Evidence row 291587

What was observed

{
  "count": 3,
  "tools": [
    {
      "description": "\nFree preview of one SEC filing (agent-friendly compact row from fi_listings_portfolio_compact).\n[COST: $0]\nIncludes agent_summary and financial_metrics (CompanyFacts-derived) but NOT full\nalpha_signals / causality_events — those ship only via purchase_filing after x402 payment.\nCompare with purchase_filing: sample = evaluate quality; purchase = full evidence-backed JSON.\n\n[EXAMPLE ARGUMENTS - MINIMAL]:\n{}\n\n[EXAMPLE ARGUMENTS - MAXIMAL]:\n{\"document_id\": \"000000708426000023\"}\n",
      "inputSchema": {
        "properties": {
          "document_id": {
            "anyOf": [
              {
                "type": "string"
              },
              {
                "type": "null"
              }
            ],
            "default": null,
            "description": "document_id from search_filings. Defaults to demo ADM 10-Q (000000708426000023).",
            "title": "Document Id"
          }
        },
        "title": "get_filing_sampleArguments",
        "type": "object"
      },
      "name": "get_filing_sample"
    },
    {
      "description": "\nPurchase and deliver one full SEC filing row from fi_listings_portfolio (MPP v1.0 x402).\n[COST: xpay per-call + on-chain USDC data price (see FINANCE_FILING_PRICE_USD)]\nFull JSON includes alpha_signals with evidence_verified causality_events and financial_metrics\nfrom SEC CompanyFacts. Do NOT return agent_bundle or internal pipeline fields.\n\n[AGENTIC WORKFLOW — mandatory 2-step 402 flow]:\nSTEP 1: Call with document_id and network only; leave tx_hash EMPTY.\nSTEP 2: Broadcast the exact transaction_payload on-chain (polygon USDC default).\nSTEP 3: Call again with the same document_id, network, and confirmed tx_hash (66 chars).\n\n[EXAMPLE ARGUMENTS - MINIMAL (Step 1 — payment info)]:\n{\"document_id\": \"000000708426000023\", \"network\": \"polygon\"}\n\n[EXAMPLE ARGUMENTS - MAXIMAL (Step 3 — claim data)]:\n{\n  \"document_id\": \"000000708426000023\",\n  \"network\": \"polygon\",\n  \"tx_hash\": \"0x1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef\"\n}\n",
      "inputSchema": {
        "properties": {
          "document_id": {
            "description": "document_id from search_filings or get_filing_sample.",
            "title": "Document Id",
            "type": "string"
          },
          "network": {
            "anyOf": [
              {
                "type": "string"
              },
              {
                "type": "null"
              }
            ],
            "default": "polygon",
            "description": "Blockchain network. Default polygon (USDC). Also supports base.",
            "title": "Network"
          },
          "tx_hash": {
            "anyOf": [
              {
                "type": "string"
              },
              {
                "type": "null"
              }
            ],
            "default": null,
            "description": "Transaction hash. LEAVE EMPTY on first call to receive 402 payment instructions.",
            "title": "Tx Hash"
          }
        },
        "required": [
          "document_id"
        ],
        "title": "purchase_filingArguments",
        "type": "object"
      },
      "name": "purchase_filing"
    },
    {
      "description": "\nPRIMARY discovery tool — lightweight catalog over 10k+ SEC filings (fi_listings_portfolio).\n[COST: low xpay per-call fee]\nDoes NOT return alpha_signals, causality_events, or financial_metrics (use get_filing_sample / purchase_filing).\nAlways returns agent_readiness_score (higher = better structured data) and edgar_url.\n\nRequired: at least one of ticker, form_type, company_name, fiscal_period, cik (avoids full-table scans).\n\nAgent workflow after this call:\n1. Shortlist by agent_readiness_score and optional agent_one_liner\n2. get_filing_sample(document_id) — free preview\n3. purchase_filing(document_id) — paid full JSON (x402)\n\n[EXAMPLE ARGUMENTS - MINIMAL]:\n{\"ticker\": \"AAPL\", \"limit\": 5}\n\n[EXAMPLE ARGUMENTS - MAXIMAL]:\n{\n  \"ticker\": \"ADM\",\n  \"form_type\": \"10-Q\",\n  \"company_name\": \"Archer\",\n  \"fiscal_period\": \"2026Q1\",\n  \"min_agent_readiness_score\": 70,\n  \"limit\": 20,\n  \"offset\": 0,\n  \"include_one_liner\": true\n}\n\n[EXAMPLE ARGUMENTS - PAGINATION (page 2)]:\n{\"ticker\": \"MSFT\", \"form_type\": \"10-K\", \"limit\": 10, \"offset\": 10}\n",
      "inputSchema": {
        "properties": {
          "cik": {
            "anyOf": [
              {
                "type": "string"
              },
              {
                "type": "null"
              }
            ],
            "default": null,
            "description": "SEC CIK prefix (digits, e.g. 0000320193).",
            "title": "Cik"
          },
          "company_name": {
            "anyOf": [
              {
                "type": "string"
              },
              {
                "type": "null"
              }
            ],
            "default": null,
            "description": "Substring match on company_name (e.g. Apple, Archer-Daniels).",
            "title": "Company Name"
          },
          "fiscal_period": {
            "anyOf": [
              {
                "type": "string"
              },
              {
                "type": "null"
              }
            ],
            "default": null,
            "description": "Fiscal period label (e.g. 2026Q1, 2025FY).",
            "title": "Fiscal Period"
          },
          "form_type": {
            "anyOf": [
              {
                "type": "string"
              },
              {
                "type": "null"
              }
            ],
            "default": null,
            "description": "SEC form: 10-K, 10-Q, 8-K, etc.",
            "title": "Form Type"
          },
          "include_one_liner": {
            "anyOf": [
              {
                "type": "boolean"
              },
              {
                "type": "null"
              }
            ],
            "default": false,
            "description": "If true, adds agent_one_liner (~1 sentence) per row for triage without calling get_filing_sample. Slightly heavier response.",
            "title": "Include One Liner"
          },
          "limit": {
            "anyOf": [
              {
                "type": "integer"
              },
              {
                "type": "null"
              }
            ],
            "default": 10,
            "description": "Page size (1–100). Default 10 keeps payloads small for LLM context.",
            "title": "Limit"
          },
          "min_agent_readiness_score": {
            "anyOf": [
              {
                "type": "integer"
              },
              {
                "type": "null"
              }
            ],
            "default": null,
            "description": "Minimum agent_readiness_score (0–100). Use 70+ for production-quality rows.",
            "title": "Min Agent Readiness Score"
          },
          "offset": {
            "anyOf": [
              {
                "type": "integer"
              },
              {
                "type": "null"
              }
            ],
            "default": 0,
            "description": "Skip rows for pagination (e.g. 10 for page 2 when limit=10).",
            "title": "Offset"
          },
          "ticker": {
            "anyOf": [
              {
                "type": "string"
              },
              {
                "type": "null"
              }
            ],
            "default": null,
            "description": "Ticker prefix, case-insensitive (e.g. AAPL, MSFT). At least one filter required.",
            "title": "Ticker"
          }
        },
        "title": "search_filingsArguments",
        "type": "object"
      },
      "name": "search_filings"
    }
  ]
}

