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Evidence row 275743

Observed , by probe.mcp/1.

Kind
mcp.tools
About
endpoint 605b7c48-ae8d-4b4c-acda-ade9ca01a9bd
Recorded
Previous row
None: the first of its kind about this subject
Body SHA-256
d128c1ecedc405a3ed0329b62f1a03fcb996e776f609fc292ba9e02614c825da
Leaf
0x745a2ad4170ed21697e339707deac9008daf9378071e9ff1fbe2ed46143519dc

What was observed

{
  "count": 19,
  "tools": [
    {
      "description": "Return the published cross-source reconciliation group for a dataset name or id, including per-member counts, dates, statuses, tolerances, and contextual deltas. A discrepancy requires human review and does not prove either source is wrong. Use it to compare a dataset with its published cross-source group; do not use it for provenance or evidence receipts—use get_provenance or get_evidence instead. It reads precomputed reconciliation data, and single_source means no group contains the resolved dataset; DataPulse is read-only, requires no API key, and the edge limits clients to roughly one request per second with a small burst, so pace or retry.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "dataset_name": {
            "description": "Stable dataset slug or exact display name to resolve, e.g. 'interestrates' or 'Monthly Interest Rates'; use search_datasets to discover valid values.",
            "examples": [
              "interestrates",
              "Monthly Interest Rates"
            ],
            "minLength": 1,
            "type": "string"
          }
        },
        "required": [
          "dataset_name"
        ],
        "type": "object"
      },
      "name": "check_reconciliation"
    },
    {
      "description": "Return datasets flagged by the latest published anomaly detection (anomalies), ranked by how far the observed update interval exceeds its threshold. Optionally require a minimum publish-reliability grade; includes pipeline-computed anomaly and reliability evidence so agents do not recompute it. Use it for unusual update intervals; do not use it for worsening freshness, recovery, reliability grades, or structural drift—use find_deteriorating, find_recovering, find_unreliable, or find_schema_drift instead. It reads precomputed anomaly data, so an empty result means no published row survives the selected filters; DataPulse is read-only, requires no API key, and the edge limits clients to roughly one request per second with a small burst, so pace or retry.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "limit": {
            "default": 50,
            "description": "Maximum highest-ranked anomalies to return, e.g. 50; omit it to use 50 without changing the ranking.",
            "examples": [
              10,
              50
            ],
            "maximum": 200,
            "minimum": 1,
            "type": "integer"
          },
          "min_reliability": {
            "anyOf": [
              {
                "type": "string"
              },
              {
                "type": "null"
              }
            ],
            "default": null,
            "description": "Optional inclusive published reliability floor, e.g. 'C' keeps A, B, and C; omit it to retain rows regardless of grade.",
            "examples": [
              "A",
              "C"
            ]
          },
          "mode": {
            "anyOf": [
              {
                "type": "string"
              },
              {
                "type": "null"
              }
            ],
            "default": null,
            "description": "Optional exact published detection mode filter, e.g. 'rolling_14d' or 'cadence_fallback'; omit it to include every mode.",
            "examples": [
              "rolling_14d",
              "cadence_fallback"
            ]
          }
        },
        "required": [],
        "type": "object"
      },
      "name": "find_anomalies"
    },
    {
      "description": "Return all datasets with the given licence, summarised. Use to enumerate what's available under a specific licence for compliance/reuse scoping. Use it to enumerate one licence; do not use it to discover by topic or inspect a dataset's citation context—use search_datasets or get_provenance instead. It reads published manifest data, so an empty list means no published dataset has the resolved licence; DataPulse is read-only, requires no API key, and the edge limits clients to roughly one request per second with a small burst, so pace or retry.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "licence": {
            "description": "Exact published licence name or supported alias, e.g. 'Creative Commons Attribution 4.0'; use search_datasets to discover licence values.",
            "examples": [
              "Creative Commons Attribution 4.0",
              "CC BY 4.0",
              "OGL"
            ],
            "minLength": 1,
            "type": "string"
          }
        },
        "required": [
          "licence"
        ],
        "type": "object"
      },
      "name": "find_by_licence"
    },
    {
