Evidence row 565062

What was observed

{
  "count": 10,
  "tools": [
    {
      "description": "Average German dog tax (Hundesteuer, first dog per year) per Bundesland (federal state), aggregated over the covered largest cities — the data behind the Deutschlandkarte. Answers 'which German state has the highest/lowest dog tax'. Note: a mean over cities, not an official state rate (the tax is municipal).",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {},
        "type": "object"
      },
      "name": "hundesteuer_by_state"
    },
    {
      "description": "List German cities that changed their Hundesteuer (dog tax) rate in a given year — the fresh-news angle for the annual city comparison. Only 2026 is curated, and it is the default: 14 of the covered cities changed their rate, led by Köln (174 EUR), Lübeck (156 EUR), Lünen (156 EUR). Also returns outlook_2027: 5 cities that have announced or resolved an increase for 2027 but are NOT yet charging it — announced and in force are kept apart deliberately. Every entry checked individually against the municipal statute.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "year": {
            "default": 2026,
            "maximum": 2030,
            "minimum": 2020,
            "type": "integer"
          }
        },
        "type": "object"
      },
      "name": "hundesteuer_changes"
    },
    {
      "description": "Look up the German dog tax (Hundesteuer) for a city: annual rate for one or more dogs, listed-dog (Listenhund) surcharge, the city's pricing model, its rank among the largest cities, plus the official source and Stand. Rates verified against each municipal Satzung.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "city": {
            "description": "City name or slug, e.g. \"Köln\", \"muenchen\", \"Frankfurt\"",
            "type": "string"
          },
          "dogs": {
            "default": 1,
            "description": "Number of dogs (default 1)",
            "maximum": 10,
            "minimum": 1,
            "type": "integer"
          },
          "listed": {
            "default": false,
            "description": "Treat as a listed/dangerous-breed dog (Listenhund) if the city has a higher rate",
            "type": "boolean"
          }
        },
        "required": [
          "city"
        ],
        "type": "object"
      },
      "name": "hundesteuer_lookup"
    },
    {
      "description": "Ranking of German cities by Hundesteuer (first dog, per year): most expensive or cheapest, plus the national average across the covered cities.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "limit": {
            "default": 10,
            "description": "How many cities to return",
            "maximum": 100,
            "minimum": 1,
            "type": "integer"
          },
          "order": {
            "default": "expensive",
            "enum": [
              "expensive",
              "cheapest"
            ],
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "hundesteuer_ranking"
    },
    {
      "description": "List the available hand-verified German municipal tax/fee datasets (Hundesteuer, Zweitwohnungsteuer, Pfändung), their coverage, source sites and refresh cadence. Call this first to see what you can query.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {},
        "type": "object"
      },
      "name": "list_datasets"
    },
    {
      "description": "Compute the attachable portion of monthly net income under German §850c ZPO (Pfändung / wage garnishment), using the current official Pfändungsfreigrenzenbekanntmachung. Returns attachable amount, remaining amount, exempt base and the P-Konto base. Informational, not legal advice.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "dependents": {
            "default": 0,
            "description": "Number of maintenance-dependent persons (0-5)",
            "maximum": 5,
            "minimum": 0,
            "type": "integer"
          },
          "net_income_eur": {
            "description": "Monthly NET income in EUR",
            "minimum": 0,
            "type": "number"
          }
        },
        "required": [
          "net_income_eur"
        ],
        "type": "object"
      },
      "name": "pfaendung_calc"
    },
    {
      "description": "Average German second-home tax (Zweitwohnungsteuer) rate in percent per Bundesland (federal state), aggregated over the levying cities with a computable rate — the data behind the Deutschlandkarte. Answers 'which German state has the highest/lowest second-home tax'. Note: a mean over cities, not an official state rate (the tax is municipal).",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {},
        "type": "object"
      },
      "name": "zweitwohnungsteuer_by_state"
    },
    {
      "description": "List German cities that changed (raised or newly introduced) their Zweitwohnungsteuer in a given year — the fresh-news angle. Only 2026 is curated, and it is the default: 12 cities changed their rate, led by Potsdam (25 %), Borkum (22 %), Stuttgart (20 %). Every entry checked individually against the municipality's own statute.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "year": {
            "default": 2026,
            "maximum": 2030,
            "minimum": 2020,
            "type": "integer"
          }
        },
        "type": "object"
      },
      "name": "zweitwohnungsteuer_changes"
    },
    {
      "description": "Look up the German second-home tax (Zweitwohnungsteuer) for a city: whether the city levies it, the rate and its basis (net cold rent etc.), the rank among cities, official source and Stand. Optionally pass a monthly cold rent to get the annual tax. Returns state = keine_steuer | berechenbar | sondermodell.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "city": {
            "description": "City name or slug, e.g. \"Stuttgart\", \"muenchen\", \"Konstanz\"",
            "type": "string"
          },
          "monthly_rent": {
            "anyOf": [
              {
                "minimum": 0,
                "type": "number"
              },
              {
                "type": "null"
              }
            ],
            "default": null,
            "description": "Monthly cold rent (Kaltmiete) in EUR, to compute the annual tax (only for computable cities)"
          }
        },
        "required": [
          "city"
        ],
        "type": "object"
      },
      "name": "zweitwohnungsteuer_lookup"
    },
    {
      "description": "Ranking of German cities by Zweitwohnungsteuer rate: highest or lowest, plus the average, count with a computable rate, and count of cities with no second-home tax.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "limit": {
            "default": 10,
            "description": "How many cities to return",
            "maximum": 120,
            "minimum": 1,
            "type": "integer"
          },
          "order": {
            "default": "expensive",
            "enum": [
              "expensive",
              "cheapest"
            ],
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "zweitwohnungsteuer_ranking"
    }
  ]
}

