Evidence row 308259

What was observed

{
  "count": 10,
  "tools": [
    {
      "description": "The full list of classification values used for eligibility matching, with what each means. Read this when you do not know what to put into benefits_match. / 자격 판정에 쓰는 분류 값의 전체 목록과 뜻.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {},
        "type": "object"
      },
      "name": "benefits_codebook"
    },
    {
      "description": "See how to apply for one benefit programme: what it provides, the application deadline, required documents, contact point and the law it rests on. Use the id returned by benefits_match. / 지원내용·신청기한·구비서류·문의처·근거법령을 봅니다.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "serviceId": {
            "description": "benefits_match 결과의 서비스ID",
            "type": "string"
          }
        },
        "required": [
          "serviceId"
        ],
        "type": "object"
      },
      "name": "benefits_detail"
    },
    {
      "description": "Find Korean government benefit programmes a person may be eligible for. Filters all 10,956 original records of the Ministry of the Interior and Safety Bojogeum24 registry by age, income bracket, household type and personal traits. A programme that does not state a condition is treated as UNRESTRICTED, not as excluded — so the fewer conditions you give, the more results you get. WARNING: the final entitlement decision belongs to the administering agency. This is a candidate list. / 보조금24 원본 10,956건에서 자격 조건으로 걸러 줍니다. 최종 수급 여부는 소관 기관이 정합니다.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "age": {
            "description": "Age in years. Omit to apply no age condition. / 나이(만). 생략하면 조건을 걸지 않습니다",
            "maximum": 130,
            "minimum": 0,
            "type": "integer"
          },
          "gender": {
            "description": "Gender (optional). / 성별. 생략 가능",
            "enum": [
              "남성",
              "여성"
            ],
            "type": "string"
          },
          "household": {
            "description": "Household types (multiple allowed). / 가구 유형(복수 가능)",
            "items": {
              "enum": [
                "다자녀가구",
                "해당사항없음",
                "신규전입",
                "무주택세대",
                "확대가족",
                "북한이탈주민",
                "다문화가족",
                "1인가구",
                "한부모가정/조손가정"
              ],
              "type": "string"
            },
            "type": "array"
          },
          "income": {
            "description": "Household median-income bracket. OMIT it if you do not know — guessing drops programmes that would have matched. / 모르면 생략하십시오. 찍으면 맞는 제도가 빠집니다",
            "enum": [
              "중위소득 51~75%",
              "중위소득 0~50%",
              "중위소득 101~200%",
              "중위소득 76~100%",
              "중위소득 200% 초과"
            ],
            "type": "string"
          },
          "limit": {
            "description": "Max records (default 20). / 최대 건수(기본 20)",
            "maximum": 50,
            "minimum": 1,
            "type": "integer"
          },
          "offset": {
            "description": "How many to skip (pagination). / 건너뛸 건수(페이지네이션)",
            "minimum": 0,
            "type": "integer"
          },
          "traits": {
            "description": "Personal traits (multiple allowed): life stage, occupation, school level, health. / 대상 특성(복수 가능)",
            "items": {
              "enum": [
                "예비부모/난임",
                "출산/입양",
                "임산부",
                "질병/질환자",
                "국가보훈대상자",
                "장애인",
                "대학생/대학원생",
                "해당사항없음",
                "구직자/실업자",
                "근로자/직장인",
                "중학생",
                "초등학생",
                "고등학생",
                "어업인",
                "농업인",
                "임업인",
                "축산업인"
              ],
              "type": "string"
            },
            "type": "array"
          }
        },
        "type": "object"
      },
      "name": "benefits_match"
    },
    {
      "description": "Search-demand ranking. It is an index relative to an anchor (libraries), NOT an absolute search volume. Use it to compare what people look for more, for market or topic research. / 검색 수요 순위. 앵커 대비 상대 지수이며 절대 검색량이 아닙니다. 시장·주제 조사에서 무엇을 더 많이 찾는지 비교할 때 씁니다.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "heldOnly": {
            "default": false,
            "description": "Keep only topics we actually hold data for. / 우리가 실제로 자료를 가진 주제만 추립니다",
            "type": "boolean"
          },
          "limit": {
            "default": 30,
            "description": "Max records (default 30, max 500). / 최대 건수",
            "type": "integer"
          }
        },
        "type": "object"
      },
      "name": "demand_rank"
    },
    {
      "description": "The datasets we have actually loaded, with record counts. Check what we can answer from. / 실제로 적재해 둔 자료 목록과 건수입니다. 무엇으로 답할 수 있는지 확인할 때 씁니다.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "query": {
            "description": "Part of a dataset name (optional). Empty means the full list. / 자료 이름 일부(선택)",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "list_datasets"
    },
    {
      "description": "Korean districts where several kinds of data overlap. Check here first to see which regions we can actually answer about. / 자료가 여러 종류 겹쳐 있는 시군구 목록입니다. 어느 지역에 대해 답할 수 있는지 먼저 확인할 때 씁니다.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "minAxes": {
            "default": 2,
            "description": "Minimum number of overlapping dataset kinds (default 2). / 최소 자료 종류 수",
            "type": "integer"
          }
        },
        "type": "object"
      },
      "name": "list_regions"
    },
    {
      "description": "See at a glance what kinds of data we hold for one Korean city or district, and how many records of each. Good as a first look before planning a trip or a site survey. Returns counts per dataset kind, so you can then drill in with search_data. / 한 시군구에 어떤 자료가 몇 건씩 있는지 한눈에 봅니다. 여행 계획이나 현장 조사 전에 먼저 훑어볼 때 씁니다. 자세한 레코드는 search_data 로 이어서 찾습니다.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "sido": {
            "description": "Province or metropolitan city, e.g. Jeju. / 시도",
            "type": "string"
          },
          "sigungu": {
            "description": "City or district (optional), e.g. Jeju-si. / 시군구 (선택)",
            "type": "string"
          }
        },
        "required": [
          "sido"
        ],
        "type": "object"
      },
      "name": "region_overview"
    },
    {
      "description": "Search the entire data.go.kr catalogue — INCLUDING datasets we have not loaded yet. Use it when search_data comes back empty, to find out whether such data exists at all and where to get it. / 공공데이터포털 대장 전체 검색. 아직 적재하지 않은 자료도 나옵니다. search_data 결과가 비었을 때, 그런 자료가 있기는 한지와 어디서 받는지 확인할 때 씁니다.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "limit": {
            "default": 20,
            "description": "Max records (default 20, max 200). / 최대 건수",
            "type": "integer"
          },
          "query": {
            "description": "Text to match against dataset names. / 자료 이름으로 찾을 말",
            "type": "string"
          },
          "type": {
            "description": "API | FILE | LINKED | STD (optional) / 자료 유형(선택)",
            "type": "string"
          }
        },
        "required": [
          "query"
        ],
        "type": "object"
      },
      "name": "search_catalog"
    },
    {
      "description": "Find Korean public-data records by region and topic. Examples: Gangneung libraries, Busan Jung-gu parking, Jeju tourism. A region word is read as an administrative area (abbreviations work); the rest is matched against record content and dataset names. The response echoes exactly how it was read in `interpreted`. Use it for what-is-where questions. / 지역과 주제로 공공데이터 레코드를 찾습니다. 예: 강릉 도서관 · 부산 중구 주차장 · 제주 관광. 「어디에 무엇이 있나」를 물을 때 씁니다. 해석 결과는 interpreted 에 밝힙니다.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "limit": {
            "default": 20,
            "description": "Max records (default 20, max 200). / 최대 건수",
            "type": "integer"
          },
          "query": {
            "description": "What to find. Region plus topic works best, e.g. Suwon library. / 찾을 말. 지역 + 주제 형태를 권장합니다.",
            "type": "string"
          }
        },
        "required": [
          "query"
        ],
        "type": "object"
      },
      "name": "search_data"
    },
    {
      "description": "Current nationwide Korean temperature, humidity and wind, plus weather warnings that are IN EFFECT RIGHT NOW. Based on the KMA ultra-short-term observation. These are observations, not a forecast, so it cannot answer about tomorrow. / 기상청 초단기실황 + 현재 발효 중인 특보. 예보가 아니라 관측값입니다. 지금 날씨·특보를 물을 때 씁니다(내일 날씨는 답하지 못합니다).",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {},
        "type": "object"
      },
      "name": "weather_now"
    }
  ]
}

