Evidence row 1527

What was observed

{
  "endpoints": [
    [
      "x402",
      "https://api.x402ai.dev/api/ask"
    ],
    [
      "x402",
      "https://api.x402ai.dev/api/embed"
    ],
    [
      "x402",
      "https://api.x402ai.dev/api/summarize"
    ]
  ],
  "name": "api.x402ai.dev",
  "owner_address": null,
  "raw": {
    "caip2_networks": [
      "eip155:8453"
    ],
    "category": "",
    "description": "",
    "domain": "api.x402ai.dev",
    "endpoints": [
      {
        "description": "Answers questions (single-turn question answering) from a small local LLM (qwen3.5 2B). Best for general knowledge, definitions and simple reasoning. POST JSON {\"input\": string}, up to 3000 characters; returns {answer, model, elapsed_ms}. Answers are brief (2-3 sentences). Typically 5-15 s. Known limits: no web access, no memory between calls, and it can hallucinate or be wrong on recent events and obscure facts. Answers are unverified.",
        "method": "POST",
        "parameters": [
          {
            "default": null,
            "description": "",
            "enumValues": [],
            "example": "What is the capital of France?",
            "group": "body",
            "name": "input",
            "required": false,
            "type": "string"
          }
        ],
        "pricing": {
          "amount": "0.04",
          "currency": "USDC",
          "maxAmount": "",
          "minAmount": "",
          "network": "eip155:8453",
          "scheme": "exact"
        },
        "providerName": "",
        "quality": {
          "l30DaysTotalCalls": "4",
          "l30DaysUniquePayers": "2"
        },
        "serviceName": "x402ai",
        "tags": [
          "question-answering",
          "qa",
          "llm",
          "general-knowledge",
          "ai"
        ],
        "url": "https://api.x402ai.dev/api/ask"
      },
      {
        "description": "Convert text into a 768-dimension embedding vector (nomic-embed-text) for semantic search, RAG retrieval, clustering, deduplication or similarity scoring. POST JSON {\"input\": string}, up to 3000 characters; returns {embedding: number[768], model, dimensions, elapsed_ms}. One text per call; English works best.",
        "method": "POST",
        "parameters": [
          {
            "default": null,
            "description": "",
            "enumValues": [],
            "example": "The quick brown fox jumps over the lazy dog.",
            "group": "body",
            "name": "input",
            "required": false,
            "type": "string"
          }
        ],
        "pricing": {
          "amount": "0.01",
          "currency": "USDC",
          "maxAmount": "",
          "minAmount": "",
          "network": "eip155:8453",
          "scheme": "exact"
        },
        "providerName": "",
        "quality": {
          "l30DaysTotalCalls": "13",
          "l30DaysUniquePayers": "9"
        },
        "serviceName": "x402ai",
        "tags": [
          "embeddings",
          "vector-search",
          "rag",
          "semantic-search",
          "nlp"
        ],
        "url": "https://api.x402ai.dev/api/embed"
      },
      {
        "description": "Summarize a passage of text into a short, concise summary with no preamble (qwen3.5 2B model). Good for condensing articles, emails, logs or documents before passing them to another agent. POST JSON {\"input\": string}, up to 3000 characters; returns {summary, model, elapsed_ms}. Typically 5-15 s. Small model: may miss nuance in technical or long text. Text only.",
        "method": "POST",
        "parameters": [
          {
            "default": null,
            "description": "",
            "enumValues": [],
            "example": "A long passage of text to condense...",
            "group": "body",
            "name": "input",
            "required": false,
            "type": "string"
          }
        ],
        "pricing": {
          "amount": "0.02",
          "currency": "USDC",
          "maxAmount": "",
          "minAmount": "",
          "network": "eip155:8453",
          "scheme": "exact"
        },
        "providerName": "",
        "quality": {
          "l30DaysTotalCalls": "4",
          "l30DaysUniquePayers": "2"
        },
        "serviceName": "x402ai",
        "tags": [
          "summarization",
          "summarize",
          "text",
          "nlp",
          "llm"
        ],
        "url": "https://api.x402ai.dev/api/summarize"
      }
    ],
    "enriched": false,
    "iconUrl": "",
    "id": "api-x402ai-dev",
    "integrationType": "",
    "isNew": false,
    "name": "api.x402ai.dev",
    "networks": [
      "Base"
    ],
    "priceSummary": {
      "avgCostBasis": "exact",
      "avgCostPerTransaction": "0.023333",
      "currency": "USDC",
      "maxAmount": "0.04",
      "minAmount": "0.01"
    },
    "provider": "api.x402ai.dev",
    "providerUrl": "",
    "serviceName": "x402ai",
    "tags": [
      "question-answering",
      "qa",
      "llm",
      "general-knowledge",
      "ai",
      "embeddings",
      "vector-search",
      "rag",
      "semantic-search",
      "nlp",
      "summarization",
      "summarize",
      "text"
    ]
  },
  "source": "agentic_market",
  "summary": ""
}

