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Evidence row 305768

Observed , by probe.mcp/1.

Kind
mcp.tools
About
endpoint 64199fd7-c7ad-454e-aefc-dd716cb37e93
Recorded
Previous row
None: the first of its kind about this subject
Body SHA-256
bce8c3d46b82e157ccc3100eaad85029b4f5a74821f984016683608be5dc76cb
Leaf
0xc107dbcf2a36a17d4bfb70d74a5ebaf3b8114d1520cd7a7c60d192a6bf74e489

What was observed

{
  "count": 8,
  "tools": [
    {
      "description": "What a school budget line was in each year, AT ONE STAGE. The stage argument is required and singular on purpose: `proposed`, `settled` and `actual` are three different documents about the same year, and a growth rate measured from an actual to a budget is partly growth and partly the step between them. That mistake put a special education escalator 1.5 points too high here and was invisible until somebody asked how the number was derived. Note also that a budget line is NET — what the town must raise after grants, fees and state aid — so a line can rise because a grant ended rather than because anything cost more.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "label": {
            "description": "Part of the line name, e.g. \"paraprofessional\"",
            "type": "string"
          },
          "stage": {
            "description": "One stage. Never compare across stages.",
            "enum": [
              "proposed",
              "settled",
              "actual"
            ],
            "type": "string"
          }
        },
        "required": [
          "label",
          "stage"
        ],
        "type": "object"
      },
      "name": "budget_history"
    },
    {
      "description": "Where a document came from: the publisher's URL, our copy, and its sha256 so a reader can check they have the same bytes. Use it to cite anything.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "name": {
            "description": "Part of a filename or path",
            "type": "string"
          }
        },
        "required": [
          "name"
        ],
        "type": "object"
      },
      "name": "document"
    },
    {
      "description": "Every dataset in the archive, with THE YEARS EACH COVERS, its row count and its size. Call this before answering from prose: it is how you find out whether the archive holds data for the year and subject you are being asked about. 49 datasets covering the town and school budgets, the town ledger, staff rosters, out-of-district placements, elections, and fifteen years of annual town reports.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {},
        "type": "object"
      },
      "name": "list_datasets"
    },
    {
      "description": "Any question the other tools do not cover, as one read-only SQL statement over the archive database. SELECT or WITH only; a LIMIT is imposed if you omit one. Call `read_first` before computing anything and `list_datasets` to find table names. A query estimated to read more than 250,000 rows is refused — narrow it with a WHERE, or ask for one table at a time.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "sql": {
            "description": "One SELECT statement.",
            "type": "string"
          }
        },
        "required": [
          "sql"
        ],
        "type": "object"
      },
      "name": "query"
    },
    {
      "description": "The grain of every table and the specific ways to get a confident wrong answer out of this data. Read this before computing anything. It states, among others, that a budget and an actual must never be combined in one calculation; that a budget line is NET of grants and fees and is not what a thing costs; and that no budget line is mapped to a ledger account, so budget-to-actual at line level cannot be answered from this data at all.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {},
        "type": "object"
      },
      "name": "read_first"
    },
    {
      "description": "Which of the 1,422 published town meeting documents contain a word — every board, 2025 onward. Returns the board, the date and a citable URL for each. AN EMPTY RESULT MEANS THE WORD IS NOT IN THE INDEXED DOCUMENTS, which is not the same as nobody having said it: the archive starts in January 2025. It matches words exactly, so plurals are separate terms — search \"jersey\" and \"jerseys\" both.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "board": {
            "description": "Optional board slug, e.g. school-committee",
            "type": "string"
          },
          "word": {
            "description": "A single word, lowercase. Not a phrase.",
            "type": "string"
          }
        },
        "required": [
          "word"
        ],
        "type": "object"
      },
      "name": "search_meetings"
    },
    {
      "description": "How many people the town PRINTED on a school staff roster, by year, school and kind of job. Uses our classification of the printed title, never the title itself, because the town has called the same job Tutor, Aide, Paraprofessional, Para, (para) and Sped Para across fifteen years. THIS IS A COUNT OF NAMES, NOT A STAFFING LEVEL: a roster carries no FTE, so a 0.4 music teacher and a full-timer are one row each, and it names no funding source, which is the question that usually matters. Grade appears only where the page happened to print it.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "category": {
            "description": "paraprofessional, teacher, administrator, counselor, nurse, psychologist, social_worker, speech_therapist, therapist, librarian, custodian, cafeteria, secretary, technology, specialist, coach",
            "type": "string"
          },
          "fy": {
            "description": "Fiscal year as four digits, e.g. 2022",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "staff"
    },
    {
      "description": "107 questions this archive can answer, each with the SQL that answers it. Every one is executed against the database on every build, so none of them is a claim. Start from the nearest one and edit it rather than writing a query from scratch.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {},
        "type": "object"
      },
      "name": "worked_examples"
    }
  ]
}

