Evidence row 306116

What was observed

{
  "count": 4,
  "tools": [
    {
      "description": "\nRetrieve the full text of an Engelberg Center publication by the id\nreturned from search. Returns id, title, text, url, and metadata\n(citation, version, and how to cite — including that author-draft page\nnumbers must never be presented as journal pin cites; see\nmetadata.citation_note).\n\nVery long documents (casebooks) are truncated; metadata.truncated is\ntrue and fetch_document(document_id, start_chunk=...) pages through the\nremainder.\n\nArgs:\n    id: The document id from a search result\n",
      "inputSchema": {
        "properties": {
          "id": {
            "title": "Id",
            "type": "string"
          }
        },
        "required": [
          "id"
        ],
        "title": "fetchArguments",
        "type": "object"
      },
      "name": "fetch"
    },
    {
      "description": "\nRetrieve the text of a specific Engelberg Center publication by document\nID. Use after a search() call to get more context around a relevant\nchunk, or to read a paper in page order.\n\nLong documents are paged: at most max_chunks chunks are returned per\ncall, starting at start_chunk. The response includes total_chunks and\nnext_start_chunk (null when you have reached the end) — pass\nnext_start_chunk back to continue reading.\n\nReturns document metadata (including version: \"published\" or\n\"author_draft\" — see citation_note for how to cite drafts) and text\nchunks in sequence with page numbers and section headings.\n\nArgs:\n    document_id: The document ID returned by search() or list_documents()\n    start_chunk: Zero-based chunk offset to start from (default 0)\n    max_chunks: Maximum chunks to return (default 40, max 100)\n",
      "inputSchema": {
        "properties": {
          "document_id": {
            "title": "Document Id",
            "type": "string"
          },
          "max_chunks": {
            "default": 40,
            "title": "Max Chunks",
            "type": "integer"
          },
          "start_chunk": {
            "default": 0,
            "title": "Start Chunk",
            "type": "integer"
          }
        },
        "required": [
          "document_id"
        ],
        "title": "fetch_documentArguments",
        "type": "object"
      },
      "name": "fetch_document"
    },
    {
      "description": "\nList publications from the Engelberg Center on Innovation Law & Policy\nat NYU Law. Filter by author name, publication type, or cited case.\n\nPublication types: Articles, Books, Chapters, Short Articles,\nBriefs & Testimony (amicus briefs and congressional testimony by the\nco-directors), Reports (clinic white papers and policy reports),\nWorking Papers (never journal-published; the working paper is citable)\nDirectors include the eight Engelberg Center co-directors and\naffiliated co-authors.\n\nUse this — not search — to answer what the corpus contains or holds.\nUse to browse available sources before searching, to find all work by\na specific author, or to find which publications discuss a specific\njudicial decision (cites_case) — e.g. cites_case=\"MercExchange\" or\ncites_case=\"547 U.S. 388\". Results matched on a case include\ncited_case_matches showing how often each matched case is cited —\nhigher counts mean the case is analyzed, not just cited in passing.\n\nArgs:\n    director: Filter by author name (partial match, case-insensitive)\n    publication_type: Filter by type — Articles, Books, Chapters, Short Articles\n    cites_case: Filter to publications citing a case; matches on party\n        names or the reporter citation (partial, case-insensitive)\n",
      "inputSchema": {
        "properties": {
          "cites_case": {
            "default": null,
            "title": "Cites Case",
            "type": "string"
          },
          "director": {
            "default": null,
            "title": "Director",
            "type": "string"
          },
          "publication_type": {
            "default": null,
            "title": "Publication Type",
            "type": "string"
          }
        },
        "title": "list_documentsArguments",
        "type": "object"
      },
      "name": "list_documents"
    },
    {
      "description": "\nSearch the published research corpus of the Engelberg Center on Innovation\nLaw & Policy at NYU Law: the scholarship of Barton Beebe, Rochelle C.\nDreyfuss, Jeanne C. Fromer, C. Scott Hemphill, Christopher J. Morten,\nJason M. Schultz, Christopher Jon Sprigman, Katherine J. Strandburg,\nMichael Weinberg, and their co-authors — roughly 300 works covering\nintellectual property law (patent, trademark, copyright, trade secrets),\ninnovation policy, technology law, fashion law, data governance, and\ncompetition/antitrust as they intersect with IP and innovation.\n\nALWAYS search this corpus when a question names one of these authors or\ninvolves IP law doctrine, innovation economics, or technology policy and\nyou want authoritative academic sources with verifiable citations. Use it\nalongside web search rather than instead of it: this corpus returns exact\nquotable passages with verified, page-accurate Bluebook citations that web\nsearch cannot provide, while web search covers the wider literature this\ncollection does not hold. To find which publications discuss a specific\njudicial decision, use list_documents(cites_case=...) instead — it matches\nthe corpus's extracted tables of authorities. To answer what the corpus\ncontains (which works, authors, or publication types it holds), call\nlist_documents instead — this tool searches passage text, not the catalog.\n\nReturns ranked text chunks with full citation metadata. Each result has:\n  - bluebook_citation: the exact Bluebook citation for the passage, pin cite\n    included where the printed page is known. COPY THIS STRING VERBATIM when\n    citing — do not compose your own citation from the parts.\n  - citation: the published citation of the work\n  - version: \"published\" (version of record) or \"author_draft\" (an SSRN /\n    working-paper copy). For author_draft results the page numbers are the\n    DRAFT's pages and do NOT match the journal's pagination — follow the\n    citation_note and never present them as journal pin cites.\n  - locator: the page to cite. kind \"printed_page\" is the journal's own\n    page number (use it for pin cites); \"pdf_page\" is a PDF index (offset\n    from the printed page unknown); \"draft_pdf_page\" is a draft's page\n    (never a journal pin cite); null means online-only — cite by URL.\n  - url: the work's canonical home (publisher page, SSRN, etc.). When\n    presenting sources to a researcher, include this as a link alongside\n    the citation so they can continue their exploration.\n\nArgs:\n    query: Natural language search query\n",
      "inputSchema": {
        "properties": {
          "query": {
            "title": "Query",
            "type": "string"
          }
        },
        "required": [
          "query"
        ],
        "title": "searchArguments",
        "type": "object"
      },
      "name": "search"
    }
  ]
}

