← The evidence ledger
Evidence row 2536496
Observed , by probe.mcp/1.
- Kind
- mcp.tools
- About
- endpoint 82972214-ef11-44a5-be02-2c42b3a5aab2
- Recorded
- Previous row
- #1300721
- Body SHA-256
- d4d2afabbe3ac52bcf320a34dc0fa923385e335899e9d2973e11acfa41d1ee8e
- Leaf
- 0xc607ab36213ad914253c098e20c86c2f75c8cc9f54ef2c0c1cfc2f59125ba191
What was observed
{
"count": 3,
"tools": [
{
"description": "List the cheapest Chinese AI models from NovAI's live price feed, ranked by a comparable cost unit (text: 1M input + 200K output; video: 5-second clip; image: per image). Use this when the user asks which model is cheapest, wants to compare costs, or is choosing a model by budget. For a batch cost estimate at list price, see https://aiapi-pro.com/video-cost-calculator (video) and https://aiapi-pro.com/image-cost-calculator (images).",
"inputSchema": {
"properties": {
"category": {
"description": "Video, Image, Chat / LLM, Audio, 3D, Embedding",
"type": "string"
},
"limit": {
"description": "max rows (default 10, max 50)",
"type": "integer"
},
"max_price": {
"description": "only models whose comparable cost is at or below this USD figure",
"type": "number"
}
},
"type": "object"
},
"name": "cheapest_models"
},
{
"description": "List the model categories available in NovAI's price feed (Chat / LLM, Video, Image, Audio, 3D, Embedding) with the number of models in each. Use this first when the category for a request is unclear, then call cheapest_models with that category. Machine-readable feed: https://aiapi-pro.com/china-ai-leaderboard.json",
"inputSchema": {
"properties": {},
"type": "object"
},
"name": "list_categories"
},
{
"description": "Look up the NovAI list price of a Chinese AI model by name fragment (seedance, kimi, glm, qwen, doubao, hunyuan, minimax...). Use this when the user asks what a specific model costs, or wants a price before choosing one. Returns the provider list price, the unit (per 1M tokens / per image / per generation) and the model id. Per-minute video costs with every row sourced: https://aiapi-pro.com/video-cost-2026",
"inputSchema": {
"properties": {
"model": {
"type": "string"
}
},
"required": [
"model"
],
"type": "object"
},
"name": "model_price"
}
]
}What the leaf hashes
{"body":"d4d2afabbe3ac52bcf320a34dc0fa923385e335899e9d2973e11acfa41d1ee8e","id":2536496,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793685643328486,"prev":1300721,"subject":"82972214-ef11-44a5-be02-2c42b3a5aab2","subject_kind":"endpoint"}Proof
Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of (425475 rows).
- 0xc607959feeb208fc95bbef834798ee3d95e1f1671b81c1494c70e9a292405438
- 0x9860a1609df66211cf163496fc62a38dcab1579906fb6d8c242c3464d4104fbd
- 0xdb5e46c5209b6ce54adffaaa89d064af2fb05582356d0d164da6bd9e501ff226
- 0xc95089eae6e5d3cf5442f9078a001fa729e7ed65a2538ec2abb287ada66b7938
- 0x74abcc3a366476571457b046cc406ee43d7bd233afcc5c62114af4c4d50e065c
- 0xe6b4e62273c341e8d74774a64ce48f3d6bdd1d71f8519f9cbe3bdff44ad55ef3
- 0x7969949848cbbcb61e07991cb87785c4d0e6b981610486f57fe338ffb89b8fe7
- 0xbc6c1ade2c996ac723f46319f327a7baa5909bb820f16f441398d722af851083
- 0xed5fb27c1c14b19ba606d360bfcf320ba702eb0b933e6c91cb7f75123d94029d
- 0x113f716773d6317f3a505b8db28dd8d35365448b32e560610704c752071cde31
- 0xc196a8f47faeeac548942dad4dbb48cccd86dfb773b8f2129a5f7ed024f86661
- 0x2776d6de184337d929278006b07b17c87f04f4b0c2a6ef891d856846b26b3417
- 0x757c81f4c079ccef5ee9694c28de1354dd783331e9778583284b2bcba45c4662
- 0xad3757a4386398bde7b5dfd7d1ed0d8391a8487b9cbded422b75d61d77ec3baf
- 0x20b1beb78a0f066bfa1ffbab05695dfb2940fd2df005cdcab3ae2e82d26c01a9
- 0x59b3a6fae1c920f45b1445649e93c8c7d68f3f69789b0df88522cdb15a28590b
- 0x7075a090980aecb33e9c15c829cb40f5b44385b6d91a159042263db068126b87
- 0xac5402954216dc6c7020a6405675c8fc3b0828c2ab02943d80de52677a2f1fc3
- 0x85f3a27c16056a361d9ba33355a575ca7123f86de901b204c88953c4b8ea441a
- Day root
- 0xb646ffa569e24bf8336b0a15a9d98d0a2f1239f58e10c2b18a9d22e43343566a
- Chained
- 0x35e926359fd19031c6b5e08fb3b44f2524386a57c8fdd353336c185603f53d43
- Published
- On Arc Testnet, block 70601990: 0xa5f9dadba13cde129126b950e64b815e6833cb8ff53b75026c9dbe769c3768c7