Evidence row 2158287

What was observed

{
  "count": 5,
  "tools": [
    {
      "description": "Rank models by monthly cost for a workload. Use a preset (chatbot, rag, coding_agent, research_agent) or give token numbers.",
      "inputSchema": {
        "properties": {
          "cached_percent": {
            "description": "Share of input billed at the cached price, 0-100 (default 50 if steps_per_task>1, else 0)",
            "type": "number"
          },
          "calls_per_day": {
            "description": "Calls (or agent tasks) per day",
            "type": "number"
          },
          "input_tokens": {
            "description": "Input tokens per call/step",
            "type": "number"
          },
          "limit": {
            "description": "How many to return (default 5, max 20)",
            "type": "number"
          },
          "output_tokens": {
            "description": "Output tokens per call/step",
            "type": "number"
          },
          "popular_only": {
            "description": "Only well-known models (default true)",
            "type": "boolean"
          },
          "preset": {
            "description": "Optional workload preset that fills in token defaults: chatbot, rag, coding_agent, research_agent. Explicit numbers override it.",
            "enum": [
              "chatbot",
              "rag",
              "coding_agent",
              "research_agent"
            ],
            "type": "string"
          },
          "steps_per_task": {
            "description": "Model calls per task for multi-step agents (default 1)",
            "type": "number"
          }
        },
        "type": "object"
      },
      "name": "cheapest_models_for"
    },
    {
      "description": "Compare 2-5 models on price and (optionally) on the monthly cost of one workload.",
      "inputSchema": {
        "properties": {
          "cached_percent": {
            "description": "Share of input billed at the cached price, 0-100 (default 50 if steps_per_task>1, else 0)",
            "type": "number"
          },
          "calls_per_day": {
            "description": "Calls (or agent tasks) per day",
            "type": "number"
          },
          "input_tokens": {
            "description": "Input tokens per call/step",
            "type": "number"
          },
          "models": {
            "items": {
              "type": "string"
            },
            "maxItems": 5,
            "minItems": 2,
            "type": "array"
          },
          "output_tokens": {
            "description": "Output tokens per call/step",
            "type": "number"
          },
          "preset": {
            "description": "Optional workload preset that fills in token defaults: chatbot, rag, coding_agent, research_agent. Explicit numbers override it.",
            "enum": [
              "chatbot",
              "rag",
              "coding_agent",
              "research_agent"
            ],
            "type": "string"
          },
          "steps_per_task": {
            "description": "Model calls per task for multi-step agents (default 1)",
            "type": "number"
          }
        },
        "required": [
          "models"
        ],
        "type": "object"
      },
      "name": "compare_models"
    },
    {
      "description": "Estimate the monthly API cost of an AI agent or chatbot on one model. Easiest: pass model + preset (chatbot, rag, coding_agent, research_agent). Or give input_tokens, output_tokens and calls_per_day (plus optional steps_per_task, cached_percent); explicit numbers override the preset.",
      "inputSchema": {
        "properties": {
          "cached_percent": {
            "description": "Share of input billed at the cached price, 0-100 (default 50 if steps_per_task>1, else 0)",
            "type": "number"
          },
          "calls_per_day": {
            "description": "Calls (or agent tasks) per day",
            "type": "number"
          },
          "input_tokens": {
            "description": "Input tokens per call/step",
            "type": "number"
          },
          "model": {
            "description": "Model id like anthropic/claude-sonnet-5.5, or a name like \"Grok 4.7\"",
            "type": "string"
          },
          "output_tokens": {
            "description": "Output tokens per call/step",
            "type": "number"
          },
          "preset": {
            "description": "Optional workload preset that fills in token defaults: chatbot, rag, coding_agent, research_agent. Explicit numbers override it.",
            "enum": [
              "chatbot",
              "rag",
              "coding_agent",
              "research_agent"
            ],
            "type": "string"
          },
          "steps_per_task": {
            "description": "Model calls per task for multi-step agents (default 1)",
            "type": "number"
          }
        },
        "required": [
          "model"
        ],
        "type": "object"
      },
      "name": "estimate_cost"
    },
    {
      "description": "Current API list price of one model (input, output, cached input per 1M tokens) plus example monthly agent costs.",
      "inputSchema": {
        "properties": {
          "model": {
            "description": "Model id like anthropic/claude-sonnet-5.5, or a name",
            "type": "string"
          }
        },
        "required": [
          "model"
        ],
        "type": "object"
      },
      "name": "get_model_price"
    },
    {
      "description": "List LLMs tracked by Agent Cost Hub with API list prices per 1M tokens. Optional filter by provider or text.",
      "inputSchema": {
        "properties": {
          "popular_only": {
            "type": "boolean"
          },
          "provider": {
            "description": "e.g. openai, anthropic, google",
            "type": "string"
          },
          "search": {
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "list_models"
    }
  ]
}

