Evidence row 530499

What was observed

{
  "count": 7,
  "tools": [
    {
      "description": "Score a resume, optionally against a job posting: a 0-100 match score, the posting's keywords found and missing (matched literally, as an ATS search would), ATS format checks, the level fit, and the probability a recruiter would move it to interview.",
      "inputSchema": {
        "$schema": "https://json-schema.org/draft/2020-12/schema",
        "properties": {
          "job_description": {
            "description": "The job posting to match against. Omit for a general resume check.",
            "maxLength": 8000,
            "type": "string"
          },
          "resume": {
            "description": "The resume as plain text.",
            "maxLength": 12000,
            "minLength": 150,
            "type": "string"
          }
        },
        "required": [
          "resume"
        ],
        "type": "object"
      },
      "name": "check_resume"
    },
    {
      "description": "Which of two versions is stronger for a stated purpose. Asked twice with the order swapped and averaged, because the model favors the second option on close calls; if the two orders disagree the result is a tie.",
      "inputSchema": {
        "$schema": "https://json-schema.org/draft/2020-12/schema",
        "properties": {
          "context": {
            "description": "The surrounding text, such as the whole essay or the job posting.",
            "maxLength": 60000,
            "type": "string"
          },
          "question": {
            "description": "e.g. 'Which opening line would an admissions reader find more compelling?'",
            "maxLength": 1000,
            "minLength": 3,
            "type": "string"
          },
          "version_a": {
            "maxLength": 5000,
            "minLength": 1,
            "type": "string"
          },
          "version_b": {
            "maxLength": 5000,
            "minLength": 1,
            "type": "string"
          }
        },
        "required": [
          "question",
          "version_a",
          "version_b"
        ],
        "type": "object"
      },
      "name": "compare_versions"
    },
    {
      "description": "Grade one essay against a built-in rubric. kind \"essay\": six criteria and a letter grade, for class essays at middle school, high school or college level. kind \"common-app\": a Common App personal statement (pass the prompt number, 1-7). kind \"sat\": an SAT School Day essay, Reading/Analysis/Writing each 1-4 (pass the source passage to check quotations).",
      "inputSchema": {
        "$schema": "https://json-schema.org/draft/2020-12/schema",
        "properties": {
          "assignment": {
            "description": "kind \"essay\": the assignment prompt.",
            "maxLength": 2000,
            "type": "string"
          },
          "essay": {
            "description": "The essay text.",
            "maxLength": 20000,
            "minLength": 100,
            "type": "string"
          },
          "kind": {
            "default": "essay",
            "enum": [
              "essay",
              "common-app",
              "sat"
            ],
            "type": "string"
          },
          "level": {
            "description": "kind \"essay\" only. Default high school.",
            "enum": [
              "middle school",
              "high school",
              "college"
            ],
            "type": "string"
          },
          "passage": {
            "description": "kind \"sat\": the source passage.",
            "maxLength": 8000,
            "type": "string"
          },
          "prompt": {
            "description": "kind \"common-app\": which of the seven prompts. Default 7, topic of your choice.",
            "maximum": 7,
            "minimum": 1,
            "type": "integer"
          }
        },
        "required": [
          "essay"
        ],
        "type": "object"
      },
      "name": "grade_essay"
    },
    {
      "description": "Grade one or more submissions (up to 30, in parallel) against a rubric you supply: each criterion scored on a 3- to 6-point scale, summed per submission. Each submission is graded in its own call, so its score never depends on the others.",
      "inputSchema": {
        "$schema": "https://json-schema.org/draft/2020-12/schema",
        "properties": {
          "assignment": {
            "maxLength": 2000,
            "type": "string"
          },
          "criteria": {
            "description": "Rubric rows, e.g. { \"name\": \"Evidence\", \"description\": \"Supports the claim with specific evidence\" }.",
            "items": {
              "properties": {
                "description": {
                  "maxLength": 300,
                  "type": "string"
                },
                "name": {
                  "maxLength": 60,
                  "minLength": 1,
                  "type": "string"
                }
              },
              "required": [
                "name"
              ],
              "type": "object"
            },
            "maxItems": 8,
            "minItems": 1,
            "type": "array"
          },
          "points": {
            "default": 4,
            "maximum": 6,
            "minimum": 3,
            "type": "integer"
          },
          "submissions": {
            "items": {
              "properties": {
                "name": {
                  "maxLength": 80,
                  "type": "string"
                },
                "text": {
                  "maxLength": 20000,
                  "minLength": 100,
                  "type": "string"
                }
              },
              "required": [
                "text"
              ],
              "type": "object"
            },
            "maxItems": 30,
            "minItems": 1,
            "type": "array"
          }
        },
        "required": [
          "criteria",
          "submissions"
        ],
        "type": "object"
      },
      "name": "grade_with_rubric"
    },
    {
      "description": "Pick the option that best fits a text, with a probability for every option and a confidence. Options map an id to a description of when it applies.",
      "inputSchema": {
        "$schema": "https://json-schema.org/draft/2020-12/schema",
        "properties": {
          "options": {
            "additionalProperties": {
              "maxLength": 500,
              "minLength": 1,
              "type": "string"
            },
            "description": "e.g. { \"billing\": \"Payments, refunds, invoices\", \"technical\": \"Bugs and errors\" }",
            "propertyNames": {
              "maxLength": 60,
              "minLength": 1,
              "type": "string"
            },
            "type": "object"
          },
          "question": {
            "maxLength": 1000,
            "minLength": 3,
            "type": "string"
          },
          "text": {
            "maxLength": 60000,
            "minLength": 1,
            "type": "string"
          }
        },
        "required": [
          "text",
          "question",
          "options"
        ],
        "type": "object"
      },
      "name": "judge_choice"
    },
    {
      "description": "Place a text on an ordered scale you define (lowest level first) and get the nearest level, the exact position and a probability for each level.",
      "inputSchema": {
        "$schema": "https://json-schema.org/draft/2020-12/schema",
        "properties": {
          "levels": {
            "description": "Lowest first, e.g. [\"Off-topic\", \"Partly relevant\", \"Fully relevant\"].",
            "items": {
              "maxLength": 300,
              "minLength": 1,
              "type": "string"
            },
            "maxItems": 10,
            "minItems": 2,
            "type": "array"
          },
          "question": {
            "maxLength": 1000,
            "minLength": 3,
            "type": "string"
          },
          "text": {
            "maxLength": 60000,
            "minLength": 1,
            "type": "string"
          }
        },
        "required": [
          "text",
          "question",
          "levels"
        ],
        "type": "object"
      },
      "name": "judge_score"
    },
    {
      "description": "Ask any yes/no question about a text and get the probability that the answer is yes. Use for checks and gates, e.g. 'Does this reply answer the customer's question?'.",
      "inputSchema": {
        "$schema": "https://json-schema.org/draft/2020-12/schema",
        "properties": {
          "no_means": {
            "maxLength": 300,
            "type": "string"
          },
          "question": {
            "maxLength": 1000,
            "minLength": 3,
            "type": "string"
          },
          "text": {
            "description": "The text to judge.",
            "maxLength": 60000,
            "minLength": 1,
            "type": "string"
          },
          "yes_means": {
            "description": "What a yes looks like, if it helps to spell out.",
            "maxLength": 300,
            "type": "string"
          }
        },
        "required": [
          "text",
          "question"
        ],
        "type": "object"
      },
      "name": "judge_yes_no"
    }
  ]
}

