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Evidence row 568268

Observed , by probe.mcp/1.

Kind
mcp.tools
About
endpoint 47f316a7-0bcb-47a4-aa04-7ce84ee6e2b3
Recorded
Previous row
None: the first of its kind about this subject
Body SHA-256
07bd6730f8313608d070d7a601ff1bf4620bf1b90da335d97d550cf63865d3da
Leaf
0x380c8978eef2723d256244eb303786ed10397e5e6c80adf0760ade73dd839f6f

What was observed

{
  "count": 3,
  "tools": [
    {
      "description": "What recipes have people and Gusto shared on What's Cooking? Inputs (all optional): query (matched against titles, tags and ingredients), author (e.g. \"Gusto\"), limit (default 5, max 20). Returns short picks; call get_explore_recipe with an id for the full recipe. Example: {\"query\":\"chicken\",\"author\":\"Gusto\"}",
      "inputSchema": {
        "properties": {
          "author": {
            "description": "Only recipes by this author, e.g. \"Gusto\".",
            "type": "string"
          },
          "limit": {
            "description": "How many picks. Default 5.",
            "maximum": 20,
            "minimum": 1,
            "type": "integer"
          },
          "query": {
            "description": "A dish, ingredient or tag, e.g. \"chicken\" or \"vegan\".",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "browse_explore"
    },
    {
      "description": "What's the full recipe for this Explore pick? Inputs: id (from browse_explore, required), servings (optional; quantities are scaled when it differs from the original). Example: {\"id\":\"<id from browse_explore>\",\"servings\":4}",
      "inputSchema": {
        "properties": {
          "id": {
            "description": "The recipe id from browse_explore.",
            "type": "string"
          },
          "servings": {
            "description": "Scale to this many servings.",
            "maximum": 48,
            "minimum": 1,
            "type": "integer"
          }
        },
        "required": [
          "id"
        ],
        "type": "object"
      },
      "name": "get_explore_recipe"
    },
    {
      "description": "What should I cook tonight with what I have? Gusto, What's Cooking's chef, decides one complete dinner and returns the full recipe, steps, and a list of what to buy. Inputs (all optional): have (what is already in the kitchen, a list or a sentence), cuisine, servings (default 2, max 24), diet (hard constraints such as vegetarian, vegan, gluten-free), max_minutes, mood, skill. Salt, pepper, oil and water are assumed on hand. Call again with different inputs for another idea. Example: {\"have\":[\"chicken\"],\"cuisine\":\"Mexican\"}",
      "inputSchema": {
        "properties": {
          "cuisine": {
            "description": "e.g. Mexican, Thai, Italian.",
            "type": "string"
          },
          "diet": {
            "description": "Hard dietary constraints, e.g. [\"vegetarian\"].",
            "items": {
              "type": "string"
            },
            "type": "array"
          },
          "have": {
            "anyOf": [
              {
                "items": {
                  "type": "string"
                },
                "type": "array"
              },
              {
                "type": "string"
              }
            ],
            "description": "Ingredients already on hand, e.g. [\"chicken\",\"rice\"] or \"chicken, rice and an onion\"."
          },
          "max_minutes": {
            "description": "Total time limit in minutes.",
            "minimum": 5,
            "type": "integer"
          },
          "mood": {
            "description": "e.g. cozy, light, celebratory.",
            "type": "string"
          },
          "servings": {
            "description": "How many people. Default 2.",
            "maximum": 24,
            "minimum": 1,
            "type": "integer"
          },
          "skill": {
            "description": "e.g. beginner, confident.",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "whats_for_dinner"
    }
  ]
}

What the leaf hashes

{"body":"07bd6730f8313608d070d7a601ff1bf4620bf1b90da335d97d550cf63865d3da","id":568268,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793138969090347,"prev":null,"subject":"47f316a7-0bcb-47a4-aa04-7ce84ee6e2b3","subject_kind":"endpoint"}

Proof

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

  1. 0x380c978e639f836a6fb507d51bb6dd6abe49cefcb5b42b5b3bc172f3a8aef0d8
  2. 0x59748da5b7fc3c5f707e572f7253306476d3a14597bdbf5a7621b68e3feb605e
  3. 0xc88e25f7eea4b16515d60a440e7d1be7fa56b3c8e0855447397e3842e856e19e
  4. 0x085b2a5d0aa9a4b69be4860d7b84c4c1506f5a1293eeda4b1e8536795c662b24
  5. 0xca271f7227cb847ee9a84b925457deef1adb5f0871a4602aee0cd71bfa9a277e
  6. 0x48abbf3dc702d343c27440f44376b4705b735a5eb76d4fb6a6ee49d7e4c552f3
  7. 0x023f13b17f022355087f4fcd4bfd319555e57ee8cc2682c465b21221655a426c
  8. 0x29dbe9aed5e6e7f3dd1fb7a47dfbbeabf3ec6e433069e950436a17ce0aa5809d
  9. 0xea09a0aaa8b4b2810549a67ea871f60fc055056f5f18a5fbdb4ae8323513321a
  10. 0x4d02885c426a5643d6eaa02b71a8ac16cd2cbc5c1e818b230f8d8610157cba05
  11. 0xa68b83bee31b674e2a75c182ac7153fa7260e48329b079cb30f4c3ff78a7ebff
  12. 0x5ad46fa78d79ba6d76c322cad1bc48cbf0c26dc875ba94214d44c9d3c0b36673
  13. 0x5a6a2d80130a2a2e783e8f8096057d594b53c7bc148344100f2c40afa809745f
  14. 0x42784d9809d120654630ee1b254a1dd90a2bbd3024aa180f1a59bbf53e9316e4
  15. 0x8360ee1105e4d9f9312067cbbfd47c69c5948665ae582b9684a580c8f4e199e1
  16. 0x52efa60e0c3d8525486d2310eb3b6b566c9677c64fd1f819edb072cf101bcbdb
  17. 0x22c1fb9487ee0b9732fa017a0cc321eb27a60c08450d112f755089796e12cb1c
  18. 0xa20d48798a34aba12eb9c7297722982d910f06c148f5e27ac59307422964a585
  19. 0x9fc354c0ea3efc3f1b6548bb77ea902a50f2c9647647ea61592efce2bd795699
Day root
0xdd77e5e99da32c3f154180d63e3c3e6fe11e896a2c6896412ef6b5c4bcf7e795
Chained
0x23bb4dfd09f55c15ac3962f53578e02c6114d5bfd9bb451cf8794fb6e2817ef4
Published
On Arc Testnet, block 69414147: 0xb2ebd83aafeb765a0ce66e76aefb133ed06606c98038fd56191e2bcd1dcb77b4

How to check it · This row as JSON