Evidence row 126106

What was observed

{
  "endpoints": [
    [
      "x402",
      "https://x402.forgemesh.io/text-vectorizer"
    ]
  ],
  "name": "x402.forgemesh.io/text-vectorizer",
  "owner_address": "0x850363a27f0ac6feb9c7a3ec4c1d295262df9432",
  "raw": {
    "accepts": [
      {
        "amount": "2000",
        "asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
        "extra": {
          "name": "USD Coin",
          "version": "2"
        },
        "maxTimeoutSeconds": 300,
        "network": "eip155:8453",
        "payTo": "0x850363a27F0aC6fEb9C7a3eC4C1d295262dF9432",
        "scheme": "exact"
      }
    ],
    "description": "Vector embeddings API: converts up to 64 pieces of text per call into 768-dimensional numeric vectors suitable for similarity comparison, no separate provider account or key needed. Pay per call in USDC, and nothing submitted is retained afterward. Use it to build semantic search indexes, cluster related documents, or de-duplicate near-identical text at scale.",
    "extensions": {
      "bazaar": {
        "info": {
          "input": {
            "body": {
              "texts": [
                "agent payments",
                "x402 protocol"
              ]
            },
            "bodyType": "json",
            "method": "POST",
            "type": "http"
          },
          "output": {
            "example": {
              "dimensions": 768,
              "embeddings": [
                [
                  0.011,
                  -0.02
                ],
                [
                  0.03,
                  0.004
                ]
              ],
              "model": "nomic-embed-text"
            },
            "type": "json"
          }
        },
        "schema": {
          "$schema": "https://json-schema.org/draft/2020-12/schema",
          "properties": {
            "input": {
              "additionalProperties": false,
              "properties": {
                "body": {
                  "properties": {
                    "text": {
                      "description": "single text alternative to texts[]",
                      "type": "string"
                    },
                    "texts": {
                      "description": "1-64 texts to embed",
                      "items": {
                        "type": "string"
                      },
                      "type": "array"
                    }
                  },
                  "type": "object"
                },
                "bodyType": {
                  "enum": [
                    "json",
                    "form-data",
                    "text"
                  ],
                  "type": "string"
                },
                "method": {
                  "enum": [
                    "POST"
                  ],
                  "type": "string"
                },
                "type": {
                  "const": "http",
                  "type": "string"
                }
              },
              "required": [
                "type",
                "method",
                "bodyType",
                "body"
              ],
              "type": "object"
            },
            "output": {
              "properties": {
                "example": {
                  "type": "object"
                },
                "type": {
                  "type": "string"
                }
              },
              "required": [
                "type"
              ],
              "type": "object"
            }
          },
          "required": [
            "input"
          ],
          "type": "object"
        }
      },
      "info": {
        "required": false
      },
      "offer-receipt": {
        "info": {
          "offers": [
            {
              "acceptIndex": 0,
              "format": "eip712",
              "payload": {
                "amount": "2000",
                "asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
                "network": "eip155:8453",
                "payTo": "0x850363a27F0aC6fEb9C7a3eC4C1d295262dF9432",
                "resourceUrl": "https://x402.forgemesh.io/text-vectorizer",
                "scheme": "exact",
                "validUntil": 1791503884,
                "version": 1
              },
              "signature": "0xaae9789a356fc61b36705a56a34d128724167370eb06064eca507ada7687847f43491cd21b4b9af3d86e2216d4239f1091c7fa339dc39d2634384708b65788071c"
            }
          ]
        },
        "schema": {
          "$schema": "https://json-schema.org/draft/2020-12/schema",
          "properties": {
            "offers": {
              "items": {
                "properties": {
                  "acceptIndex": {
                    "type": "integer"
                  },
                  "format": {
                    "type": "string"
                  },
                  "payload": {
                    "properties": {
                      "amount": {
                        "type": "string"
                      },
                      "asset": {
                        "type": "string"
                      },
                      "network": {
                        "type": "string"
                      },
                      "payTo": {
                        "type": "string"
                      },
                      "resourceUrl": {
                        "type": "string"
                      },
                      "scheme": {
                        "type": "string"
                      },
                      "validUntil": {
                        "type": "integer"
                      },
                      "version": {
                        "type": "integer"
                      }
                    },
                    "required": [
                      "version",
                      "resourceUrl",
                      "scheme",
                      "network",
                      "asset",
                      "payTo",
                      "amount"
                    ],
                    "type": "object"
                  },
                  "signature": {
                    "type": "string"
                  }
                },
                "required": [
                  "format",
                  "signature"
                ],
                "type": "object"
              },
              "type": "array"
            }
          },
          "required": [
            "offers"
          ],
          "type": "object"
        }
      },
      "schema": {
        "$schema": "https://json-schema.org/draft/2020-12/schema",
        "properties": {
          "id": {
            "maxLength": 128,
            "minLength": 16,
            "pattern": "^[a-zA-Z0-9_-]+$",
            "type": "string"
          },
          "required": {
            "type": "boolean"
          }
        },
        "required": [
          "required"
        ],
        "type": "object"
      }
    },
    "lastUpdated": "2026-10-08T23:53:04.397Z",
    "quality": {
      "l30DaysTotalCalls": 2,
      "l30DaysUniquePayers": 2,
      "lastCalledAt": "2026-10-08T23:53:04.132Z"
    },
    "resource": "https://x402.forgemesh.io/text-vectorizer",
    "type": "http",
    "x402Version": 2
  },
  "source": "x402_bazaar",
  "summary": "Vector embeddings API: converts up to 64 pieces of text per call into 768-dimensional numeric vectors suitable for similarity comparison, no separate provider account or key needed. Pay per call in USDC, and nothing submitted is retained afterward. Use it to build semantic search indexes, cluster related documents, or de-duplicate near-identical text at scale."
}

