Evidence row 570505

What was observed

{
  "count": 7,
  "tools": [
    {
      "description": "Exact compound annual growth rate (CAGR) calculation over verified SEC filing facts. Deterministic mathematical execution with zero language model confabulation.",
      "inputSchema": {
        "properties": {
          "company": {
            "description": "Company ticker or name, e.g. AAPL",
            "type": "string"
          },
          "end_period": {
            "description": "End fiscal period, e.g. FY2023",
            "type": "string"
          },
          "low_tokens": {
            "description": "Optional. When true, returns compact JSON schema.",
            "type": "boolean"
          },
          "metric": {
            "description": "EDGAR metric to compound, e.g. revenue, free cash flow, net income",
            "type": "string"
          },
          "start_period": {
            "description": "Start fiscal period, e.g. FY2020",
            "type": "string"
          }
        },
        "required": [
          "company",
          "metric",
          "start_period",
          "end_period"
        ],
        "type": "object"
      },
      "name": "compute_sec_cagr"
    },
    {
      "description": "Deterministic zero-error algebraic solver (cagr, ratio, multiply, divide, yoy_series, product_chain) over verified SEC EDGAR financial metrics.",
      "inputSchema": {
        "properties": {
          "company": {
            "description": "Ticker or name when fetching EDGAR cells",
            "type": "string"
          },
          "end_period": {
            "description": "End / denominator period, e.g. FY2023",
            "type": "string"
          },
          "factors": {
            "description": "Optional comma-separated positive factors for product_chain, e.g. 0.79,0.30,1.07,4.5",
            "type": "string"
          },
          "low_tokens": {
            "description": "Optional. When true, returns compact JSON schema.",
            "type": "boolean"
          },
          "metric": {
            "description": "EDGAR metric, e.g. free cash flow, revenue",
            "type": "string"
          },
          "op": {
            "description": "cagr | ratio | multiply | divide | yoy_series | product_chain",
            "type": "string"
          },
          "periods": {
            "description": "Optional comma-separated fiscal periods for yoy_series/product_chain, e.g. FY2020,FY2021,FY2022",
            "type": "string"
          },
          "start_period": {
            "description": "Start / numerator period, e.g. FY2020",
            "type": "string"
          }
        },
        "required": [
          "op"
        ],
        "type": "object"
      },
      "name": "lattice_arith_evaluate"
    },
    {
      "description": "Certified SEC fact query. Returns verified values with provenance or SAFE_REFUSAL. Does not invent numbers. Treat SAFE_REFUSAL as success-of-honesty, not a tool failure. Monetary answers default to the filer's reporting currency; request FX conversion via target_currency / usd_only or natural-language 'in USD'.",
      "inputSchema": {
        "properties": {
          "low_tokens": {
            "description": "Optional. When true, returns compact ~38-token schema optimized for LLM context windows.",
            "type": "boolean"
          },
          "query": {
            "description": "Natural language financial question. Append 'in USD' (or another supported ISO code) to convert foreign reporting currencies after verified recall.",
            "type": "string"
          },
          "target_currency": {
            "description": "Optional ISO 4217 code (e.g. USD, EUR) for post-recall FX conversion using audited annual-average rates. Provenance records original_unit, fx_rate, and fx_converted.",
            "type": "string"
          },
          "usd_only": {
            "description": "When true, forces monetary answers into USD.",
            "type": "boolean"
          }
        },
        "required": [
          "query"
        ],
        "type": "object"
      },
      "name": "query_financial_sec"
    },
    {
      "description": "Exact EDGAR metric recall for company+metric+period. Server-side verified fact with provenance; SAFE_REFUSAL when missing. No LLM math.",
      "inputSchema": {
        "properties": {
          "company": {
            "description": "Company ticker or name, e.g. AAPL",
            "type": "string"
          },
          "low_tokens": {
            "description": "Optional. When true, returns compact JSON schema.",
            "type": "boolean"
          },
          "metric": {
            "description": "EDGAR metric, e.g. net income, free cash flow, total revenue, operating cash flow",
            "type": "string"
          },
          "period": {
            "description": "Fiscal period, e.g. FY2023",
            "type": "string"
          }
        },
        "required": [
          "company",
          "metric",
          "period"
        ],
        "type": "object"
      },
      "name": "query_sec_metric_exact"
    },
    {
      "description": "Returns certified SEC EDGAR XBRL metrics across an industry peer group dynamically derived from SEC filing SIC codes and 10-K business segment disclosures. Use this for sector screening or when no specific company ticker is provided.",
      "inputSchema": {
        "properties": {
          "limit": {
            "description": "Optional peer limit, default 5",
            "type": "number"
          },
          "low_tokens": {
            "description": "Optional. When true, returns compact JSON schema.",
            "type": "boolean"
          },
          "metrics": {
            "description": "Optional comma-separated or array of SEC XBRL metrics, e.g. Revenues,OperatingIncome,TotalLongTermDebt",
            "type": "string"
          },
          "period": {
            "description": "Optional filing period, e.g. FY2025",
            "type": "string"
          },
          "sector_or_industry": {
            "description": "Industry or sector description as declared in SEC filings, e.g. 'photonics', 'optics', 'semiconductors', 'pharmaceuticals', 'aerospace'",
            "type": "string"
          }
        },
        "required": [
          "sector_or_industry"
        ],
        "type": "object"
      },
      "name": "query_sec_sector_peers"
    },
    {
      "description": "Certified SEC/EDGAR valuation inputs pack (12 packs including dcf_valuation_inputs historical FCF). Not market EV, P/E, trading DCF, or macro gauges (Buffett Indicator / CAPE).",
      "inputSchema": {
        "properties": {
          "company": {
            "description": "Company ticker or name, e.g. AAPL, TSLA, MSFT",
            "type": "string"
          },
          "low_tokens": {
            "description": "Optional. When true, returns compact JSON schema.",
            "type": "boolean"
          },
          "pack": {
            "description": "Certified SEC valuation pack ID (equity_screen, ev_bridge, quality_of_earnings, segment_mix, returns_screen, leverage_screen, piotroski_f, altman_z_prime, beneish_m_score, dupont_5step, working_capital_efficiency, dcf_valuation_inputs)",
            "type": "string"
          },
          "period": {
            "description": "Optional reporting period, e.g. FY2023, Q3 FY2023. Defaults to FY2023 if omitted.",
            "type": "string"
          }
        },
        "required": [
          "company",
          "pack"
        ],
        "type": "object"
      },
      "name": "valuation_inputs"
    },
    {
      "description": "Returns a complete structured overview of all certified EDGAR valuation packs, deterministic financial arithmetic operations, SEC calculations, and product scope boundaries on finsec.caleralabs.com.",
      "inputSchema": {
        "properties": {
          "low_tokens": {
            "description": "Optional. When true, returns compact JSON schema.",
            "type": "boolean"
          }
        },
        "required": [],
        "type": "object"
      },
      "name": "vln_capabilities_overview"
    }
  ]
}