      "description": "Return datasets whose published freshness trend is deteriorating, ranked by staleness slope. Optionally require a minimum historical anomaly rate; includes pipeline-computed trend and reliability evidence so agents do not recompute it. Use it for worsening freshness trends; do not use it for anomalies, recovery, reliability grades, or structural drift—use find_anomalies, find_recovering, find_unreliable, or find_schema_drift instead. It reads precomputed trend data, so an empty result means no published deteriorating row survives the selected filters; DataPulse is read-only, requires no API key, and the edge limits clients to roughly one request per second with a small burst, so pace or retry.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "limit": {
            "default": 50,
            "description": "Maximum highest-ranked deteriorating datasets to return, e.g. 50; omit it to use 50 without changing ranking.",
            "examples": [
              10,
              50
            ],
            "maximum": 200,
            "minimum": 1,
            "type": "integer"
          },
          "min_anomaly_rate": {
            "anyOf": [
              {
                "maximum": 100,
                "minimum": 0,
                "type": "number"
              },
              {
                "type": "null"
              }
            ],
            "default": null,
            "description": "Optional inclusive anomaly-rate filter on published history, e.g. 25.0; omit it to retain every deteriorating row.",
            "examples": [
              25,
              50
            ]
          }
        },
        "required": [],
        "type": "object"
      },
      "name": "find_deteriorating"
    },
    {
      "description": "Return datasets whose published freshness trend is recovering, with the fastest staleness reductions first. Includes pipeline-computed trend and publish-reliability evidence. Use it for improving freshness trends; do not use it for deterioration, anomalies, reliability grades, or structural drift—use find_deteriorating, find_anomalies, find_unreliable, or find_schema_drift instead. It reads precomputed trend data, so an empty result means no published recovering row exists; DataPulse is read-only, requires no API key, and the edge limits clients to roughly one request per second with a small burst, so pace or retry.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "limit": {
            "default": 50,
            "description": "Maximum fastest-recovering datasets to return, e.g. 50; omit it to use 50 without changing ranking.",
            "examples": [
              10,
              50
            ],
            "maximum": 200,
            "minimum": 1,
            "type": "integer"
          }
        },
        "required": [],
        "type": "object"
      },
      "name": "find_recovering"
    },
    {
      "description": "Return datasets with published structural or record-count drift evidence, ranked with structural changes first. Optionally require a minimum number of structural transitions; includes pipeline-computed evidence so agents do not infer drift from freshness alone. Use it for structural or record-count changes; do not use it for freshness risk, anomalies, trends, or reliability—use find_stale, find_anomalies, find_deteriorating, or find_unreliable instead. It reads precomputed drift data, so an empty result means no published drift row survives the selected filters; DataPulse is read-only, requires no API key, and the edge limits clients to roughly one request per second with a small burst, so pace or retry.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "limit": {
            "default": 50,
            "description": "Maximum structural-first ranked drift results to return, e.g. 50; omit it to use 50 without changing ranking.",
            "examples": [
              10,
              50
            ],
            "maximum": 200,
            "minimum": 1,
            "type": "integer"
          },
          "min_change_count": {
            "default": 0,
            "description": "Inclusive filter on the larger published shape or column transition count, e.g. 1; omit it to include every drift row.",
            "examples": [
              0,
              1
            ],
            "maximum": 100,
            "minimum": 0,
            "type": "integer"
          }
        },
        "required": [],
        "type": "object"
      },
      "name": "find_schema_drift"
    },
    {
      "description": "Return datasets whose status is aging, stale, or degraded, plus datasets missing from the latest health snapshot. Use when an agent needs to know which data has a freshness or schema-validity risk. Use it to enumerate freshness or schema-risk candidates; do not use it for anomalies, trends, reliability, or drift—use find_anomalies, find_deteriorating, find_unreliable, or find_schema_drift instead. It reads the published health snapshot, so an empty result means no rows met this snapshot-based rule; DataPulse is read-only, requires no API key, and the edge limits clients to roughly one request per second with a small burst, so pace or retry.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "max_age_hours": {
            "default": 24,
            "description": "Maximum published-snapshot age before otherwise healthy rows are included, e.g. 72; omit it to use 24 hours.",
            "examples": [
              24,
              72
            ],