What the leaf hashes

{"body":"9ba776aff5ca5ae01b628502c396ce96a8f11329e8d96a34a073386b7469a05d","id":291587,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793048185909653,"prev":null,"subject":"a6ca5d70-b2ed-4ca0-b443-ec50d49d84e0","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. 0x62d6bebd6bb453e3924580800167d727631a58c82324b6d5f8cedf6edccba201
2. 0x9d3bce0f58e4763ed131bebd8a425dc52476c93b0307841f5371b733d0c66bb0
3. 0x5b9f616ba314840a3d719d4ebe6212942cb716069e8b5d52f7f560a405a93f08
4. 0x34163c26e087bac0e69be3071a35c87df1a396e606598fd75588161f938428ce
5. 0x1b977387f8c8bd27a1e42a0b5d53d08649ce35b6c35c824c0b87b8951ff6aae3
6. 0x75e9d36936ffceabf0befdc3f774012897e84251b3c17c2a44343755ebb62fb6
7. 0x57960477960138b687cfcb1834c1d586777a1573c6327ff517f19c85c13e7f9d
8. 0x29852106eeedeb30652461e2a742548bf776639f8b3c95541087471c70382df7
9. 0x02dcf67e393f5295b2e183726d530c8289248ede5931fe31ff3de73461a13e3f
10. 0xb184ee2974258f113625a96655b34d89a19737485675dd6584b8ff67217463c8
11. 0x131755a2ea202f5e6a5e7b2b4223cbbcd0bee9398f637648162d1129112491ce
12. 0x7285c0b02d1aedd949b8ba0c7b2499f7121588ebdd4c96ef8725919bb84dd534
13. 0x89fcaf55e37dd777228f271b79ea895534a66ec0d184363c2a6eb1b4d23c9ef1
14. 0x216cebb9ae5414599109a02297c4817d7d1c6b1394afeb97efe38e32f0053974
15. 0x7726154b91b2ad65b13849ef6cb6443b1f0ff113a3089c9bd5f2bcfc16be099d
16. 0x47b89901b0f07938a6b9a66ddf35683903f79d756a7c7763665fd632758b08d0
17. 0x9a83be955a206deb65b995adfd92c58fa31c95fbbf926bd199d300e70b08b26d
18. 0x20704208aa6923d6b2450ef74ede87a6e0265d46447926038fe9506e9e154b2d
19. 0x9b9ce5b74b9bab5121612ef6b64920a8d453cbf311096a423eef9702747e868a

Day root

0xf43e8dcc3d451a4788b26be904c55e8c4c0fa75c9666796c51db38d37e2c0df8

Chained

0x702d5ac508f08b0d1accf36af25822d8e5660367494edd17a642fb61e158a57a

Published

On Arc Testnet, block 69251483: 0x495162f8936e19f0039918feebe6c307f327cd6bf8c37219620b1970041fa9ae