What the leaf hashes

{"body":"624a822aa498566fcb91aeee7606f4023c71e5ab403bb62070d00c67ea3c901c","id":570505,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793139811808479,"prev":null,"subject":"d22ded9d-c2ae-4ac7-8c26-769f77d07cca","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. 0x23f2f2b082d49a3aa1592766f6aa1cd2e8f4415e94d1dd453796111805220014
2. 0xcd7169ce848196aa7325d62e75828785ad13beaa2917117bb0e1467c3d12eca3
3. 0x860f70220e8f7335f62dd226c83460127509606781d7ba1dbb448a3925f3c552
4. 0x24335c908829ae8a4d2443a7a6798253e2cb6d8d91c7f6c7495b9cc17da5ff6e
5. 0x70523f2db5c76b036c1a63ab1f935692042ce27182c8032a7167da53446de8a2
6. 0x62296cd778489b108626f26b53c4ac87de0cf7496649c349b8f5f090a634b9ef
7. 0x2329b643e5d3359c9e13c6d9b68dcd3d6a84566465c2629e8815c78605c9b2ae
8. 0x441275d7c1b56c62e8713de8f04b5a1727afd15cfac23d3c755a04154e11722b
9. 0x9dd939084f4d215599195c47600f867c51d2d905bd6a85d5cdbe8fbb8b637a35
10. 0xcc3b635aa6ff475ba96afbb14eb21f771fe18361e8162f1cc45373e44a7ef411
11. 0xfd863135f9c1f207179b2582d91fd1a03f96c94cc1ab5865734d13d77a7655b6
12. 0x1e91fb86942396b9cc1330407cbddfe6048e98bde8c739e6cb5545d04c5cadd7
13. 0x1a710d4f8e6092d584b581d8599ff9183c0008f9275cf0601c925b43b4e84ae6
14. 0xe8ee6f6ed50253c5ee2d1aa85a4b1a38ce94bca7f3b72fd1850f496152dbe285
15. 0xa383a1cfe9b3f6af67eb4c7642564b9424d46d7fca90e7ba175d549f8b67dd0c
16. 0x52efa60e0c3d8525486d2310eb3b6b566c9677c64fd1f819edb072cf101bcbdb
17. 0x22c1fb9487ee0b9732fa017a0cc321eb27a60c08450d112f755089796e12cb1c
18. 0xa20d48798a34aba12eb9c7297722982d910f06c148f5e27ac59307422964a585
19. 0x9fc354c0ea3efc3f1b6548bb77ea902a50f2c9647647ea61592efce2bd795699

Day root

0xdd77e5e99da32c3f154180d63e3c3e6fe11e896a2c6896412ef6b5c4bcf7e795

Chained

0x23bb4dfd09f55c15ac3962f53578e02c6114d5bfd9bb451cf8794fb6e2817ef4

Published

On Arc Testnet, block 69414147: 0xb2ebd83aafeb765a0ce66e76aefb133ed06606c98038fd56191e2bcd1dcb77b4