Evidence row 290008

What was observed

{
  "count": 5,
  "tools": [
    {
      "description": "Shows one engine's input schema: required fields, units, alternative shapes, and a worked example. Engines reject bad input rather than guessing.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "engine": {
            "description": "Engine id.",
            "type": "string"
          }
        },
        "required": [
          "engine"
        ],
        "type": "object"
      },
      "name": "describe_engine"
    },
    {
      "description": "Returns the full method for one skill: when to use it, the steps, the quality bar, and how to run its engine if it has one.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "skill": {
            "description": "Skill slug.",
            "type": "string"
          }
        },
        "required": [
          "skill"
        ],
        "type": "object"
      },
      "name": "get_skill"
    },
    {
      "description": "Lists every AAJ marketing engine: its id, the question it answers, and its category. Engines cover unit economics, pipeline forecast, budget allocation, retention, A/B significance, SEO/GEO scoring, ad spend and pricing.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "category": {
            "description": "Optional filter. Words are matched against the engine's category, id and skill title (for example \"pricing\", \"retention\" or \"seo audit\"), then against its summary.",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "list_engines"
    },
    {
      "description": "Runs an AAJ engine and returns its verdict. Give `input` as an object of the engine's fields. Omit `input` to run the engine's built-in worked example. Engines are deterministic, offline, and validate their input — a wrong unit is reported as an error, not absorbed into a confident answer.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "engine": {
            "description": "Engine id.",
            "type": "string"
          },
          "input": {
            "description": "The engine's configuration object. Some engines also accept a named mode as a plain string (for example 'design' or 'readout'). Omit for the demo.",
            "type": [
              "object",
              "string"
            ]
          }
        },
        "required": [
          "engine"
        ],
        "type": "object"
      },
      "name": "run_engine"
    },
    {
      "description": "Finds AAJ marketing skills by the problem they solve — 'churn is rising', 'we're launching next month', 'not showing up in AI answers'. Returns matching methods and marks which have a runnable engine.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "limit": {
            "description": "Max results, default 8.",
            "maximum": 73,
            "minimum": 1,
            "type": "integer"
          },
          "query": {
            "description": "The problem, in plain words.",
            "type": "string"
          }
        },
        "required": [
          "query"
        ],
        "type": "object"
      },
      "name": "search_skills"
    }
  ]
}

What the leaf hashes

{"body":"a8d5da1d4b67a57d2b6406a10e876ac830b79202d818d5bd419eb9b2537f2fa8","id":290008,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793046897247811,"prev":null,"subject":"dcccbf6d-d79e-4f95-ad2c-fcb70989bb8a","subject_kind":"endpoint"}

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. 0xc32a306ab50530934744551fa05a06b7490f61a2bcf6ab5a0d21cd0670112d74
2. 0xe2b8e6c83a57ca5be6b5aaad20835b957e6e1bb659fb68eb13dc8f215157d621
3. 0x11548c3545ee1b59efc791f670a289606a99c44bd93c2a74c6916eecff442d3d
4. 0xbf60c10db5d185549703dffafa5af3d43dc86d0efe6fb0ee12a737c5ed923da4
5. 0x07ab482e45dd3cb026876703305efb8a60bedba2a9906671716cee8f0a0d139a
6. 0xc33f9e3c374fd408b67ce24d7808fec3d4e41739cf40d42a7d3af94d31f5478d
7. 0xfed59d7fb2398248bf8276e035bb722aaf89471ee4b4af69edf76a96945ecc14
8. 0x4210c0813cd19b511bc7ae88af46b2e84c8650513fda399addf7c86b62451a73
9. 0xaecea24081eddc492f2627d7a524e8dacb8752124e901c8341d96d99238ca95e
10. 0x00d960df50a5325e5736603a5a0d0a56310dedcefbef5371376f8262982d78ed
11. 0x7f4ae229fdca48d3ef8476aa02e4d171abb9d529ffe12fe147f9a22b16589b6a
12. 0x63002f2569d43725bbf2d04d90ec9e6cf925c96b6dda5e7e220ecfbdd9c2444d
13. 0x641fba1f23ec69d96721e34ace1926954d835b9614cb5eae215a069c056399b8
14. 0xdbe2e8dd65ea1248b2936612538f18268abd5cf27ebdab3737694571ad496004
15. 0x9f68b5e15459cb62b8c0cd4c124fa61c74147b4a5755a200fbecd21a581635d1
16. 0x123ec8bee20ddc55223eeef5a4f4d6c4b6416515adbb911c56759f5cde56e452
17. 0xd0651cb9bc8155eb52b5247d506e74b8a935057dc190ba52091702ac25ed3a40
18. 0x9a9024edb5069d88a324facb310a5ce8e495214bbaa968f077bede437390194f
19. 0x9b9ce5b74b9bab5121612ef6b64920a8d453cbf311096a423eef9702747e868a

Day root

0xf43e8dcc3d451a4788b26be904c55e8c4c0fa75c9666796c51db38d37e2c0df8

Chained

0x702d5ac508f08b0d1accf36af25822d8e5660367494edd17a642fb61e158a57a

Published

On Arc Testnet, block 69251483: 0x495162f8936e19f0039918feebe6c307f327cd6bf8c37219620b1970041fa9ae