niche is refused with PRODUCT_REQUIRES_CONTEXT and charges nothing; a typed niche is read without a product. Formats also reads the top TikTok and YouTube videos' transcripts, so each item's hook is its opening line. Search also asks ChatGPT, Claude, Gemini and Perplexity the category's buyer question (no brand is sent) and returns data.ai_answers: who each answer names, whether that includes the brand or its competitors, and the domains cited. A Customers or Trending call, or a read without product, also returns data.communities when the brand's confirmed communities have been read: each one's rules on self-promotion, links and AI-written posts (citing rule numbers), the formats it favours, what wins there over all time (winning_format, hook_pattern and avoid, read by Claude from its top posts), the moderators' pinned posts (pinned), and a play for taking part without breaking them. A Trending call may also give each item a topic_history: where its topic is in its life across days and channels (state, since, first_seen, peak_day, channels, 7-day velocity, as_of), or null until the topic has a lifecycle state; it is the only basis for saying when a topic started rising. new_research says whether the call collected or asked. CORE means a specific topic, problem, keyword or exact competitor-account match; sharing only a broad family such as AI is ADJACENT. A temporary niche may add communities, competitor_handles, competitor_domains and keywords for exact matching. data.brief and each item's evidence_class, uses and caution describe what the evidence supports. Saves a result and may debit credits.",
"inputSchema": {
"$schema": "http://json-schema.org/draft-07/schema#",
"additionalProperties": false,
"properties": {
"input": {
"additionalProperties": false,
"properties": {
"context_id": {
"format": "uuid",
"pattern": "^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-8][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}|00000000-0000-0000-0000-000000000000|ffffffff-ffff-ffff-ffff-ffffffffffff)$",
"type": "string"
},
"filters": {
"additionalProperties": false,
"default": {
"limit": 20,
"lookback_hours": 72
},
"properties": {
"categories": {
"items": {
"enum": [
"COFFEE_BREWING",
"CONTENT_CREATION",
"CUSTOMER_DISCOVERY",
"SOFTWARE_DEVELOPMENT",
"PRODUCTIVITY",
"FITNESS",
"GARDENING",
"COOKING",
"SKINCARE",
"TRAVEL",
"AI",
"ECOMMERCE",
"FINANCE",
"EDUCATION",
"ENTERTAINMENT",
"SUSTAINABILITY",
"MARKETING",
"SALES",
"HEALTHCARE",
"HEALTH_WELLNESS",
"HOME_SERVICES",
"REAL_ESTATE",
"FASHION",
"BEAUTY",
"PETS",
"GAMING",
"PARENTING",
"AUTOMOTIVE",
"LEGAL",
"RESTAURANTS",
"SPORTS",
"CRYPTO",
"CAREERS",
"HOME_DECOR",
"WEDDINGS",
"OUTDOORS",
"PHOTOGRAPHY",
"CRAFTS_DIY",
"CYBERSECURITY",
"NONPROFIT",
"MUSIC_CREATION",
"DRINKS",
"GENERAL"
],
"type": "string"
},
"maxItems": 10,
"minItems": 1,
"type": "array"
},
"compare_to": {
"format": "date-time",
"pattern": "^(?:(?:\\d\\d[2468][048]|\\d\\d[13579][26]|\\d\\d0[48]|[02468][048]00|[13579][26]00)-02-29|\\d{4}-(?:(?:0[13578]|1[02])-(?:0[1-9]|[12]\\d|3[01])|(?:0[469]|11)-(?:0[1-9]|[12]\\d|30)|(?:02)-(?:0[1-9]|1\\d|2[0-8])))T(?:(?:[01]\\d|2[0-3]):[0-5]\\d(?::[0-5]\\d(?:\\.\\d+)?)?(?:Z))$",
"type": "string"
},
"content_types": {
"items": {
"enum": [
"VIDEO",
"CONVERSATION",
"SEARCH",
"ARTICLE"
],
"type": "string"
},
"maxItems": 4,
"minItems": 1,
"type": "array"
},
"country": {
"pattern": "^[A-Z]{2}$",
"type": "string"
},
"evidence_quality": {
"items": {
"enum": [
"ATTRIBUTED_METADATA",
"PERMITTED_TEXT",
"INSPECTED_MEDIA"
],
"type": "string"
},
"maxItems": 3,
"minItems": 1,
"type": "array"
},
"history_days": {
"maximum": 90,
"minimum": 1,
"type": "integer"
},
"language": {
"pattern": "^[a-z]{2}(?:-[A-Z]{2})?$",
"type": "string"
},
"limit": {
"default": 20,
"maximum": 100,
"minimum": 1,
"type": "integer"
},
"lookback_hours": {
"default": 72,
"maximum": 720,
"minimum": 1,
"type": "integer"
},
"observed_from": {
