addrbookFor publishers
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Evidence row 574560

Observed , by probe.mcp/1.

Kind
mcp.tools
About
endpoint c4096c17-204d-4ebc-8567-746b3f5c93f6
Recorded
Previous row
None: the first of its kind about this subject
Body SHA-256
f1631e9415ac2874776c9dc2742d35898fbab9b575e58b475e6ab587ffa6594f
Leaf
0x1676082d7fb89073f54370b31e0326231a418ecdc9378b86d30d6a4e826bbdd3

What was observed

{
  "count": 26,
  "tools": [
    {
      "description": "Call any public A2A-compatible agent directly by its endpoint URL.\n\n    Returns the agent's response immediately (synchronous — no task_id needed).\n    Get agent_url values from discover_agents (look for ENDPOINT in results).\n    Works with any agent on a2aregistry.org or any A2A JSON-RPC endpoint.\n    Free, no login required.\n\n    Args:\n        agent_url: The A2A endpoint URL (from discover_agents ENDPOINT field).\n        message: The message or task to send to the agent.\n        context_id: Optional — pass the context_id from a prior response to continue a multi-turn conversation.\n        timeout_seconds: Seconds to wait for a response (default 30, max 120).\n    ",
      "inputSchema": {
        "properties": {
          "agent_url": {
            "title": "Agent Url",
            "type": "string"
          },
          "context_id": {
            "default": "",
            "title": "Context Id",
            "type": "string"
          },
          "message": {
            "title": "Message",
            "type": "string"
          },
          "timeout_seconds": {
            "default": 30,
            "title": "Timeout Seconds",
            "type": "integer"
          }
        },
        "required": [
          "agent_url",
          "message"
        ],
        "title": "a2a_call_agentArguments",
        "type": "object"
      },
      "name": "a2a_call_agent"
    },
    {
      "description": "Performs goal-oriented web navigation to complete tasks using a browser tool. Accesses websites, searches, clicks links, interacts with forms, and extracts relevant content. Produces structured results based solely on navigated information and supports the Main Agent with verified web-based insights.\nExpected Runtime: ~30s.",
      "inputSchema": {
        "$defs": {
          "AgentPayload_210913b8": {
            "additionalProperties": true,
            "properties": {
              "task_description": {
                "description": "",
                "title": "Task Description",
                "type": "string"
              }
            },
            "required": [
              "task_description"
            ],
            "title": "AgentPayload_210913b8",
            "type": "object"
          }
        },
        "properties": {
          "payload": {
            "$ref": "#/$defs/AgentPayload_210913b8"
          }
        },
        "required": [
          "payload"
        ],
        "title": "dynamic_handlerArguments",
        "type": "object"
      },
      "name": "browsernavigationagent"
    },
    {
      "description": "Plan complete camping trips based on destination, weather, experience level, group size, budget, and activities. Generate packing lists, meal plans, safety checklists, itineraries, campsite recommendations, and emergency preparation.\nExpected Runtime: ~30s.",
      "inputSchema": {
        "$defs": {
          "AgentPayload_a1585e09": {
            "additionalProperties": true,
            "properties": {
              "activities": {
                "default": null,
                "description": "",
                "title": "Activities",
                "type": "string"
              },
              "budget": {
                "default": null,
                "description": "",
                "title": "Budget",
                "type": "number"
              },
              "children": {
                "default": null,
                "description": "",
                "title": "Children",
                "type": "string"
              },
              "destination": {
                "description": "",
                "title": "Destination",
                "type": "string"
              },
              "experience": {
                "description": "",
                "title": "Experience",
                "type": "string"
              },
              "people": {
                "description": "",
                "title": "People",
                "type": "number"
              },
              "pets": {
                "default": null,
                "description": "",
                "title": "Pets",
                "type": "string"
              },
              "session": {
                "default": null,
                "description": "",
                "title": "Session",
                "type": "string"
              },
              "transport": {
                "default": null,
                "description": "",
                "title": "Transport",
                "type": "string"
              },
              "trip_days": {
                "description": "",
                "title": "Trip Days",
                "type": "number"
              }
            },
            "required": [
              "people",
              "trip_days",
              "experience",
              "destination"
            ],
            "title": "AgentPayload_a1585e09",
            "type": "object"
          }
        },
        "properties": {
          "payload": {
            "$ref": "#/$defs/AgentPayload_a1585e09"
          }
        },
        "required": [
          "payload"
        ],
        "title": "dynamic_handlerArguments",
        "type": "object"
      },
      "name": "campbuddy"
    },
    {
      "description": "Analyzes complex approaches and strategies by identifying strengths and weaknesses. Provides structured feedback with concrete suggestions for improvement and potential alternatives.\nExpected Runtime: ~30s.",
      "inputSchema": {
        "$defs": {
          "AgentPayload_06e6b8d5": {
            "additionalProperties": true,
            "properties": {
              "approache/strategie": {