            "minimum": 0,
            "type": "integer"
          }
        },
        "required": [],
        "type": "object"
      },
      "name": "find_stale"
    },
    {
      "description": "Return datasets whose evaluated publish-reliability grade is at or below a threshold (the unreliable ones), with the worst grades and lowest on-time percentages first. Reliability measures timeliness of successful freshness observations, not uptime; sample days are included so agents can judge evidence depth. Use it for timeliness reliability grades; do not use it for individual anomalies, trends, or structural drift—use find_anomalies, find_deteriorating, find_recovering, or find_schema_drift instead. It reads precomputed reliability data, so an empty result means no published grade meets the threshold; DataPulse is read-only, requires no API key, and the edge limits clients to roughly one request per second with a small burst, so pace or retry.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "at_or_below_grade": {
            "default": "C",
            "description": "Inclusive published reliability threshold; e.g. 'C' returns grades C, D, and F; omit it to use C.",
            "examples": [
              "C",
              "F"
            ],
            "type": "string"
          },
          "limit": {
            "default": 50,
            "description": "Maximum worst-ranked unreliable datasets to return, e.g. 50; omit it to use 50 without changing ranking.",
            "examples": [
              10,
              50
            ],
            "maximum": 200,
            "minimum": 1,
            "type": "integer"
          }
        },
        "required": [],
        "type": "object"
      },
      "name": "find_unreliable"
    },
    {
      "description": "Return one bounded, machine-readable Dataset Passport v1 for a canonical dataset ID. It reads the published Passport artifact only; it does not fetch an upstream source or create evidence. The Passport describes observed metadata and evidence availability, not semantic truth, completeness, certification, legal permission, safety, or AI admission. Use it for the bounded Passport artifact; do not use it for current health detail or citation context—use get_dataset or get_provenance instead. It reads precomputed published data, and evidence_available=false identifies an unavailable or unsupported Passport; DataPulse is read-only, requires no API key, and the edge limits clients to roughly one request per second with a small burst, so pace or retry.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "dataset_id": {
            "description": "Stable dataset slug returned by search_datasets, e.g. 'fuelprice'; this tool requires the slug, not a display name.",
            "examples": [
              "fuelprice"
            ],
            "minLength": 1,
            "type": "string"
          }
        },
        "required": [
          "dataset_id"
        ],
        "type": "object"
      },
      "name": "get_data_passport"
    },
    {
      "description": "Return full detail for one dataset id, including its latest health status and last-verified timestamp, content_freshness_date, and freshness_signal_source (last_modified, content_parse, or none). Use to fetch the provenance/citation metadata for a dataset found via search_datasets and distinguish unknown-freshness from proven stale data. Use it for one dataset's current published detail; do not use it for citation context or a Passport—use get_provenance or get_data_passport instead. It reads published data, so an absent health row is reported as unknown rather than probed live; DataPulse is read-only, requires no API key, and the edge limits clients to roughly one request per second with a small burst, so pace or retry.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "dataset_id": {
            "description": "Stable dataset slug returned by search_datasets, e.g. 'dosm_cpi_state'; this tool requires the slug, not a display name.",
            "examples": [
              "dosm_cpi_state"
            ],
            "minLength": 1,
            "type": "string"
          }
        },
        "required": [
          "dataset_id"
        ],
        "type": "object"
      },
      "name": "get_dataset"
    },
    {
      "description": "Use for a deep evidence audit or to inspect a provenance and evidence receipt. Returns the complete published evidence receipt for one dataset: probe time, transport, access dependency, freshness, schema drift / record-count drift, tolerance, status, anomaly fields, and receipt/evidence references. It reads published pipeline evidence, not a live source fetch: you may report what the pipeline observed, but must not infer the source is currently reachable or semantically true. Use it for a deep audit before or alongside verification. search_datasets → get_evidence → verify_evidence → verify_attestation. Use it for a complete published receipt; do not use it for a live transport check or signature verification—use verify_evidence or verify_attestation instead. It reads precomputed evidence, so evidence_available=false means no published health row; DataPulse is read-only, requires no API key, and the edge limits clients to roughly one request per second with a small burst, so pace or retry.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "dataset_id": {