"format": "date-time",
"pattern": "^(?:(?:\\d\\d[2468][048]|\\d\\d[13579][26]|\\d\\d0[48]|[02468][048]00|[13579][26]00)-02-29|\\d{4}-(?:(?:0[13578]|1[02])-(?:0[1-9]|[12]\\d|3[01])|(?:0[469]|11)-(?:0[1-9]|[12]\\d|30)|(?:02)-(?:0[1-9]|1\\d|2[0-8])))T(?:(?:[01]\\d|2[0-3]):[0-5]\\d(?::[0-5]\\d(?:\\.\\d+)?)?(?:Z))$",
"type": "string"
},
"observed_market": {
"pattern": "^[A-Z]{2}$",
"type": "string"
},
"observed_to": {
"format": "date-time",
"pattern": "^(?:(?:\\d\\d[2468][048]|\\d\\d[13579][26]|\\d\\d0[48]|[02468][048]00|[13579][26]00)-02-29|\\d{4}-(?:(?:0[13578]|1[02])-(?:0[1-9]|[12]\\d|3[01])|(?:0[469]|11)-(?:0[1-9]|[12]\\d|30)|(?:02)-(?:0[1-9]|1\\d|2[0-8])))T(?:(?:[01]\\d|2[0-3]):[0-5]\\d(?::[0-5]\\d(?:\\.\\d+)?)?(?:Z))$",
"type": "string"
},
"platforms": {
"items": {
"enum": [
"TIKTOK",
"YOUTUBE",
"INSTAGRAM",
"FACEBOOK",
"X",
"REDDIT",
"GOOGLE",
"BING",
"AI_SEARCH",
"WEB",
"FORUM",
"GITHUB"
],
"type": "string"
},
"maxItems": 11,
"minItems": 1,
"type": "array"
},
"region": {
"maxLength": 100,
"minLength": 1,
"type": "string"
},
"signals": {
"items": {
"enum": [
"POPULAR_NOW",
"RISING",
"EMERGING",
"RECURRING_PROBLEM",
"SEARCH_INTEREST",
"CREATIVE_PATTERN",
"NEW_DEVELOPMENT",
"INSUFFICIENT_EVIDENCE"
],
"type": "string"
},
"maxItems": 8,
"minItems": 1,
"type": "array"
}
},
"type": "object"
},
"include_adjacent": {
"default": true,
"type": "boolean"
},
"include_global": {
"default": true,
"type": "boolean"
},
"niche": {
"additionalProperties": false,
"properties": {
"adjacent_categories": {
"default": [],
"items": {
"maxLength": 180,
"minLength": 1,
"type": "string"
},
"maxItems": 20,
"type": "array"
},
"audiences": {
"default": [],
"items": {
"maxLength": 180,
"minLength": 1,
"type": "string"
},
"maxItems": 20,
"type": "array"
},
"capabilities": {
"default": [],
"items": {
"maxLength": 180,
"minLength": 1,
"type": "string"
},
"maxItems": 20,
"type": "array"
},
"communities": {
"items": {
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"minLength": 1,
"type": "string"
},
"maxItems": 10,
"type": "array"
},
"competitor_domains": {
"items": {
"maxLength": 180,
"minLength": 1,
"type": "string"
},
"maxItems": 20,
"type": "array"
},
"competitor_handles": {
"items": {
"maxLength": 180,
"minLength": 1,
"type": "string"
},
"maxItems": 40,
"type": "array"
},
"competitors": {
"default": [],
"items": {
"maxLength": 180,
"minLength": 1,
"type": "string"
},
"maxItems": 20,
"type": "array"
},
"customer_interests": {
"default": [],
"items": {
"maxLength": 180,
"minLength": 1,
"type": "string"
},
"maxItems": 20,
"type": "array"
},
"description": {
"maxLength": 2000,
"minLength": 3,
"type": "string"
},
"exclusions": {
"default": [],
"items": {
"maxLength": 180,
"minLength": 1,
"type": "string"
},
"maxItems": 20,
"type": "array"
},
"industry": {
"default": [],
"items": {
"maxLength": 180,
"minLength": 1,
"type": "string"
},
"maxItems": 20,
"type": "array"
},
"jobs": {
"default": [],
"items": {
"maxLength": 180,
"minLength": 1,
"type": "string"
},
"maxItems": 20,
"type": "array"
},
"keywords": {
"items": {
"maxLength": 180,
"minLength": 1,
"type": "string"
},
"maxItems": 20,
"type": "array"
},
"language": {
"maxLength": 20,
"type": "string"
},
"market": {
"maxLength": 100,
"type": "string"
},
"platforms": {
"default": [],
"items": {
"enum": [
"TIKTOK",
"YOUTUBE",
"INSTAGRAM",
"FACEBOOK",
"X",
"REDDIT",
"GOOGLE",
"BING",
"AI_SEARCH",
"WEB",
"FORUM",
"GITHUB"
],
"type": "string"
},
"maxItems": 11,
"type": "array"
},
"problems": {
"default": [],
"items": {
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"minLength": 1,
"type": "string"
},
"maxItems": 20,
"type": "array"
},
"product_categories": {
"default": [],
"items": {
"maxLength": 180,
"minLength": 1,
"type": "string"
},
"maxItems": 20,
"type": "array"
},
"topics": {
"default": [],
"items": {
"maxLength": 180,
"minLength": 1,
"type": "string"
},
"maxItems": 20,
"type": "array"
},
"url": {
"format": "uri",