What the leaf hashes

{"body":"bce8c3d46b82e157ccc3100eaad85029b4f5a74821f984016683608be5dc76cb","id":305768,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793056630568550,"prev":null,"subject":"64199fd7-c7ad-454e-aefc-dd716cb37e93","subject_kind":"endpoint"}

Proof

Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of (296695 rows).

  1. 0xc107e851e5b03547b9e4f959c716da14c4bcd79a4b3e0d98d5400263d55816ff
  2. 0x03ebf1e6e8ef9e36017f82f12fb3fb5451cd5206248cac0bb9d5b647b0613096
  3. 0x7880574d86c98d809ca0850161ae9f68dbfa5d9c37998079ae7054d7d838d9b8
  4. 0x6715e3a93d6528d83ec57775ca5000ce62e8aca1bae15a3584575d077200edf4
  5. 0xd6d07a20bf4ce5db90d13bcb63aae9f79d4cce3694c6cb470d4b6815ceb82a59
  6. 0xf56402dacf3efb220e04e4dceccd28c41d633964f3907259292ad35c03b3e58c
  7. 0xfd9cae6c906c62e5baebceaad0056e2f946c92ac2b12272639ee40831b426ed4
  8. 0x43f40eceebb64f4e34da666ccaf4bf3b00f48c4a85fd4d6232975af57bcb854d
  9. 0xfd1f815d8fe2b986657ea7e224298e1d7c53081b1ea3cf652ba24d44cab8220a
  10. 0x7b149f9f7c296adb8af6cd00f57acc46b0fa098e83f5b758ee8289cf64e766c0
  11. 0xf4fdcce8aa5f97c7e98aeab4ad558743dfee0aa6d4d12415896a148aee663b17
  12. 0x111576180a2fecebcaf560e6b72ed8cefedaacb8c607539ece417b7465831f66
  13. 0x96eae331a78c1c9248bc58130ff83d31b884760a51fe7191de2a39105ae7c072
  14. 0xdbe2e8dd65ea1248b2936612538f18268abd5cf27ebdab3737694571ad496004
  15. 0x9f68b5e15459cb62b8c0cd4c124fa61c74147b4a5755a200fbecd21a581635d1
  16. 0x123ec8bee20ddc55223eeef5a4f4d6c4b6416515adbb911c56759f5cde56e452
  17. 0xd0651cb9bc8155eb52b5247d506e74b8a935057dc190ba52091702ac25ed3a40
  18. 0x9a9024edb5069d88a324facb310a5ce8e495214bbaa968f077bede437390194f
  19. 0x9b9ce5b74b9bab5121612ef6b64920a8d453cbf311096a423eef9702747e868a
Day root
0xf43e8dcc3d451a4788b26be904c55e8c4c0fa75c9666796c51db38d37e2c0df8
Chained
0x702d5ac508f08b0d1accf36af25822d8e5660367494edd17a642fb61e158a57a
Published
On Arc Testnet, block 69251483: 0x495162f8936e19f0039918feebe6c307f327cd6bf8c37219620b1970041fa9ae

How to check it · This row as JSON