What the leaf hashes

{"body":"456f33efde09093a97e2a4061bda504799e0ebe4875f08b24d09434638fc55b5","id":308259,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793058144697924,"prev":null,"subject":"772af8fa-674c-428e-ada8-c185172e2f51","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. 0x346393eef037b2dbd36f826d88da2759d87da0dcf5dc059c365d86f4f6f729a5
2. 0xa5c8c41bfe79876b3501c3af4c5367aeaa54054ab21ced9e05b1af288dd37fa4
3. 0xb40f5fc589b3b1f7788c362db9ae8b92eb65e623ef4137405b77396a8335139a
4. 0x70f32bad777b45c130b309dd1579474417009725f3c694d63047d6b3e1a3a579
5. 0x18799aa770f06cd024ec117b910faf94c002438e612da99d38cbda792acd825f
6. 0x81574e03c027ddcaba48a9145b3d73b8a877298915186f26ae227f6fd06eefa7
7. 0x6328370d6cc2251aece64143d65177d801834ea05c0111a77b525c2e11b6e12e
8. 0x8f8835154cab9381946b7dd51f7c57ec9596fe5dd4e795293507847a4c8dbd56
9. 0xd71f5a25f0d5b218cfeb434ccd6ff02215b58aaa777de94e58c83317ba247693
10. 0x852ba002507b16449e45904851c68e7f0b59aa6069ac1ae74dc557389e7c7646
11. 0x5b8798d4cefad64becd1c03dfc4c9f7111db423ab06ea3f8878316222a2b26de
12. 0xe57be1a98d96d75db9e9d2122794eabebfd735dea66e9d16ca63347243b3d483
13. 0x08de74b7fb265ddb83e4c673da8a94e5f71829b2e6e7464c71c5138e450f2217
14. 0x4338355a835617a26aa0bfcc971e84eb030d84e2aa840e3c8af958921dd080c7
15. 0x610738e0c43687aded83c613c73de8b5226c73c375858a167436461c522ea213
16. 0x06d71bfa7d8b41d62c8836efc2c601e1cc3772d9453596b2ae4950887f3310ca
17. 0x8c756542e482157df0c36464d75c937b845e4423dbbcfad08f0cf8d5a16b9a13
18. 0x20704208aa6923d6b2450ef74ede87a6e0265d46447926038fe9506e9e154b2d
19. 0x9b9ce5b74b9bab5121612ef6b64920a8d453cbf311096a423eef9702747e868a

Day root

0xf43e8dcc3d451a4788b26be904c55e8c4c0fa75c9666796c51db38d37e2c0df8

Chained

0x702d5ac508f08b0d1accf36af25822d8e5660367494edd17a642fb61e158a57a

Published

On Arc Testnet, block 69251483: 0x495162f8936e19f0039918feebe6c307f327cd6bf8c37219620b1970041fa9ae