addrbookFor publishers
← The evidence ledger

Evidence row 301927

Observed , by probe.mcp/1.

Kind
mcp.tools
About
endpoint acac4cf9-75b5-4ec6-adaa-496aa38044d2
Recorded
Previous row
None: the first of its kind about this subject
Body SHA-256
d8ef8e60f89e47cbde80431515cea0ad23a487f78c1955ba1a1602de1119e41a
Leaf
0x2647e15e81436dc6ab37c62e202e5095eae2d8c3a3ea01ac333f4cc9dc782ef0

What was observed

{
  "count": 1,
  "tools": [
    {
      "description": "Hybrid keyword + semantic search over the public pages of vascue.io: healthcare-operations guides, the AI front desk for clinics, provider-side insurance-claims automation, Cliniko and Nookal integration, security and compliance pages, case studies, pricing and blog posts.\n\nUse it to answer questions about what Vascue offers, how its products work and what it has published. One topic per call; cite the returned page URL for every excerpt you use.\n\nReturns a JSON text payload: result.chunks[] ordered by relevance, each with text (a Markdown excerpt), score (0-1, higher is better) and item.metadata.url (the canonical https://www.vascue.io/... page). Off-topic queries still return the nearest chunks, so treat scores below about 0.5 as weak evidence and say so when the site does not cover a topic.\n\nRead-only and idempotent; no authentication; 60 requests per minute per client. Public content only: never send patient information, claim documents, clinic credentials or booking requests. It cannot book appointments or look up clinic data.",
      "inputSchema": {
        "properties": {
          "ai_search_options": {
            "description": "Optional retrieval tuning. Omit for the defaults: hybrid search, 8 results, score threshold 0.35.",
            "properties": {
              "retrieval": {
                "properties": {
                  "context_expansion": {
                    "description": "Neighbouring chunks from the same page to include around each hit (default 0).",
                    "maximum": 3,
                    "minimum": 0,
                    "type": "integer"
                  },
                  "match_threshold": {
                    "description": "Minimum relevance score for a chunk to be included (default 0.35); raise for precision, lower for recall.",
                    "maximum": 1,
                    "minimum": 0,
                    "type": "number"
                  },
                  "max_num_results": {
                    "description": "Maximum chunks to return (default 8).",
                    "maximum": 50,
                    "minimum": 1,
                    "type": "integer"
                  },
                  "retrieval_type": {
                    "description": "hybrid (default) fuses keyword and vector ranking; keyword for exact phrases or product names; vector for paraphrased questions.",
                    "enum": [
                      "hybrid",
                      "vector",
                      "keyword"
                    ],
                    "type": "string"
                  }
                },
                "type": "object"
              }
            },
            "type": "object"
          },
          "query": {
            "description": "What to look for, as a natural-language question or keywords, e.g. \"how does claims pre-authorisation work\" or \"Cliniko integration\". 3-15 words works best; one topic per call.",
            "type": "string"
          }
        },
        "required": [
          "query"
        ],
        "type": "object"
      },
      "name": "search"
    }
  ]
}

What the leaf hashes

{"body":"d8ef8e60f89e47cbde80431515cea0ad23a487f78c1955ba1a1602de1119e41a","id":301927,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793054357080158,"prev":null,"subject":"acac4cf9-75b5-4ec6-adaa-496aa38044d2","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. 0x2647dbc98a8510939ddc5b7a9866627dedb68edf4845922b546a1bfabac2e143
  2. 0x0f8bebaa4d96973565ce2ac76fabbe32b015dea372762b85956729cafcc3b7f7
  3. 0x448c4af128503e4ef096a01ba8c068f5e652f79de2376ccfd539295354d14aec
  4. 0xb8553689e92579ee7ee16cd0da287d466f8eabf52be2b1e12956fcd3a9be4452
  5. 0x67000a95bee97bce0bb153e25fea39f3f833a6c4ccb05e574b165cf83c0ea59a
  6. 0xd09957e4ed89a338fae348da4da2a54733fd504356f62aa9ae152fca85046a1a
  7. 0x1dca628a9a6964004485ff778a2d828dcbab4e43d8f68fcadf9fc98ed5f0f7d9
  8. 0xf5b6ede652a764034fde0c7bd8154ab87f35e0d6e60b172059750d62af284f01
  9. 0xeac39e1a0ebecf6a1aabde93560176deeaf9d6126348ff76ef10cd221e99e21c
  10. 0x1dad1edcb2a79dd2d06559e438975ccfdf5ae3c94d461c1d78f86118f235991b
  11. 0x90f2b3a28efa276421488834f526df2e5769ef8f14ee569439eea7b97f77a866
  12. 0x266d991b0a994042474d2789bd5d3ba2433a122ae3c1027e2ccd7c0f4cf63071
  13. 0x830b2c874449c7499489eba2baa67d49f991298225763c0161b471621038d0fb
  14. 0xd843afcced75dedd39194ff9bd12326b88099e6112686db2299392d022dc3146
  15. 0xc3a6a3ae44ec0da1848b16d40c45d7aac97a67352eea8df18e0f26edabea8a2f
  16. 0x06d71bfa7d8b41d62c8836efc2c601e1cc3772d9453596b2ae4950887f3310ca
  17. 0x8c756542e482157df0c36464d75c937b845e4423dbbcfad08f0cf8d5a16b9a13
  18. 0x20704208aa6923d6b2450ef74ede87a6e0265d46447926038fe9506e9e154b2d
  19. 0x9b9ce5b74b9bab5121612ef6b64920a8d453cbf311096a423eef9702747e868a
Day root
0xf43e8dcc3d451a4788b26be904c55e8c4c0fa75c9666796c51db38d37e2c0df8
Chained
0x702d5ac508f08b0d1accf36af25822d8e5660367494edd17a642fb61e158a57a
Published
On Arc Testnet, block 69251483: 0x495162f8936e19f0039918feebe6c307f327cd6bf8c37219620b1970041fa9ae

How to check it · This row as JSON