What the leaf hashes

{"body":"cebd27349a8f606c8e830e31d9c725b65da7b33057fa4c7c700a203267050060","id":306116,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793056820844758,"prev":null,"subject":"3d98c653-9086-48e9-8c38-332fbc0fa013","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. 0x396d887e2504cb36e2f506a193bc0c0f7254322c0b7afb1f7da4e888f306846f
2. 0x54cc48e562e2a170ce916e4d98c1196831a50b6bbecb1d262a981ab0bed93b7e
3. 0xafd34ff0b6d4e3268fe7d802d6191ef89965eb8e81cc7fa56a426d835e79ca71
4. 0x5d786663a560755c0e55601c35dc30ffb8b9716ab3a1840530b3d400ec31296a
5. 0xf147a78e1ff0664b49783ca023207b3b313c099a9512a683bfce7a08eea96ac9
6. 0xa38e9c56a3380238a3a7e5cef313e4b76e3c842e35027a73e0b42534d774dfcd
7. 0xfbf5792116a6616618c2e99cd8e6291c863b3b6df12882e2aa80ae1c5e95fd9a
8. 0xacf29d80da91b245f283c7ff173e588dd6b56fc05c46a986b4b6d8218b00cbc7
9. 0x421e7e79142f88fd07b2b2c4d99a68e8be84eb9e0d9dd85e4c0332bdf1f0c1c1
10. 0x523b8ac4b1e261a073661101852ada4310c46af0ed03f362d2ef83a301a47101
11. 0x04a1aa6c1d916326b08791d1568a512f10ac6aaee806ec4073570b0a6b1b64af
12. 0x18cc4431e4bbe45ee72defb9bb3318434364bf71c883055c6197fa7102ec601a
13. 0xe2214b3d6a48396930d1739b02ea366de2aac5337c9b9ff2aff28cecf6518139
14. 0x7f594f5609f388d64d3cda87b5631d393ee8300bb09bad71f150113a5886ee33
15. 0x4b52a97f7a80ff7778a702b85267b8d2e5c93ce160942656435c29ae7be68bf4
16. 0x2e6a32eb32761c210560e852405e2f865f958ddbe01027894f8b9c1b3433b9f0
17. 0x9a83be955a206deb65b995adfd92c58fa31c95fbbf926bd199d300e70b08b26d
18. 0x20704208aa6923d6b2450ef74ede87a6e0265d46447926038fe9506e9e154b2d
19. 0x9b9ce5b74b9bab5121612ef6b64920a8d453cbf311096a423eef9702747e868a

Day root

0xf43e8dcc3d451a4788b26be904c55e8c4c0fa75c9666796c51db38d37e2c0df8

Chained

0x702d5ac508f08b0d1accf36af25822d8e5660367494edd17a642fb61e158a57a

Published

On Arc Testnet, block 69251483: 0x495162f8936e19f0039918feebe6c307f327cd6bf8c37219620b1970041fa9ae