                "description": "",
                "title": "Approache/Strategie",
                "type": "string"
              }
            },
            "required": [
              "approache/strategie"
            ],
            "title": "AgentPayload_06e6b8d5",
            "type": "object"
          }
        },
        "properties": {
          "payload": {
            "$ref": "#/$defs/AgentPayload_06e6b8d5"
          }
        },
        "required": [
          "payload"
        ],
        "title": "dynamic_handlerArguments",
        "type": "object"
      },
      "name": "constructivecritic"
    },
    {
      "description": "Find agents to call — both platform agents and public A2A registry agents.\n\n    Returns two types:\n    • TYPE=platform — built-in agents, call via their MCP tool name (async, returns task_id → use wait_for_task)\n    • TYPE=a2a_registry — public agents from a2aregistry.org, call via a2a_call_agent(agent_url=ENDPOINT, message='...') (sync, returns immediately)\n\n    Registry agents are filtered by the registry's own is_healthy flag.\n    Each result shows UPTIME and LATENCY from the registry's own reported metrics.\n\n    Free.\n\n    Args:\n        query: Keywords to filter by capability (e.g. 'weather', 'web scraping', 'research'). Leave empty to browse top agents.\n        limit: Max results to return (default 10, max 25).\n    ",
      "inputSchema": {
        "properties": {
          "limit": {
            "default": 10,
            "title": "Limit",
            "type": "integer"
          },
          "query": {
            "default": "",
            "title": "Query",
            "type": "string"
          }
        },
        "title": "discover_agentsArguments",
        "type": "object"
      },
      "name": "discover_agents"
    },
    {
      "description": "Agent created via direct DB write\nExpected Runtime: ~30s.",
      "inputSchema": {
        "$defs": {
          "AgentPayload_96b6478e": {
            "additionalProperties": true,
            "properties": {},
            "title": "AgentPayload_96b6478e",
            "type": "object"
          }
        },
        "properties": {
          "payload": {
            "$ref": "#/$defs/AgentPayload_96b6478e"
          }
        },
        "required": [
          "payload"
        ],
        "title": "dynamic_handlerArguments",
        "type": "object"
      },
      "name": "exploitagent"
    },
    {
      "description": "full financial agent\nExpected Runtime: ~60s.",
      "inputSchema": {
        "$defs": {
          "AgentPayload_eb4f8b51": {
            "additionalProperties": true,
            "properties": {
              "financial agent": {
                "description": "",
                "title": "Financial Agent",
                "type": "string"
              }
            },
            "required": [
              "financial agent"
            ],
            "title": "AgentPayload_eb4f8b51",
            "type": "object"
          }
        },
        "properties": {
          "payload": {
            "$ref": "#/$defs/AgentPayload_eb4f8b51"
          }
        },
        "required": [
          "payload"
        ],
        "title": "dynamic_handlerArguments",
        "type": "object"
      },
      "name": "financial_agent"
    },
    {
      "description": "Deconstructs complex tasks or problems using a first-principles approach. Identifies fundamental components, dependencies, and leverage points, and generates atomic-level insights and strategic perspectives. Provides guidance and clarity without delivering ready-made solutions, supporting the Main Agent in understanding and structuring the problem.\nExpected Runtime: ~30s.",
      "inputSchema": {
        "$defs": {
          "AgentPayload_1108d7f2": {
            "additionalProperties": true,
            "properties": {
              "task_description": {
                "description": "",
                "title": "Task Description",
                "type": "string"
              }
            },
            "required": [
              "task_description"
            ],
            "title": "AgentPayload_1108d7f2",
            "type": "object"
          }
        },
        "properties": {
          "payload": {
            "$ref": "#/$defs/AgentPayload_1108d7f2"
          }
        },
        "required": [
          "payload"
        ],
        "title": "dynamic_handlerArguments",
        "type": "object"
      },
      "name": "firstprinciplesanalyst"
    },
    {
      "description": "Fetch a ClawHub skill by slug — metadata plus optional SKILL.md body.\n\n    Use the slug from search_skills results (e.g. 'agent-browser-clawdbot').\n    The response includes version, stats, install command, and the SKILL.md content\n    agents can follow to adopt the skill's behavior.\n\n    Free to use — no API key required.\n\n    Args:\n        slug: ClawHub skill slug (lowercase, from search_skills).\n        include_content: If true (default), include SKILL.md text. Set false for metadata only.\n    ",
      "inputSchema": {
        "properties": {
          "include_content": {
            "default": true,
            "title": "Include Content",
            "type": "boolean"
          },
          "slug": {
            "title": "Slug",
            "type": "string"
          }
        },
        "required": [
          "slug"
        ],
        "title": "get_skillArguments",
        "type": "object"
      },
      "name": "get_skill"
    },
    {
      "description": "Demo agent that echoes back any text query it receives. Useful for testing A2A webhook integrations.\nExpected Runtime: ~10s.",
      "inputSchema": {
        "$defs": {
          "AgentPayload_6c89a029": {
            "additionalProperties": true,
            "properties": {
              "query": {
                "description": "",
                "title": "Query",
                "type": "string"
              }
            },
            "required": [
              "query"
            ],
            "title": "AgentPayload_6c89a029",
            "type": "object"
          }
        },
        "properties": {
