Evidence row 569762

What was observed

{
  "count": 8,
  "tools": [
    {
      "description": "Aggrometer's signature metric: aggro = live Twitch viewers / concurrent Steam players, same hour, per game (min 500 players). Above 1.0 means more people watch than play — spectacle games, watch-to-learn genres. A sudden aggro jump is an early attention signal.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "genre": {
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "aggro_board"
    },
    {
      "description": "Full profile of one game by Steam app id: hourly player history, Twitch viewer history, daily viewer-hours, price/discount history, top-seller rank appearances, clips-per-day virality, review counts and review-activity buckets back to launch, Wikipedia pageview history (monthly since 2018 + daily), developer news velocity, achievement-completion depth, and metadata (genres, developer, publisher). Use search_games first if you only know the name.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "app_id": {
            "description": "Steam app id, e.g. 1623730 for Palworld",
            "type": "integer"
          }
        },
        "required": [
          "app_id"
        ],
        "type": "object"
      },
      "name": "game_detail"
    },
    {
      "description": "Every Steam genre aggregated: game count, combined players, combined live viewers, genre-level aggro ratio, and combined hype (anticipation) of the genre's unreleased games. The whitespace signal: high players + low hype = an underserved genre; low players + high hype = a wave arriving.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {},
        "type": "object"
      },
      "name": "genre_rollup"
    },
    {
      "description": "Warehouse status: how many games are tracked, hours of history recorded, snapshot counts, and data freshness timestamps. Call this first to understand data coverage.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {},
        "type": "object"
      },
      "name": "get_summary"
    },
    {
      "description": "Aggrometer Anticipation Index: top-wishlisted unreleased Steam games scored with pre-release Twitch attention and Wikipedia attention surges (score = wishlist-rank points + log-scaled live viewers + log-scaled pageview surge vs 30-day average). A relative index - compare games against each other; week-over-week change is the launch-anticipation signal.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {},
        "type": "object"
      },
      "name": "hype_board"
    },
    {
      "description": "Find games in the tracked catalog by name (substring match). Returns app ids for use with game_detail, plus current player counts.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "query": {
            "minLength": 2,
            "type": "string"
          }
        },
        "required": [
          "query"
        ],
        "type": "object"
      },
      "name": "search_games"
    },
    {
      "description": "Top 100 games by current Steam concurrent players (updated hourly). Optionally scoped to one Steam genre.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "genre": {
            "description": "Steam genre name, e.g. 'Action', 'RPG', 'Strategy' (exact match; see genre_rollup for the list)",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "top_played"
    },
    {
      "description": "Top 100 games by current live Twitch viewership (15-min updates). Optionally scoped to one Steam genre.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "genre": {
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "top_watched"
    }
  ]
}

What the leaf hashes

{"body":"fd9712f04f2d7a08d85ec500dfcd1c147b5358e0005183e23924f82569b25634","id":569762,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793139498575540,"prev":null,"subject":"b7a4371b-1a89-4772-9c61-d362923e6b9d","subject_kind":"endpoint"}

Proof

Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of 2026-10-27 (273461 rows).

1. 0xf9fc8d167e4438dd5b43d1f2d8c401e02db7793d1c231365546d8e8696cb56cf
2. 0xc3922e91d320b9c00f393a7636d15a3654aa63e4626e07e3c1e5e6d1314eeb59
3. 0x10bbe24bc0affd55282b72efb1799bade786ce4c4ef4b484a409e278e7273499
4. 0x5da23fd0011f8e6fbd8bee0811765dbf38b95470c865ee35c3565608097a8bea
5. 0x86830ae0e9b376ea0e29204bf013e921769de1ad42cbb2c6e7fb46f516b456e0
6. 0x3119d1007bf9827f3aae819574b579095643bc39564ffce6a92aa0ca40fca6b9
7. 0x866761b527534e1641e4525964db3fc0cd42dac1040d88d5e246709169e9505b
8. 0x00baaad2db6bc987e4ca7f34dc517e8a438c90d84212b3ae7a8f79bc535c8a71
9. 0x22296b59060147fa326ef487e78840aa7a3beca9a9fa418f2f5e7009c14947c5
10. 0x3f753238d34d960f4019aebe8c972d7e10ee2d26eea6fcefef5aba9b96cf5fed
11. 0x38d8d177d48b033acf33474f44cf1a36a3cfaa58563d48c7d92671c34bb12589
12. 0x58215df828d47943a710362ab6e17ad0eb4a7c42a13dbec3ab2635d1abf3945f
13. 0xf24b37f8ac293f5328e3e6b28cf868989fe99debf025c153c0d9a1698e846e25
14. 0x94d3785ce9330e4580bccada5459380aa2aac76a0bf11354d1353b375afc17d2
15. 0xb5b652bba4a5afca56c21031d89b1c06361563aaf54ccc8541c296ceeb2b66fa

Day root

0xdd77e5e99da32c3f154180d63e3c3e6fe11e896a2c6896412ef6b5c4bcf7e795

Chained

0x23bb4dfd09f55c15ac3962f53578e02c6114d5bfd9bb451cf8794fb6e2817ef4

Published

On Arc Testnet, block 69414147: 0xb2ebd83aafeb765a0ce66e76aefb133ed06606c98038fd56191e2bcd1dcb77b4