Evidence row 264637

What was observed

{
  "count": 4,
  "tools": [
    {
      "description": "Convert a volume of water (mL) into everyday comparisons: teaspoons, 500 mL bottles, shower time,\nand lifecycle items (A4 sheet, almond, cup of tea, beef burger), plus the number of typical AI text\nprompts it equals. Includes the boundary caveat that lifecycle footprints are not like-for-like.",
      "inputSchema": {
        "properties": {
          "water_ml": {
            "title": "Water Ml",
            "type": "number"
          }
        },
        "required": [
          "water_ml"
        ],
        "title": "compare_water_useArguments",
        "type": "object"
      },
      "name": "compare_water_use"
    },
    {
      "description": "Estimate the water (mL) and energy (Wh) used by chat-style AI prompts (ChatGPT, Claude, Gemini etc.).\n\nqueries_per_day: prompts per day. usage: 'simple' (text chat, ~0.34 Wh/prompt), 'mixed' (~1 Wh),\n'intensive' (image generation / deep reasoning, ~3 Wh). boundary: 'onsite' (data-centre cooling only,\nas vendors report) or 'comprehensive' (adds water used to generate the electricity – the wider boundary\nmost researchers use). days: number of days to total over (e.g. 250 workdays, 365).\nReturns per-prompt, per-day and total figures with everyday equivalents, assumptions and a source link.\nFor agentic/coding sessions use estimate_session_footprint instead.",
      "inputSchema": {
        "properties": {
          "boundary": {
            "default": "comprehensive",
            "enum": [
              "onsite",
              "comprehensive"
            ],
            "title": "Boundary",
            "type": "string"
          },
          "days": {
            "default": 1,
            "title": "Days",
            "type": "integer"
          },
          "queries_per_day": {
            "title": "Queries Per Day",
            "type": "number"
          },
          "usage": {
            "default": "simple",
            "enum": [
              "simple",
              "mixed",
              "intensive"
            ],
            "title": "Usage",
            "type": "string"
          }
        },
        "required": [
          "queries_per_day"
        ],
        "title": "estimate_ai_footprintArguments",
        "type": "object"
      },
      "name": "estimate_ai_footprint"
    },
    {
      "description": "Estimate the water and energy of an AI session (e.g. an agent or coding-assistant run) from its token\nusage. Pass the SUM across all model calls: input_tokens (uncached prompt tokens), output_tokens\n(including any reasoning/thinking tokens) and cached_input_tokens (prompt-cache reads). model_class:\n'small' (Haiku/mini/Flash-class), 'frontier' or 'reasoning'. Returns a central estimate and a 0.3x–3x\nrange – this is an order-of-magnitude estimate calibrated to published per-prompt figures, not a\nmeasurement.",
      "inputSchema": {
        "properties": {
          "boundary": {
            "default": "comprehensive",
            "enum": [
              "onsite",
              "comprehensive"
            ],
            "title": "Boundary",
            "type": "string"
          },
          "cached_input_tokens": {
            "default": 0,
            "title": "Cached Input Tokens",
            "type": "integer"
          },
          "input_tokens": {
            "title": "Input Tokens",
            "type": "integer"
          },
          "model_class": {
            "default": "frontier",
            "enum": [
              "small",
              "frontier",
              "reasoning"
            ],
            "title": "Model Class",
            "type": "string"
          },
          "output_tokens": {
            "title": "Output Tokens",
            "type": "integer"
          }
        },
        "required": [
          "input_tokens",
          "output_tokens"
        ],
        "title": "estimate_session_footprintArguments",
        "type": "object"
      },
      "name": "estimate_session_footprint"
    },
    {
      "description": "Return the per-prompt energy and water figures, accounting boundaries, sources, limitations, a\ncitation line, and the reasons published AI water estimates differ by ~100x (0.3 mL to 50 mL per prompt).\nUse it to explain or check a published AI water or energy figure.",
      "inputSchema": {
        "properties": {},
        "title": "get_methodologyArguments",
        "type": "object"
      },
      "name": "get_methodology"
    }
  ]
}

What the leaf hashes

{"body":"8beb8a98706260be920f6192f54e2f0a589f1885d22db63b53b2a8992ba8c476","id":264637,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793034321084597,"prev":null,"subject":"4cc5be62-ca9f-4092-9943-246e72a7718e","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. 0x7d19494d06c12255fb70112e742cf240dff48c98a852e8276754d85f25a67ac0
2. 0xfb575d24951c369be91aabad1e2d1b994b55f46673dcef2d518fe89f46de8c8e
3. 0x07a73cfd2220e2345b392f1745b008b102baf0309257933c3c2d729e53fbb0cd
4. 0x19ecfda283dacba0a3c58ecba8fcf66597b6e2a4823fcb8ba07e408a890d491d
5. 0x2fa527b1d4324360a578197e55364ee21d91130b9470fcd31610903a19b937c7
6. 0x5297f1fcf43c983d59dc50fc7f782364125bf466968a8fb4ebddae9b27b3d28c
7. 0xb7392e24404c3e722f0d32536c363562e0da4429dfe6ec0dc805b8261db68a0a
8. 0xb6ad5ba14232f23ff30fb6b9fe383205836e99b8885d9cedab333b250ef72972
9. 0x7e1ec73780098fac490af117915a41a976dff267e71b952d3a320caa7180a1e1
10. 0x27bb9eefd00206cde7209859f541e1ae68cb3baba4968278bfa6a4028b0fe719
11. 0x05b818019343d04f2973b36329a447f88301721891653961b94822610edda553
12. 0x779c77295186b32da6387dfb36d3a76522e7d713472a7cebed7c93529ccc4be6
13. 0x0bffb634300aa5609bddaa79e8d31d7cde36c0a5a4465472f809b9f5287e40d2
14. 0x7721d38652b6444b18e1193824e50490ade04851ce6221771f6e374c4527d80f
15. 0x15039087bf60ae9b06b756ec3cbc299760e59923a438bbd91e34d105186db0ed
16. 0x2b6e23e3624a1b66e1d2298cfbce99a93ce6b13d24a58112a71802d79c5f7a76
17. 0xd21942ae3214eff88e08ab04884fd4b11958b51af9a0741b7668e2d07a2c56c9
18. 0x9a9024edb5069d88a324facb310a5ce8e495214bbaa968f077bede437390194f
19. 0x9b9ce5b74b9bab5121612ef6b64920a8d453cbf311096a423eef9702747e868a

Day root

0xf43e8dcc3d451a4788b26be904c55e8c4c0fa75c9666796c51db38d37e2c0df8

Chained

0x702d5ac508f08b0d1accf36af25822d8e5660367494edd17a642fb61e158a57a

Published

On Arc Testnet, block 69251483: 0x495162f8936e19f0039918feebe6c307f327cd6bf8c37219620b1970041fa9ae