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Evidence row 766680

Observed , by probe.mcp/1.

Kind
mcp.tools
About
endpoint e02856ce-442f-456c-a7b2-62fc1f55ed3c
Recorded
Previous row
#541007
Body SHA-256
3449bd1410879729508493ce829e08e25609fc33938f7c96ffc58e9e55755f9f
Leaf
0xa3fcc1027523f040cabf7947613aa4b0c976bdfdca7eb151faeaac9b4fee1a2d

What was observed

{
  "count": 5,
  "tools": [
    {
      "description": "Static-analyze a public GitHub repo (owner/name) or a set of source files for LLM token waste: uncached static prompts, frontier models on extraction tasks, hot loops, non-deterministic repeat calls. Returns findings with fixes and an estimated recoverable percentage.",
      "inputSchema": {
        "properties": {
          "files": {
            "description": "Alternative to repo: files to analyze",
            "items": {
              "properties": {
                "content": {
                  "type": "string"
                },
                "path": {
                  "type": "string"
                }
              },
              "required": [
                "path",
                "content"
              ],
              "type": "object"
            },
            "type": "array"
          },
          "repo": {
            "description": "GitHub owner/name (public)",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "audit_repo_token_waste"
    },
    {
      "description": "Price a workload at list prices across models: cost per request and per month for the requested model, its cheaper sibling, and the effect of prompt caching. Pricing table version 2026-10-27.",
      "inputSchema": {
        "properties": {
          "compare_to": {
            "items": {
              "type": "string"
            },
            "type": "array"
          },
          "input_tokens": {
            "type": "number"
          },
          "model": {
            "type": "string"
          },
          "output_tokens": {
            "type": "number"
          },
          "requests_per_month": {
            "type": "number"
          },
          "static_tokens": {
            "description": "portion of input_tokens that is a fixed prefix (system + tools)",
            "type": "number"
          }
        },
        "required": [
          "model",
          "input_tokens",
          "output_tokens"
        ],
        "type": "object"
      },
      "name": "calculate_model_arbitrage"
    },
    {
      "description": "Rewrite an OpenAI Chat/Responses or Anthropic Messages request body so its static prefix is provider-cacheable (Anthropic cache_control breakpoints, OpenAI prompt_cache_key). Returns the optimized body, what changed, the token profile and the projected per-request saving. Never changes the tokens the model sees.",
      "inputSchema": {
        "properties": {
          "body": {
            "description": "The request body",
            "type": "object"
          },
          "endpoint": {
            "enum": [
              "/v1/chat/completions",
              "/v1/responses",
              "/v1/messages"
            ],
            "type": "string"
          },
          "strategy": {
            "enum": [
              "static",
              "conversation"
            ],
            "type": "string"
          }
        },
        "required": [
          "body"
        ],
        "type": "object"
      },
      "name": "optimize_prompt_payload"
    },
    {
      "description": "Create a TokenZero workspace and key with no form. Returns the key once, the base URLs that route through it (OPENAI_BASE_URL / ANTHROPIC_BASE_URL), the one-click dashboard link and the badge URL. Free up to the monthly free tier; nothing is billed.",
      "inputSchema": {
        "properties": {
          "name": {
            "description": "workspace name (default mcp-agent)",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "provision_workspace"
    },
    {
      "description": "Live value scorecard for a TokenZero workspace: hard savings and net ROI per window, the four engines' contribution, speed, parity, availability and privacy posture, per-model breakdown and one-click recommendations. Needs the workspace key (tz_live_…); pass demo: true for a labelled sample.",
      "inputSchema": {
        "properties": {
          "demo": {
            "description": "return the sample scorecard instead",
            "type": "boolean"
          },
          "key": {
            "description": "workspace key (tz_live_…)",
            "type": "string"
          },
          "window": {
            "enum": [
              "24h",
              "7d",
              "30d",
              "all"
            ],
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "workspace_metrics"
    }
  ]
}

What the leaf hashes

{"body":"3449bd1410879729508493ce829e08e25609fc33938f7c96ffc58e9e55755f9f","id":766680,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793180494005337,"prev":541007,"subject":"e02856ce-442f-456c-a7b2-62fc1f55ed3c","subject_kind":"endpoint"}

Proof

Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of (231336 rows).

  1. 0xa3fcce337b8eb61eafdf02243db374a2c43406aa18f78aa8527adfa0d58262f8
  2. 0xe22775397ffebd7d6dab6797124b0a25680d57442286ce53fbdc8f3ad65f94db
  3. 0x8f6a8670a2bdf46eadeb496c9138e75fe0653159ac742f3f5f0cb212cadb31c4
  4. 0x270bc77ea8d813fc85e7064b2801bff7298b7ee4b3228a06dc047539544795e1
  5. 0x30460aa0ade1bb588859a5be942be6f684c4ab7b3e9dacf400ef1fe54287a61f
  6. 0x9751c04a947de6e8fad04280f0c654a93526e534659f5a4cb8df3868d7aeb9cf
  7. 0x752c03248e45d67875ccd7e7d616b6319d89e880dfdf44fab58a3f42166d7db5
  8. 0x9e5b9dd2e868dd5e0a71eae88a56afa24744f71010e09c53c09d2b621a0ea263
  9. 0xbd077ae4f4b833d0f0f886731c7193349fa31d0b8cca25cea51d1351ce77073f
  10. 0xbee3158f256798024ebf505beed71ae1d32f12a0f107919106cf9510813a9754
  11. 0xa93a1c5082d1ae8f18c5497fc3ea9e0e5d898ffc2c8de701e90563e7abce2e00
  12. 0xc76daff8dd433614e4df32053a3c7a221e41f4a1f5313320c4e5f6454368d7df
  13. 0xb5454b2881dcf5871db87f595c9d60eba5c4fd664d097bbcb5ca16283b093246
  14. 0x518f746edef7675640c92fbe2c056392702ec8f1ebbb6ede597bd5f7c0c5aea1
  15. 0xcd8084fb60eb6be382a8750a344eb425404f5162e8ae3db9a15ef555a7942b85
  16. 0x0f8977bd16865247451d1ee836b084081d3d0cd17d6a07353fad0c70393c7403
  17. 0xe08e8bd91858a8a10c46ecde9c29a6288b960987303173c5e882afb46ce91fa0
  18. 0xe6cfe00ae4e02bc12327e45b5f3334ea5850ba3bcc8e3101d30a8189856a95af
Day root
0x2c19037464cc4c493624565f01775d6446fc78eaa118fc6865bfe2bfca9ff78e
Chained
0xd1d7dee8322ceff8f4c8d83aa1fe4a4466825c2af1c97dbde3d35db61234f7be
Published
On Arc Testnet, block 69584042: 0x8bae2b1d097834c8b458513862d70d29ee807e98dc2e863b27250131c15b35ae

How to check it · This row as JSON