What the leaf hashes

{"body":"8c40b51a605909f87a99a754bcdcca9ebe6c8189e3f24e16e4f8c336e150fc42","id":530499,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793126125884836,"prev":null,"subject":"81a129f8-2653-47b1-8737-062b71aca7e3","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. 0x4d0a1f1dd1a3f6b44d61dc2cbb22f19b0fbc5a816b37f71e463786813d0309dc
2. 0x9a36e4e45db609d97069d1ad35fb5fa0a8f16ad0548fd526b791573703d030d5
3. 0x0b205be98e381e93b47d608234b3281931f378f553f0efb2025aeab077d2c9a3
4. 0xa13cf342cf06bab3ad1b25ac1ed5880a6cb5dfeb0daa8f11731163f7a37fe2bc
5. 0x1794a47a529057c9d805f08b31e6634c32cf35615732292e25320a8bde612bdc
6. 0x5a77e1619b01733a72a1fd110b986f516e1b7a5a142a745555df02c0476d41a0
7. 0x801c56b1956f60ddaf7f13509181aceee0489436f97f28c825fd0decde2696ce
8. 0x0c665814fe9acf8a97ac1f6d8ce2fdc8617aecb092665c7cbd6d4344f7be6185
9. 0x3112a7b0b654103b064f00944b0c7a784a62cfd98513fc14ab83f50e2f58ccf6
10. 0x9305fa39c0bfbf15674949ab145ca0a40479400bedc3333826053de29a32e9ef
11. 0x699e1831216ceb5d0324397f8f4f58989765f950328c8adcbcb3a202d688993c
12. 0xf9b21ec258212225fc012a1ed6399d0ec608e930f4423d2badb8be79550861ef
13. 0x797da99476c7ebaa971607ae725e5e240b79de9e49d28859b94de107c850aaab
14. 0x9ea0c6a53f80a30b6f13671109f98a000cf98e581875129f4be4b57131d06364
15. 0xb78ea6a255dd06e2f402a1a733bca392fa6243920bcba95e8b80bdfc6ce5f553
16. 0x3ed50f053eca72dfd3a9d45a11935240bfe691e57835c367ddebe2cbc49efe9d
17. 0x0e01aa9525097570a6edaf32bfc959de57bf5c24317cf10c0716affea85ca60d
18. 0xa20d48798a34aba12eb9c7297722982d910f06c148f5e27ac59307422964a585
19. 0x9fc354c0ea3efc3f1b6548bb77ea902a50f2c9647647ea61592efce2bd795699

Day root

0xdd77e5e99da32c3f154180d63e3c3e6fe11e896a2c6896412ef6b5c4bcf7e795

Chained

0x23bb4dfd09f55c15ac3962f53578e02c6114d5bfd9bb451cf8794fb6e2817ef4

Published

On Arc Testnet, block 69414147: 0xb2ebd83aafeb765a0ce66e76aefb133ed06606c98038fd56191e2bcd1dcb77b4