Evidence row 1222757

What was observed

{
  "count": 4,
  "tools": [
    {
      "description": "Audits a website URL or domain for AI crawler access (GPTBot, OAI-SearchBot, PerplexityBot, ClaudeBot), 25,000-token HTML RAG truncation, /llms.txt presence, Schema.org JSON-LD entities, and Google Lighthouse 13.5 Agentic Browsing (/.well-known/ai-catalog.json ARD 1.0). Use this tool first when diagnosing why a site is omitted or misquoted by ChatGPT, Perplexity, or Claude. Do not use this tool to extract full-page Markdown content (use extract_byte0_markdown instead) or to generate static manifest files (use generate_ai_manifests instead). Read-only network check; requires no API key.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "url": {
            "description": "Fully qualified HTTPS URL or bare domain name to audit (e.g., \"https://stripe.com/pricing\" or \"example.com\"). Defaults to HTTPS if scheme is omitted.",
            "type": "string"
          }
        },
        "required": [
          "url"
        ],
        "type": "object"
      },
      "name": "audit_ai_readiness"
    },
    {
      "description": "Strips React/Next.js hydration scripts, Shopify Liquid/WordPress DOM bloat, and inline SVGs/CSS from any URL, returning clean Byte-0 GitHub-Flavored Markdown (GFM) with front-loaded Schema.org tables. Use this tool when you need to read a web page or pricing table inside an LLM context window without exceeding the 25,000-token truncation limit. Do not use this tool if you only need a diagnostic readiness score or robots.txt check (use audit_ai_readiness instead). Read-only HTTP extraction; requires no API key.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "url": {
            "description": "Fully qualified URL of the web page to convert into Byte-0 Markdown (e.g., \"https://vercel.com/pricing\").",
            "type": "string"
          }
        },
        "required": [
          "url"
        ],
        "type": "object"
      },
      "name": "extract_byte0_markdown"
    },
    {
      "description": "Compiles ready-to-save /llms.txt documentation index and Google Lighthouse 13.5 /.well-known/ai-catalog.json (ARD 1.0) JSON manifests from a live domain, plus HTML <head> and robots.txt Agentmap snippets. Use this tool when a developer wants to remediate missing discovery manifests identified by audit_ai_readiness. Do not use this tool for general web scraping (use extract_byte0_markdown instead). Read-only synthesis; requires no API key and does not modify remote servers.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "domain": {
            "description": "Target domain name or root URL to generate manifests for (e.g., \"example.com\" or \"https://example.com\").",
            "type": "string"
          }
        },
        "required": [
          "domain"
        ],
        "type": "object"
      },
      "name": "generate_ai_manifests"
    },
    {
      "description": "Retrieves empirical benchmark telemetry from the 2026 50-Site SaaS & E-Commerce AI Truncation Study (measuring raw HTML token weight, 25,000-token Perplexity/ChatGPT cutoff truncation, visible price omission, /llms.txt adoption, and Lighthouse 13.5 ARD 1.0 adoption). Use this tool when comparing a site against industry peers (such as Stripe, Vercel, Datadog, or Shopify) or answering research questions about the Static /llms.txt Paradox. Do not use this tool to run a live scan on an arbitrary unbenchmarked URL (use audit_ai_readiness instead). Read-only benchmark lookup; requires no API key.",
      "inputSchema": {
        "additionalProperties": false,
        "properties": {
          "domain": {
            "description": "Optional domain name (e.g., \"stripe.com\" or \"vercel.com\") to filter the benchmark study. Omit or pass empty string to return the full 50-site statistical summary.",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "query_truncation_benchmark"
    }
  ]
}

What the leaf hashes

{"body":"7ece8266f3a91f3a4d00d903f0753711138c35b416e7ef725f98a88ca5be8e13","id":1222757,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793319908201521,"prev":null,"subject":"fc940b87-db67-420e-9f54-0f1cf5dedd5a","subject_kind":"endpoint"}

Proof

Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of 2026-10-30 (243099 rows).

1. 0xc3e4e85ee29f22353a5d4e6ba70bf7caacaee2068f4e20a082451007bcd5b88e
2. 0xb066e1de0b9147646074fd5efd2b7fca6ba307ba46b60f4a42bd2c6a6f154cb7
3. 0x3fd1905ea54b2cbbb5b481a1a06e822a7fec8b440061d595de26fab0cd774beb
4. 0xbbaacfdffb4bcc1de77ad7f06ab4d6ce32b058aaa41ad2221ade2343183db3a3
5. 0x5e5ee03b8b153bd56f1f0a91c2a08a30ce3673cd4d510b8707433841a7e94fdf
6. 0x5a14304b017b1ca5e7c65cb4b51ff848c4b35b9d8abc919307ea1794baf6f3e1
7. 0x35e3922826e777064dfc6ce4af31ff5588ce7177cc6b883b348f14d04140635d
8. 0xe412b70f570302a9544c86fe2dac476607e936a54ce6a3f7de2c77b0e5175004
9. 0x0a39d25ec478c58477d8baaf9955d178997a419d5e2d8fbfe72ad7d15c084106
10. 0xe90d52ba6cfa2a3fb9155200cbf934779b3a3e2dc770976fbb9311017f984717
11. 0x1ffb5959cab188148a2c047208237bed6c52b131de21c82461feb1868d714a63
12. 0x9fb1119d8b5095fdcdaef00d4f92ce423ad5d224a8ecf628aca8fa9c35c3dc5e
13. 0x471b09add521b98a16ea9fc9d6a9b0d36c3550dc29ba4c83971dbd67d002d009
14. 0x342f35813d736e85ba1881bcb69ecc7b4b96d68e557b8417f1f4ec705ab16ab6
15. 0x9fb4eebd924fd42d4eb61d55691812de0db9242fc9c0dabb65c4054447246797
16. 0x0c59b8770d2782eb535aefbb9b2f6810bab4757f51b37e00f5147713a1de9481
17. 0x61ef83255d34604cb052882568ca1d1386ac3cfb8284509715bc1734cff77831
18. 0x0c43c73b62a5d49ee1444b5dc4195fc5b16b141d3f4458e2e9fbd5fd6ecb367d

Day root

0x0826c7ad6039e06a2360ca0a4a3a4fe7f2626c6dc19f71a37599386f78b39875

Chained

0x36b4c8a1063758f0b8765fa1bdf75fa92fb543cc183add3e261880ee2bd1f822

Published

On Arc Testnet, block 69923247: 0x8704744146c6967c8abc9e9a99de4db7283b29e840922ea83a69b6fe776e6861