What the leaf hashes

{"body":"f6a9d1b0b08d6664bf748914c991157695643cacab05b265f522d9bc1e6cc417","id":126106,"kind":"listing","method":"baseline/1","observed_us":1793025627232580,"prev":null,"subject":"x402_bazaar:https://x402.forgemesh.io/text-vectorizer","subject_kind":"source_record"}

Proof

Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of 2026-10-26 (296695 rows).

1. 0x7dc2b64a8cae161a61fce9617cd3a92fb541d6c3660532127a40534dd56a2e87
2. 0x657c7c71400a33de008a53608ab1f6a670c31455e0223819bfb9678e2b710188
3. 0x4ae2367c233ef7c929417dcffe52aa3b67d8a62332ddaef8e1c57da08a170d24
4. 0x9405b718fb066b34eb69a0d66d8a0ba00c94ea6051f7ba339b93ccaf37f166d8
5. 0xe349e2da28a75d476a8f4101566fd19c962347a31a84db3f594e570b1a96fc40
6. 0xfa8d2cca59bffb05fb1520a2867fb6062e540ac3cf3d6bac32f5dbda091ece32
7. 0x752a6308d420a7aedd9076d88f24db9f0f4c8e9e58a4311cab2128a31e927135
8. 0x4a6cdfb800a495e78f277bd519b765ba2c68c7bb4a1b1992ebccfdc8741d079d
9. 0xca4de9d28408d7dddd5546456f374709b11bc58deba5a4057f79915305523933
10. 0x9fa5dbe99ca21068042ed16a3612abec879ae9bc437beeaf788519de22645918
11. 0xaf10e841089e5989890dc77ffce42a46564d25ef15f30d1e35bf53a495483ad4
12. 0xab729e4203b650f2a3c15efd6fd44eb2482232373bc1de662fd9d496869eb2d3
13. 0x0bffb634300aa5609bddaa79e8d31d7cde36c0a5a4465472f809b9f5287e40d2
14. 0x7721d38652b6444b18e1193824e50490ade04851ce6221771f6e374c4527d80f
15. 0x15039087bf60ae9b06b756ec3cbc299760e59923a438bbd91e34d105186db0ed
16. 0x2b6e23e3624a1b66e1d2298cfbce99a93ce6b13d24a58112a71802d79c5f7a76
17. 0xd21942ae3214eff88e08ab04884fd4b11958b51af9a0741b7668e2d07a2c56c9
18. 0x9a9024edb5069d88a324facb310a5ce8e495214bbaa968f077bede437390194f
19. 0x9b9ce5b74b9bab5121612ef6b64920a8d453cbf311096a423eef9702747e868a

Day root

0xf43e8dcc3d451a4788b26be904c55e8c4c0fa75c9666796c51db38d37e2c0df8

Chained

0x702d5ac508f08b0d1accf36af25822d8e5660367494edd17a642fb61e158a57a

Published

On Arc Testnet, block 69251483: 0x495162f8936e19f0039918feebe6c307f327cd6bf8c37219620b1970041fa9ae