Evidence row 561583

What was observed

{
  "count": 5,
  "tools": [
    {
      "description": "Which podcasts a brand advertises on. Returns the shows where that brand's ad reads were detected, newest first, with the exact total even when the list itself is truncated for the plan. Accepts a brand name, slug or domain (a domain is the most reliable). Returns candidate brands when the name is ambiguous.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "brand": {
            "description": "Brand name, slug or domain, e.g. \"Squarespace\" or \"squarespace.com\".",
            "type": "string"
          }
        },
        "required": [
          "brand"
        ],
        "type": "object"
      },
      "name": "get_brand_podcasts"
    },
    {
      "description": "Which advertiser categories are buying the most podcast ads right now, by ad reads detected, with the number of brands and shows behind each. Aggregate only — it does not list the brands in a category.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "days": {
            "description": "Lookback window in days. Defaults to 30.",
            "enum": [
              30,
              90,
              365
            ],
            "type": "integer"
          }
        },
        "type": "object"
      },
      "name": "get_busiest_categories"
    },
    {
      "description": "How much of podcasting this dataset actually covers: shows indexed, episodes transcribed, and the real number of brands and shows with detected ad reads. Call this before stating any sponsor finding as complete, and to explain why a show or brand might be missing.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {},
        "type": "object"
      },
      "name": "get_coverage_info"
    },
    {
      "description": "Who sponsors a given podcast. Returns every brand whose ad read was detected in that show's transcribed episodes, with how many reads, whether they were host-read or network-inserted, and when they were first and last heard. Accepts a show title, a trackpodcasts.com slug or a URL. If the title is ambiguous it returns candidate shows to choose from instead of guessing. Detected ad reads only — brands that were merely mentioned are not included.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "show": {
            "description": "Podcast title, slug or trackpodcasts.com URL, e.g. \"The Glenn Beck Program\".",
            "type": "string"
          }
        },
        "required": [
          "show"
        ],
        "type": "object"
      },
      "name": "get_show_sponsors"
    },
    {
      "description": "How a brand’s podcast advertising has moved month by month: shows reached, ad reads detected and organic mentions, for up to 36 months. Use this for trend questions (\"is this brand spending more?\", \"when did they start?\"). Months with no detections are returned as zero, which means nothing was detected rather than that the brand stopped.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "brand": {
            "description": "Brand name, slug or domain.",
            "type": "string"
          },
          "months": {
            "description": "Months of history to return. Defaults to 12.",
            "maximum": 36,
            "minimum": 1,
            "type": "integer"
          }
        },
        "required": [
          "brand"
        ],
        "type": "object"
      },
      "name": "get_sponsor_activity_summary"
    }
  ]
}

What the leaf hashes

{"body":"064f802843771e59a5c1d8236c1b6e202e702c5e97fb0ad7c318a253743e341f","id":561583,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793137194728648,"prev":null,"subject":"f9e5a4f5-4b5b-4646-a69d-6ab92b4681e1","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. 0xa3918d55b8437ae9a110184d110db83979b08fb3ec7a109e8af38bc71c75c766
2. 0x4edd5bcfbb68c04c2296f8a051dcdea67362eea01a8c560c434c380363a166bc
3. 0xe79739053dc1e8c646218d63f13ca2996c9104cab431b26cb3c48f294d4af278
4. 0x7a3d96fad1152226b1c2aaa73c7c0955f6bacb99552f422a9ca555e8023ae84f
5. 0xe3734ba285c38d65a0a8ecf2069ac1e49c48e9058a31a64a1752162594601277
6. 0x97da0bf73a0b1be4532b2ca1caafce946c0e4f6fb25e0f8aa51f6829050d8b6c
7. 0xfb2920f0a5e73e286bbaad5f885e82f8db56686453e740e9f28904cd67ad1519
8. 0x4b81737ffc971521b0eef5ce5c6978228746e7e6d666c8422cf08ed01eebd734
9. 0x0ce6111c24ab48de4e2530e2515b06cf0191fdc5a18459f7a2a6cae0775fb11e
10. 0xa0ea68059b84d3e8082a97b6f66d61d00092b368cef47b86fa4b782fde336acf
11. 0xd9929b92c66c9433d68fc7d48eddf234ae765144f98d397c91dd32e9124ee876
12. 0x0c9efc71bd73a056aab018d34b600797c2287eaa0df0398c8404046e9420d684
13. 0x87816aee66e8f6e0f1e55ea83733bb58cf9612d36c45fd5b7fc5d6f4484b78fd
14. 0x0644f7e2a4b5bf9b66f185cc3fbb766d456ad94490183852f4c6db5855114cc5
15. 0xa3fff4662cd48659f5bafd0612931759a90e53a7b4209ed8f26f6594a07bb547
16. 0x64c405a28e8819716221eb2529fe4ce277ab08025e17e685cbd5ece75ceb75c7
17. 0xf30fddbf4811226c58e8f0daf36fddd79fc5f1356b592bb1d99a8061ddbabe66
18. 0x2bf8151e5f157dd183b9de6fa00469551932a7a6e3f33a694895000ac9061197
19. 0x9fc354c0ea3efc3f1b6548bb77ea902a50f2c9647647ea61592efce2bd795699

Day root

0xdd77e5e99da32c3f154180d63e3c3e6fe11e896a2c6896412ef6b5c4bcf7e795

Chained

0x23bb4dfd09f55c15ac3962f53578e02c6114d5bfd9bb451cf8794fb6e2817ef4

Published

On Arc Testnet, block 69414147: 0xb2ebd83aafeb765a0ce66e76aefb133ed06606c98038fd56191e2bcd1dcb77b4