What the leaf hashes

{"body":"4207b3342fbc10ffb58dba1fe93e9ed1c63724eae066cf830d2dd17d62032271","id":2158287,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793630819202260,"prev":null,"subject":"cb26523a-21df-4f20-ac43-075b52e7129e","subject_kind":"endpoint"}

Proof

Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of 2026-11-02 (444186 rows).

1. 0x3b556cb2d28518a36b5caac7c74e3e61f3bfe02a8cb0595a2d0234965be38fa0
2. 0xcd960f319ab320f00ee9b140ca4963d4dd6a2761fd531410fcd045ce7a9cb9ec
3. 0xab175c5e92d16ac5a38767ffa9d38a0f0223947a4ea470fcee2e73c947504dbc
4. 0xa72743447af2e8dba5ead73483de8ffe00e5c4c1a6a6db86f41767e6af164608
5. 0x0dee84f5550fb4bbdab0a720c03d2ad0696cfa07b14ed0de740eb9472627d4b4
6. 0x793e776265a77db5076b1134c19e6867fcf8b01601f4465229f9776e7e80eee7
7. 0x9fe4272da84f1995e519f913c9258bb14fcf57583c293d39cd12e0b467e5adfd
8. 0xd33ef69984e1a1eccfc2d42d8cebfeeca2cdcfa8080ea1c4a697fa93f9935ef1
9. 0x15f7ff529d8380c22dc15161ec755b37adbc373b3067649b489836767715c3d7
10. 0x55c677d32ff6a20b58dcad74ef0229761486f2ec5d5ec05004d605e14ca729b4
11. 0x35d8466a1b1164401e37eab603d7f1f3a41843b2a82e92a0df1a2ef7ee3f2198
12. 0x066ca260f44392bd6f2d8db1214a53c03dfa715357ef60f9784f111e11047120
13. 0x507a2180313be0729754aef4a9f5ae0f5f1b96b322bfe83831a668afc9bd9d5e
14. 0x637ba5f029eadccf80c2665ace422cf50802b8ffd21717811c25c8f068f65dc8
15. 0x8448bd1fe3c2d48b62a118ace4a5cb82fee53586dd43d776c2526ad844398919
16. 0x8760c227928c5295506cd8606e763f86cf8cd2a549820fab4dc86d29ca0d816d
17. 0xa20b9be86af7d690e040c9060a373b2fc5498edf3432f43c26f74fa2febc1e9a
18. 0x050f2978b537f7afb21ee1551577cdf146d1c56f4df12d24315ae5e69366b0a4
19. 0x365b161a4b68d750dcc4b3ecce1154a2163c87b08762079428e68f0ebb6a754e

Day root

0x78fecaabbe319e56f5c4b80fc02e2052e198ad24781da8832a475ff65f2002d1

Chained

0xdc35957db5d1371ca382b9152878ffece28ec7c5cb4f98fd71ddb367f8b999b2

Published

On Arc Testnet, block 70432815: 0x56b814612eb2e3e544153df3e91e1f7199106d1e430c7d8c6b653feeb9ebe9af