"maxLength": 2048,
"type": "string"
}
},
"required": [
"description"
],
"type": "object"
},
"product": {
"enum": [
"customers",
"niche",
"competitors",
"formats",
"search"
],
"type": "string"
}
},
"type": "object"
},
"max_credits": {
"maximum": 1000,
"minimum": 0,
"type": "integer"
},
"request_id": {
"format": "uuid",
"pattern": "^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-8][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}|00000000-0000-0000-0000-000000000000|ffffffff-ffff-ffff-ffff-ffffffffffff)$",
"type": "string",
"x-mcp-header": "request-id"
}
},
"required": [
"request_id",
"max_credits",
"input"
],
"type": "object"
},
"name": "trendsfast_niche_trends"
},
{
"description": "Read the connected project name, ID and current confirmed niche context, or an explicit missing-context state. Returns the context_id that niche and Ask queries accept. No credit debit, context mutation or new research.",
"inputSchema": {
"$schema": "http://json-schema.org/draft-07/schema#",
"additionalProperties": false,
"properties": {},
"type": "object"
},
"name": "trendsfast_project_context"
},
{
"description": "Read a saved result, page it on next_cursor, or recover an exact accepted request ID. No credit debit or research. Source permissions, retention and context are rechecked.",
"inputSchema": {
"$schema": "http://json-schema.org/draft-07/schema#",
"additionalProperties": false,
"properties": {
"cursor": {
"maxLength": 512,
"type": "string"
},
"request_id": {
"format": "uuid",
"pattern": "^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-8][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}|00000000-0000-0000-0000-000000000000|ffffffff-ffff-ffff-ffff-ffffffffffff)$",
"type": "string",
"x-mcp-header": "request-id"
},
"result_id": {
"format": "uuid",
"pattern": "^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-8][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}|00000000-0000-0000-0000-000000000000|ffffffff-ffff-ffff-ffff-ffffffffffff)$",
"type": "string"
}
},
"type": "object"
},
"name": "trendsfast_read_result"
}
]
}What the leaf hashes
{"body":"536fe2d9e70a765bd5512a732fc28db15d9f0f30234e23f3031f3d78fbb2dd48","id":1222747,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793319907217377,"prev":null,"subject":"af3092d7-5007-456c-a250-da940dc0c8b3","subject_kind":"endpoint"}Proof
Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of (243099 rows).
- 0x4197a83da06078687c7c02f6dda030d2553c32d8f0397ca2ad5454ac4b08358d
- 0x4b48c7b6f75d1edf0f182efd0209b099a1568ff119dd606ccc3571383d024d0b
- 0x69eb2faf56ac603fe851dc5f93444ec06b15c32bcbfb61fcf5b29a0fba2472d4
- 0x3152415b4f7fd6668ebbb14c11dc0441336aa9d55334ab1f851cd58a1b0c5c08
- 0xa5c586ba40e7870f01f9550713bf78fc6702557f19b27bd083e37494321695d9
- 0x4d83009fdd54b96ada0bc9970b8127526b71b732fde308047c8c0d133fa5397b
- 0x191eaaf4f27015a81c6ade10365ffafb58ef2dc0e6164abb8067eb15f0eb5304
- 0xde29d89eef366d85bb3583ce18764a4d2fcf798edf835569bc1a45e8d3ad456b
- 0x518838646575e57c4a45da96c94e1d4f7b106a1075db0e5b59885c9941c5122f
- 0x3d2b947b66a65cd0aceedfc5ee4c024760a6d2a94b89ebdfd886d9ed05ed5dca
- 0x9846cbcb7a1bebc639615d7393b3d5347a07af0b33697f6030f6afc84b3195fa
- 0xe226567c96df43c9ffa01238eb3aea9c0de478ff057d56848a0462858afad839
- 0xcc206dc2f9e188db598d4b3a17da47efe415d2946ef4b3a478b5d02f3ddb1474
- 0x775f1cf1eda93a75a3d05aa8e7b45b258d1de91c21741301b1aa3d048fba588c
- 0xd7d5c71ec079257a487d0494049c896f97cf8bf7d89a43fea539777c548c96f3
- 0x50ca74d7c8f26a46e9c3b8fb5e7f9ebcdfdcc1b7c863db3b6d2b7c12e24ca66f
- 0xb0c9ef42e725578748f3119c9dbebf2fc437266bda013df29f98ed3ebe621403
- 0x30a81d8fcef4e8f9e2877c62796cfc5612fc1b251127d531dee28f8dbd5c5147
- Day root
- 0x0826c7ad6039e06a2360ca0a4a3a4fe7f2626c6dc19f71a37599386f78b39875
- Chained
- 0x36b4c8a1063758f0b8765fa1bdf75fa92fb543cc183add3e261880ee2bd1f822
- Published
- On Arc Testnet, block 69923247: 0x8704744146c6967c8abc9e9a99de4db7283b29e840922ea83a69b6fe776e6861