            "description": "Stable dataset slug returned by search_datasets for its complete receipt, e.g. 'fuelprice'; this tool requires the slug, not a display name.",
            "examples": [
              "fuelprice"
            ],
            "minLength": 1,
            "type": "string"
          }
        },
        "required": [
          "dataset_id"
        ],
        "type": "object"
      },
      "name": "get_evidence"
    },
    {
      "description": "Return a freshness-at-a-glance summary of the published catalogue: fresh, aging, stale, and reference counts plus the latest health check time. Use it for catalogue-level freshness context; do not use it to enumerate affected datasets—use find_stale instead. It reads the latest published snapshot, so missing counts or check time mean the artifact omitted them; DataPulse is read-only, requires no API key, and the edge limits clients to roughly one request per second with a small burst, so pace or retry.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {},
        "required": [],
        "type": "object"
      },
      "name": "get_freshness_summary"
    },
    {
      "description": "Use when asked 'can I cite this source?', for licence and attribution, or for citation-ready provenance. Returns source, steward, licence/attribution context, canonical URL, and compact published evidence context: probe time, transport, access dependency, freshness signal, schema drift / record-count drift context, anomaly flag, and status. Bind a citation to dataset identity, source/evidence URL, observed-at or last-checked time, DataPulse status/verdict, licence/attribution, and a receipt/evidence digest when available. You may cite the returned provenance and describe its published evidence; it is not a freshness guarantee and does not itself verify the source is current. For pre-trust use search_datasets → verify_dataset → get_provenance. Use it for citation-ready provenance; do not use it for full evidence or a live comparison—use get_evidence or verify_evidence instead. It reads published evidence context, so absent fields mean the pipeline did not publish that value; DataPulse is read-only, requires no API key, and the edge limits clients to roughly one request per second with a small burst, so pace or retry.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "dataset_ids": {
            "description": "Dataset slugs returned by search_datasets for a batched citation lookup, e.g. ['fuelprice', 'pricecatcher']; preserve order and use get_dataset for display-name resolution.",
            "examples": [
              [
                "fuelprice",
                "pricecatcher"
              ]
            ],
            "items": {
              "type": "string"
            },
            "maxItems": 50,
            "minItems": 1,
            "type": "array"
          }
        },
        "required": [
          "dataset_ids"
        ],
        "type": "object"
      },
      "name": "get_provenance"
    },
    {
      "description": "Use for discovery only: find DataPulse's 440 Malaysian public datasets by topic, source, or licence—for example, 'Malaysian public data inflation', licence and attribution, or a government dataset source. Returns ranked matches with id, title, source, licence, published status, and score. This is not trust verification: a status is published pipeline context, not proof that a dataset is current or reliable. For pre-trust use search_datasets → verify_dataset → get_provenance. Use it to discover candidates; do not use it for a trust decision—use verify_dataset instead. It reads published catalogue data, so no match means the published catalogue has no matching entry; DataPulse is read-only, requires no API key, and the edge limits clients to roughly one request per second with a small burst, so pace or retry.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "licence": {
            "anyOf": [
              {
                "type": "string"
              },
              {
                "type": "null"
              }
            ],
            "default": null,
            "description": "Optional exact licence name or supported alias applied before ranking, e.g. 'CC BY 4.0'; omit it to search every licence.",
            "examples": [
              "CC BY 4.0",
              "Open Government Licence (Malaysia)"
            ]
          },
          "limit": {
            "default": 10,
            "description": "Maximum highest-ranked discovery matches to return, e.g. 10; omitted defaults to 10 and does not change ranking.",
            "maximum": 50,
            "minimum": 1,
            "type": "integer"
          },
          "query": {
            "description": "Topic or task phrasing used to rank discovery candidates, e.g. 'Malaysian public data inflation'; use a returned id with get_dataset.",
            "examples": [
              "Malaysian public data inflation"
            ],
            "minLength": 1,
            "type": "string"
          },
          "source": {
            "anyOf": [
              {
                "type": "string"
              },
              {
                "type": "null"
              }
            ],
            "default": null,
