Evidence row 566933

What was observed

{
  "count": 6,
  "tools": [
    {
      "description": "判斷一句搜尋或提問屬於資訊探索、商業比較、技術除錯或行動指引哪種意圖，並給出建議答案結構、結構化資料類型與本站相關內容。",
      "inputSchema": {
        "properties": {
          "q": {
            "type": "string"
          }
        },
        "required": [
          "q"
        ],
        "type": "object"
      },
      "name": "classify_search_intent"
    },
    {
      "description": "比較兩個 AI 概念差在哪（如 RAG vs 微調、MCP vs API、SEO vs GEO），回傳結論、比較表與各自適用情境。可給 id，或 a、b 兩個名詞。",
      "inputSchema": {
        "properties": {
          "a": {
            "type": "string"
          },
          "b": {
            "type": "string"
          },
          "id": {
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "compare_concepts"
    },
    {
      "description": "用白話解釋 AI 或科技名詞（如 MCP、RAG、AI 代理人、幻覺、GEO、x402），回傳定義、運作方式、例子、常見誤解、FAQ 與原始來源。可用中文、英文或別名。",
      "inputSchema": {
        "properties": {
          "term": {
            "description": "名詞或 id，例如 MCP、檢索增強生成、ai-agent",
            "type": "string"
          }
        },
        "required": [
          "term"
        ],
        "type": "object"
      },
      "name": "explain_term"
    },
    {
      "description": "取得 AI 實作教學（建立 MCP 伺服器、llms.txt、FAQPage JSON-LD、robots.txt 封鎖 AI 訓練、x402 流程、計算 Token），含需求、步驟、程式碼與常見錯誤。",
      "inputSchema": {
        "properties": {
          "id": {
            "type": "string"
          },
          "q": {
            "description": "關鍵字，例如 MCP、llms.txt",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "get_howto"
    },
    {
      "description": "列出所有名詞（可依分類篩選）、概念比較與實作教學。",
      "inputSchema": {
        "properties": {
          "category": {
            "enum": [
              "基礎概念",
              "模型技術",
              "協定與標準",
              "應用與產品",
              "搜尋與行銷",
              "硬體"
            ],
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "list_topics"
    },
    {
      "description": "模糊搜尋本站的 AI 名詞、概念比較與實作教學。",
      "inputSchema": {
        "properties": {
          "limit": {
            "maximum": 20,
            "minimum": 1,
            "type": "integer"
          },
          "q": {
            "type": "string"
          }
        },
        "required": [
          "q"
        ],
        "type": "object"
      },
      "name": "search_glossary"
    }
  ]
}

What the leaf hashes

{"body":"a1300ed798e1cba3c10e9fa0e9d4c22454b27f585b38ff15f90d3dda54b4fc89","id":566933,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793138570058723,"prev":null,"subject":"6e2a9cc8-ca06-4484-841f-74fb45a023e0","subject_kind":"endpoint"}

Proof

Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of 2026-10-27 (273461 rows).

1. 0xfbde98f6fa7cd418264dd749f0d7b5558559523e8388177fd8c6aeb8ca259c0f
2. 0xfa17ffbf138df126b74d091385e96d345ea33a204430c0d7652779bb0bb0344b
3. 0x106fdff1b5d9fa25d1feee2fb6de1aba4698b1bac74d0318e13d7396d6625b3f
4. 0x82cf07c607172b7c1aa88016bcc2dace892e6009e95f716015ba9d533200e594
5. 0xc1b6286a1905c6ed91c7b80393449870845aad71f54df915074fc6b4def6852f
6. 0x6bf45af2cb02f7751973af742e8c2d15e812b1280e51c0673d140ced95a89b94
7. 0xbe729ad608b88ddb5b7482b5a5664fcd00337597775544cd24994aa2d84be1f3
8. 0x76b9601fcb366efe5164956a0e7cc854cf1f1126cb383d81be1148be78c0904e
9. 0x1a7020eae06cd4dfe96bc33cc7699a58078d843fa108b3f80aae0bcd04ed7260
10. 0x4dcf6d8a4f1e6bb73ab94022ec0e317eea2cf5fc629f68590944c9b051494f00
11. 0xcefdb19b0b337beca00b9fd7a48a1f5a4460d9248ad35867cf96e844d9dc0897
12. 0xf4dd076e6efbd5ea0ecb7bbba37a353ed1d340e9d41fd6bbc5f05edbb05ca1cf
13. 0xf24b37f8ac293f5328e3e6b28cf868989fe99debf025c153c0d9a1698e846e25
14. 0x94d3785ce9330e4580bccada5459380aa2aac76a0bf11354d1353b375afc17d2
15. 0xb5b652bba4a5afca56c21031d89b1c06361563aaf54ccc8541c296ceeb2b66fa

Day root

0xdd77e5e99da32c3f154180d63e3c3e6fe11e896a2c6896412ef6b5c4bcf7e795

Chained

0x23bb4dfd09f55c15ac3962f53578e02c6114d5bfd9bb451cf8794fb6e2817ef4

Published

On Arc Testnet, block 69414147: 0xb2ebd83aafeb765a0ce66e76aefb133ed06606c98038fd56191e2bcd1dcb77b4