Evidence row 1054404

What was observed

{
  "count": 6,
  "tools": [
    {
      "description": "Which tracked models run on a given GPU or Mac: measured GGUF weights + computed context cache + runtime overhead versus usable memory. Returns the best recommendation and every verdict (EXCELLENT/GOOD/TIGHT/OFFLOAD_REQUIRED/NOT_RECOMMENDED/UNKNOWN) with plain-language reasons. Get hardware ids from list_hardware.",
      "inputSchema": {
        "$schema": "https://json-schema.org/draft/2020-12/schema",
        "properties": {
          "context": {
            "description": "Context length in tokens (default 8192).",
            "maximum": 1048576,
            "minimum": 512,
            "type": "integer"
          },
          "hardware": {
            "description": "Hardware id or page slug, e.g. rtx-4090, mac-studio-m3-ultra-96gb.",
            "type": "string"
          },
          "kv": {
            "description": "KV-cache quantization (default f16).",
            "enum": [
              "f16",
              "q8_0",
              "q4_0"
            ],
            "type": "string"
          },
          "model": {
            "description": "Restrict to one model slug.",
            "type": "string"
          }
        },
        "required": [
          "hardware"
        ],
        "type": "object"
      },
      "name": "find_fit"
    },
    {
      "description": "Median verified on-demand rental price per GPU class on Vast.ai (USD per hour), with min/p75 and offer counts, the collection timestamp, and per class the Rent Index: this week's median against last week and against the first week collected, a trend word, and the days excluded as marketplace glitches, plus RunPod's lowest posted on-demand price per class (a list price, not a median), Clore.ai's median for the same class (a second marketplace, never blended), and the AWS, Azure and Oracle Cloud pay-as-you-go list prices per GPU-hour, each with the instance type, VM size or bare-metal shape the price sits in (list prices, read four times a day, no statement about capacity). The index describes what prices did; it never forecasts.",
      "inputSchema": {
        "$schema": "https://json-schema.org/draft/2020-12/schema",
        "properties": {},
        "type": "object"
      },
      "name": "gpu_prices"
    },
    {
      "description": "Curated GPU and Mac profiles the fit engine knows — ids, memory, usable memory after margins, bandwidth. Use an id with find_fit.",
      "inputSchema": {
        "$schema": "https://json-schema.org/draft/2020-12/schema",
        "properties": {},
        "type": "object"
      },
      "name": "list_hardware"
    },
    {
      "description": "Daily price history per GPU class and source, up to 90 days: the rows the Rent Index and the 30-day range are computed from. Marketplace days (Vast.ai, Clore.ai) are medians over the day's counted hourly medians with min, p75 and offer count; list-price days (RunPod, AWS, Azure, Oracle Cloud, Lambda, Nebius, CoreWeave, Hyperstack) carry the posted price. Each row says which kind it is; never blend the two. Describes what prices did; it never forecasts.",
      "inputSchema": {
        "$schema": "https://json-schema.org/draft/2020-12/schema",
        "properties": {
          "days": {
            "description": "Days back from today (default 30, max 365; the series starts 26 August 2026).",
            "maximum": 365,
            "minimum": 1,
            "type": "integer"
          },
          "gpu": {
            "description": "One class by slug or name, e.g. rtx-4090, h100. Every class without it.",
            "type": "string"
          },
          "source": {
            "description": "One source key, e.g. vast, runpod, aws. Every published source without it.",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "price_history"
    },
    {
      "description": "Tracked AI models ranked by Heat Score (0–100, weighted percentiles of measured Hugging Face/OpenRouter signals) with the raw signals, local-run facts (GGUF size, quantization) and links. Models still collecting a week of history have heat=null and rank after scored ones.",
      "inputSchema": {
        "$schema": "https://json-schema.org/draft/2020-12/schema",
        "properties": {
          "limit": {
            "description": "How many models to return (default 12).",
            "maximum": 100,
            "minimum": 1,
            "type": "integer"
          },
          "slug": {
            "description": "Return a single model by slug.",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "trending_models"
    },
    {
      "description": "The current pick of the week: one tracked model chosen by a published rule (largest counted Heat Score rise among models that run comfortably on a consumer card of up to 24 GB), with the numbers frozen at selection time, a device-by-device fit ladder and the written report including its caveats. Pass week (e.g. 2026-w37) for a past issue. issue is null until the first issue is published.",
      "inputSchema": {
        "$schema": "https://json-schema.org/draft/2020-12/schema",
        "properties": {
          "week": {
            "description": "ISO week label of a past issue, e.g. 2026-w37 (default: the current issue).",
            "pattern": "^\\d{4}-w\\d{2}$",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "weekly_pick"
    }
  ]
}

What the leaf hashes

{"body":"83de1d4060643c2fb6823aa521769be2a9b206424944f92df2baa9b969209c7f","id":1054404,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793314939454837,"prev":564873,"subject":"25c66ffe-c1e8-4726-8e78-6cf4d2185008","subject_kind":"endpoint"}

Proof

Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of 2026-10-29 (242798 rows).

1. 0x3960fe6ecc05f3657fe2ed061266cd5c08741041d1abec609debfcb8e7c3188a
2. 0xdb598e82c0633b89d12bef900176e3403a2993cedd061134317cf032ecb9563c
3. 0x69a1f92cad573d0f9e244aca05b46073d7d58617348c9068ba1a740e1bfeece4
4. 0xaf2a993bd08f5bea7198d36110493a98142b99155dceb3c408aae87fb2bfadf9
5. 0x439a33d2777063368a7f7d837c529ec3de2ed24f2d683d4a63dd6d9d3719d161
6. 0x914193fc600961a88c64f4237d32f4bdacadb91f3d32576092722052b23cbe17
7. 0x62b72bddc53d0ad56a4adde6292fb7075e7e26671d960ce58106bfecae8eea8c
8. 0x52e97577ea414c411dce08fc4e1b66bb3546e8ee6344e1c9ef86bd235cfe4f9f
9. 0x1d9855b3ebb8421232ddbf101926d9473479518cd817877d09927cafb4163ba7
10. 0xcb8ed52989dab9f648336093523eba98c39b00817e1fcae6de77085d40d1b39c
11. 0xec762f4c2d03974f74a7f1bf16368606eb68a80f1928758498bcd47dfbc281c6
12. 0x323c003b20088ff5fc994bd02dcef5bb060fb6e3c817a34b4c86849e5240cf52
13. 0x4b7bfa7784180e2ff8d66e25e97761344643b8692c744c82acf0f77be5670a82
14. 0x14b86aca7e0af6917fa29c5b89b8f3eab1f2340a671c3d06e6ac6a34fd3a07ee
15. 0xa03bd318a195be3bd16f335c7e189443bea4f1f439087a7ac19afec9fa97f9be
16. 0x1c3764b490d23b94e5ac838c89f8d3850dedb0819196f367da2479c7a88bf2c0
17. 0xd76435ead496863d8b0bfab3434f54cd11da3c49d104fc4064b9cb3381567bbd
18. 0xd56e61af23709ed9f460471e3c08400c0142ee83e1fd9057e46350d12edf9c07

Day root

0xc050555c6b023f2aefb6536efb9f0760b92c30a0d06c572b7daf63db259ea17c

Chained

0x4cde8bae2042512e1bec11650628f0293556311cc4ea74d99ffddf02b671a7d6

Published

On Arc Testnet, block 69753317: 0x9e85c340732f416e431b111fae72f7624870125f7f379af2732eb6c2ba8cf6a1