            "description": "Optional publisher/source substring filter applied before ranking, e.g. 'OpenDOSM'; omit it to search every source.",
            "examples": [
              "OpenDOSM",
              "data.gov.my",
              "MET Malaysia"
            ]
          }
        },
        "required": [
          "query"
        ],
        "type": "object"
      },
      "name": "search_datasets"
    },
    {
      "description": "Return published attestation facts, the unsigned methodology-versioned trust score, numeric components, and component_availability reasons, plus existing health/trend/drift/reconciliation evidence for one canonical dataset id, e.g. 'fuelprice'. This tool does not re-probe or verify the signature; call verify_attestation separately. Use it to assemble the published trust view; do not use it for receipt verification, live comparison, or signature verification—use verify_dataset, verify_evidence, or verify_attestation instead. It reads precomputed artifacts, so missing component availability explains omitted evidence rather than a live probe; DataPulse is read-only, requires no API key, and the edge limits clients to roughly one request per second with a small burst, so pace or retry.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "dataset_id": {
            "description": "Stable dataset slug returned by search_datasets to aggregate, e.g. 'fuelprice'; display names are not resolved here.",
            "examples": [
              "fuelprice"
            ],
            "minLength": 1,
            "type": "string"
          }
        },
        "required": [
          "dataset_id"
        ],
        "type": "object"
      },
      "name": "trust_verdict"
    },
    {
      "description": "Aggregate anonymous tool usage for an inclusive ISO date range, e.g. 2026-08-01 to 2026-08-07. Returns `total_calls`, `by_outcome`, `by_tool`, `by_dataset`, `trust_verdict_calls` (the count of trust_verdict records regardless of outcome or result shape), and `trust_distribution` (counts of returned trust verdicts by published score band: 90-100, 75-89, 50-74, 25-49, 0-24) for the inclusive range. Use it for aggregate tool activity; do not use it to find data-quality risks—use find_stale, find_anomalies, find_deteriorating, find_recovering, find_unreliable, or find_schema_drift instead. It reads persisted usage records, so zero totals mean no retained records in that range; DataPulse is read-only, requires no API key, and the edge limits clients to roughly one request per second with a small burst, so pace or retry.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "since": {
            "description": "Inclusive first day of the persisted-record window, e.g. '2026-08-01'; it must not be after until.",
            "examples": [
              "2026-08-01"
            ],
            "type": "string"
          },
          "until": {
            "description": "Inclusive last day of the persisted-record window, e.g. '2026-08-07'; it must not be before since.",
            "examples": [
              "2026-08-07"
            ],
            "type": "string"
          }
        },
        "required": [
          "since",
          "until"
        ],
        "type": "object"
      },
      "name": "usage_summary"
    },
    {
      "description": "Use to verify a signed published probe attestation after an evidence audit. Returns L1 signature, key, time, and chain-link checks; optional L2 replay of daily heads to a Git-tag anchor; and L3 scope, which requires verify_evidence for live transport. A valid signature proves attestation integrity and scope, not upstream semantic truth or currentness. For a deep audit use search_datasets → get_evidence → verify_evidence → verify_attestation. Use it for signed-attestation integrity; do not use it for published receipt verification, a live transport comparison, or an aggregate verdict—use verify_dataset, verify_evidence, or trust_verdict instead. L2 is not run unless replay_chain is set, and a failed level reports an unsatisfied check rather than upstream semantic truth; DataPulse is read-only, requires no API key, and the edge limits clients to roughly one request per second with a small burst, so pace or retry.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "reference": {
            "description": "Dataset slug returned by search_datasets or an exact published digest reference, e.g. 'fuelprice'; the slug resolves through the attestation index.",
            "examples": [
              "fuelprice",
              "attestations/2026-08-15/fuelprice.json"
            ],
            "minLength": 1,
            "type": "string"
          },
          "replay_chain": {
            "default": false,
            "description": "Set true to perform the slower L2 daily-head replay to a Git tag, e.g. true; omit it to run L1 only.",
            "examples": [
              false,
              true
            ],
            "type": "boolean"
          }
        },
        "required": [
          "reference"
        ],
        "type": "object"
      },
      "name": "verify_attestation"
    },
    {