What the leaf hashes

{"body":"049c9fb31db992db5338624fe3bc82f1ee706cb46ea32e5ba85c6ac28e27116f","id":565062,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793138000413848,"prev":null,"subject":"9564ebfb-f91d-46ac-b6bc-b07a0c8e8237","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. 0x612e090cbc2c7ca7a02fea0b0bd0fe1210f342d2e4eb95f87cae8b818b1cd5d5
2. 0x9ff19d2d6533b372f282ac1e93fe2e4b4b61933a259a22c3f555814cc4f4c703
3. 0x2e2042a3c98f6eaaf8e28ef1db5d536e2c6c10abbd285412e7974ad33db7e527
4. 0x94244178d4d5536101a734614153c81abd62b19dad9b268d4c88f7bc0871fa3c
5. 0xd2a67d5ed0e2a43fdb1be626142d26a30cfa504edb5f74ddb2b65edfa440aa0f
6. 0x638eacdad68a5708055045eb94e5d45d96817ef2b9ee7d72951ab0af708d6df4
7. 0xc168b51af7c2bedaeb9da35c298434ee6e479c38f3f8fd6c46f1816f47941355
8. 0xec284d624e71b8afdd2639afb46c9a28bc117265836b5b20def7c895f6662df7
9. 0x6eaa7373904a30786c6553f3ba1bbf02c6fb4bb2bc81e73a7fd6bed3bcf62885
10. 0xb8dca56c4c23574ede757cf5e83ed44a235623a9856f6e3fa8ac143787acedb6
11. 0xa81a051dde23e51110ae9919545b7ebf678423a44796b6dd73cba5f3e8134f16
12. 0x4fbbcb97bbe92a4202db4cfe9ed5ce98ec76cb76473d9a37a3775c708528409e
13. 0x38f17e73d675dd35d0dd4a9f0ebd22a3333bcd28f96e42d5dd126e08211ffc4a
14. 0x4277e02be0b5d91d78bc2247e37d402572474ba896c2e8f45765c8dc4e244d36
15. 0x6f00f0da417f4126951ba8ba9b7962c847e91f5c61364ad9ad47e5f979698a60
16. 0x23cf9bb4337ee8be7fcae368fd69d24c62c11fb45882127b4cd919bb96a19996
17. 0x0e01aa9525097570a6edaf32bfc959de57bf5c24317cf10c0716affea85ca60d
18. 0xa20d48798a34aba12eb9c7297722982d910f06c148f5e27ac59307422964a585
19. 0x9fc354c0ea3efc3f1b6548bb77ea902a50f2c9647647ea61592efce2bd795699

Day root

0xdd77e5e99da32c3f154180d63e3c3e6fe11e896a2c6896412ef6b5c4bcf7e795

Chained

0x23bb4dfd09f55c15ac3962f53578e02c6114d5bfd9bb451cf8794fb6e2817ef4

Published

On Arc Testnet, block 69414147: 0xb2ebd83aafeb765a0ce66e76aefb133ed06606c98038fd56191e2bcd1dcb77b4