What the leaf hashes

{"body":"959983546b5126084b941ac5380ef0b98a2db1a73a00905e724a3416dd53ef0d","id":1527,"kind":"listing","method":"baseline/1","observed_us":1793025254291448,"prev":null,"subject":"agentic_market:api-x402ai-dev","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. 0xac7dd0bc66731144149f5cecbdc12444a993e4db801922ce9d19b3dc9aa047d7
2. 0x53daa509a984489b63b6295a649ad2d257d4d868f988bc58b84eef5078da61c5
3. 0xbe9f27627b9c34a6e262cf238a41fb85dcdd742637d14933e75c9be41ddaab44
4. 0x0548ca76d7233e464319819e9d1b764a0c9375b591e0ec0532faf5ff103f482c
5. 0x9e51d95507a4dbd13350a4ca24461899a6464f2fb8487270c06888bbc0e8d9ef
6. 0xb956631c1b6fac88e364dca5778a34d04ba6e22d675b07c6a8473f637f5e455f
7. 0x3fa6dda7783ba8b354834f07d45c4f6dc169e0a3b73c0c03f05b20892c3b7704
8. 0xdcf751e1326fa9d7a3d180688a02bbffe81d87be6331ab06f33f5e90ce299f9a
9. 0xb534cbe0be78469c8f0a3d0670c9d16c3638abf08efcaab7785e2519e34b3eda
10. 0xc97abdede7c4060ef185e84128116a0ad0ab1d598f63d28fa5df0730f940fb58
11. 0x3777e64f7ac9f40ae7e4f13404a570afc2a739656a377469485865c026d1c99c
12. 0xb7fae69bb7bd717d54a83df961404a3e4de2a5cfbcfa013fd83a38627fe13f7e
13. 0x4700d6dfdb40e52e2ceb8ffe62c75f3f708d23452f828255fd003d795f5d9d66
14. 0x3b4dba7d874fc323b0a364140a9c60f37bf547fe671897653118a9873fe03420
15. 0x1a74ed3b3756b9cd946da49701bcec120ec88645013da99fa9eea60b39e1a570
16. 0x123ec8bee20ddc55223eeef5a4f4d6c4b6416515adbb911c56759f5cde56e452
17. 0xd0651cb9bc8155eb52b5247d506e74b8a935057dc190ba52091702ac25ed3a40
18. 0x9a9024edb5069d88a324facb310a5ce8e495214bbaa968f077bede437390194f
19. 0x9b9ce5b74b9bab5121612ef6b64920a8d453cbf311096a423eef9702747e868a

Day root

0xf43e8dcc3d451a4788b26be904c55e8c4c0fa75c9666796c51db38d37e2c0df8

Chained

0x702d5ac508f08b0d1accf36af25822d8e5660367494edd17a642fb61e158a57a

Published

On Arc Testnet, block 69251483: 0x495162f8936e19f0039918feebe6c307f327cd6bf8c37219620b1970041fa9ae