      "description": "This is the preferred single-call pre-trust check for 'is this dataset current?', stale, unknown-freshness, degraded, or browser-dependent questions, and whenever an agent must verify before relying on data. Returns dataset metadata, published evidence and fail-closed signed receipt verification with artifact references. It verifies published artifacts, not a live source check: you may infer whether their receipt verifies, but must not infer current upstream availability or semantic truth. Use search_datasets → verify_dataset → get_provenance. Use it for one published pre-trust check; do not use it for a live transport comparison or attestation-chain verification—use verify_evidence or verify_attestation instead. It verifies precomputed published artifacts, so a failed check does not identify current upstream availability; DataPulse is read-only, requires no API key, and the edge limits clients to roughly one request per second with a small burst, so pace or retry.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "dataset_id": {
            "description": "Stable dataset slug returned by search_datasets for the published receipt check, e.g. 'fuelprice'; this tool requires the slug, not a display name.",
            "examples": [
              "fuelprice"
            ],
            "minLength": 1,
            "type": "string"
          },
          "include_proof_steps": {
            "default": false,
            "description": "Set true to include bounded verifier diagnostics for an audit, e.g. false; omit it to suppress diagnostics without changing verification.",
            "examples": [
              false,
              true
            ],
            "type": "boolean"
          }
        },
        "required": [
          "dataset_id"
        ],
        "type": "object"
      },
      "name": "verify_dataset"
    },
    {
      "description": "Use when a fresh, rate-limited live-vs-published comparison is needed for a direct-access dataset, for example after asking whether a government dataset is reachable now. Performs a rate-limited live GET and returns comparable transport receipts plus a match, mismatch, unreachable, or not_verifiable verdict. This live check is an observation, not semantic truth: it does not recompute content dates, record counts, or shape fingerprints. Results are ephemeral and do not update published health artifacts. For a deep audit use search_datasets → get_evidence → verify_evidence → verify_attestation. Use it for a live transport comparison; do not use it for published receipt integrity or signed-attestation verification—use verify_dataset or verify_attestation instead. An unreachable or not_verifiable verdict reports that this live comparison could not establish a match, while cached results are still ephemeral; DataPulse is read-only, requires no API key, and the edge limits clients to roughly one request per second with a small burst, so pace or retry.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "dataset_id": {
            "description": "Stable direct-access dataset slug returned by search_datasets for a live transport observation, e.g. 'fuelprice'; browser-dependent sources return not_verifiable.",
            "examples": [
              "fuelprice"
            ],
            "minLength": 1,
            "type": "string"
          }
        },
        "required": [
          "dataset_id"
        ],
        "type": "object"
      },
      "name": "verify_evidence"
    }
  ]
}

What the leaf hashes

{"body":"d128c1ecedc405a3ed0329b62f1a03fcb996e776f609fc292ba9e02614c825da","id":275743,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793040792003920,"prev":null,"subject":"605b7c48-ae8d-4b4c-acda-ade9ca01a9bd","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. 0x745a3f1accb90f3794890069ce2e33faf3e4bd925f2e45ee4e58546655bf1a5f
  2. 0x6eb7387422703098cc89444ba5561421d693eab010c955eb08b232b3dac8b6ae
  3. 0x1eecf25539b142fb01e318a54d4cfa15aea5675419dbcd8d0f06e1ac98b7a85b
  4. 0x88077c20aba25bcb9a0d0a1fdf5281add90d6e6aaddbadea13c1a458614e5730
  5. 0xe383e3c820a1222145d002b11af33961b7abb5795a049eb7171ecd45b40a7542
  6. 0x00bb74a5f7e45754e23b34f65be6edc7f46b178966204ec9051829386f534051
  7. 0x1afc0c78dcc9ecfdf58207835cf84c66cd9cb1e8337cb91b7cc926ee9ac8850f
  8. 0xbedcd42ca7c3d14a88c7c1864b5bfcf816c96f4dceb39130b856a97e62565159
  9. 0xd0bbcf02f0483daaff2680f7dc63577b211f9daed61d6ffaf73cadb654bf6124
  10. 0xeeb27e00b2f1b77815fcef94bdfe05e33ce9324a8f8948c0770868e4d010c7b9
  11. 0x9adfaac1e332051e6999b9b702c6d539c2d639f94fd57735f2ddd441a4b5230c
  12. 0x3f193b47c78cf4e7b9e4988cd716854b0e1011e5fcbca161f5a885f1aa02857d
  13. 0x06064dc1eb2363bec8c2a752e0a28aafc4bf0cb21d1b1b755821c1575bb77a96
  14. 0xc4fe2177880ea1b0e82b6fe4c270090fd0fbe5af3a42a8cbf6a6ba2fa35625f6
  15. 0x15039087bf60ae9b06b756ec3cbc299760e59923a438bbd91e34d105186db0ed
  16. 0x2b6e23e3624a1b66e1d2298cfbce99a93ce6b13d24a58112a71802d79c5f7a76
  17. 0xd21942ae3214eff88e08ab04884fd4b11958b51af9a0741b7668e2d07a2c56c9
  18. 0x9a9024edb5069d88a324facb310a5ce8e495214bbaa968f077bede437390194f
  19. 0x9b9ce5b74b9bab5121612ef6b64920a8d453cbf311096a423eef9702747e868a
Day root
0xf43e8dcc3d451a4788b26be904c55e8c4c0fa75c9666796c51db38d37e2c0df8
Chained
0x702d5ac508f08b0d1accf36af25822d8e5660367494edd17a642fb61e158a57a
Published
On Arc Testnet, block 69251483: 0x495162f8936e19f0039918feebe6c307f327cd6bf8c37219620b1970041fa9ae

How to check it · This row as JSON