          "payload": {
            "$ref": "#/$defs/AgentPayload_6c89a029"
          }
        },
        "required": [
          "payload"
        ],
        "title": "dynamic_handlerArguments",
        "type": "object"
      },
      "name": "hpo_demo_echo_agent"
    },
    {
      "description": "Autonomous strategic analysis framed in NEXUS's lens: competitive positioning, portfolio economics, and defensibility. Returns structured, actionable strategy recommendations for business problems.\nExpected Runtime: ~20s.",
      "inputSchema": {
        "$defs": {
          "AgentPayload_73d7f7a4": {
            "additionalProperties": true,
            "properties": {
              "query": {
                "description": "The business/strategy question to analyze",
                "title": "Query",
                "type": "string"
              }
            },
            "required": [
              "query"
            ],
            "title": "AgentPayload_73d7f7a4",
            "type": "object"
          }
        },
        "properties": {
          "payload": {
            "$ref": "#/$defs/AgentPayload_73d7f7a4"
          }
        },
        "required": [
          "payload"
        ],
        "title": "dynamic_handlerArguments",
        "type": "object"
      },
      "name": "nexus_strategy_analyst"
    },
    {
      "description": "The high-effort reasoning agent is built for complex tasks that require deep, multi-step analysis and robust problem-solving. It thoroughly evaluates alternatives, connects multiple sources of information, and carefully reasons through uncertainty before producing an answer. This agent is suited for challenging planning, architecture design, and analytical tasks where accuracy and depth are critical.\nExpected Runtime: ~60s.",
      "inputSchema": {
        "$defs": {
          "AgentPayload_7ca1324c": {
            "additionalProperties": true,
            "properties": {
              "query": {
                "description": "",
                "title": "Query",
                "type": "string"
              }
            },
            "required": [
              "query"
            ],
            "title": "AgentPayload_7ca1324c",
            "type": "object"
          }
        },
        "properties": {
          "payload": {
            "$ref": "#/$defs/AgentPayload_7ca1324c"
          }
        },
        "required": [
          "payload"
        ],
        "title": "dynamic_handlerArguments",
        "type": "object"
      },
      "name": "reasoningdelegationhigh"
    },
    {
      "description": "A low-effort reasoning agent designed to handle simple to moderate tasks by performing lightweight reflection and structured thinking. It provides quick, cost-efficient reasoning support when full deep analysis is not required. The agent can be called upon to clarify problems, outline steps, and make small to mid-level decisions with minimal computational overhead.\nExpected Runtime: ~45s.",
      "inputSchema": {
        "$defs": {
          "AgentPayload_7bc51e44": {
            "additionalProperties": true,
            "properties": {
              "task": {
                "description": "",
                "title": "Task",
                "type": "string"
              }
            },
            "required": [
              "task"
            ],
            "title": "AgentPayload_7bc51e44",
            "type": "object"
          }
        },
        "properties": {
          "payload": {
            "$ref": "#/$defs/AgentPayload_7bc51e44"
          }
        },
        "required": [
          "payload"
        ],
        "title": "dynamic_handlerArguments",
        "type": "object"
      },
      "name": "reasoningdelegationlow"
    },
    {
      "description": "The medium-effort reasoning agent is designed to handle moderate to complex tasks by applying structured, multi-step thinking and deeper analysis. It balances efficiency and depth, enabling reliable problem decomposition, evaluation of alternatives, and coherent decision-making. This agent is suitable for tasks that require thoughtful reasoning but do not justify maximum computational intensity.\nExpected Runtime: ~50s.",
      "inputSchema": {
        "$defs": {
          "AgentPayload_485b0bc8": {
            "additionalProperties": true,
            "properties": {
              "task": {
                "description": "",
                "title": "Task",
                "type": "string"
              }
            },
            "required": [
              "task"
            ],
            "title": "AgentPayload_485b0bc8",
            "type": "object"
          }
        },
        "properties": {
          "payload": {
            "$ref": "#/$defs/AgentPayload_485b0bc8"
          }
        },
        "required": [
          "payload"
        ],
        "title": "dynamic_handlerArguments",
        "type": "object"
      },
      "name": "reasoningdelegationmedium"
    },
    {
      "description": "Conducts thorough, iterative internet research on a given topic. Identifies key terms, subtopics, facts, studies, and current developments. Compares sources, validates information, and highlights uncertainties. Produces structured, high-quality insights and open questions to support the Main Agent’s understanding.\nExpected Runtime: ~60s.",
      "inputSchema": {
        "$defs": {
          "AgentPayload_8cd8fde5": {
            "additionalProperties": true,
            "properties": {
              "topic": {
                "description": "",
                "title": "Topic",
                "type": "string"
              }
            },
            "required": [
              "topic"
            ],
            "title": "AgentPayload_8cd8fde5",
            "type": "object"
          }
        },
        "properties": {
          "payload": {
            "$ref": "#/$defs/AgentPayload_8cd8fde5"
          }
        },
        "required": [
          "payload"
        ],
        "title": "dynamic_handlerArguments",
        "type": "object"
      },
      "name": "researchagent"
    },
    {
      "description": "Проводит доказательный аудит сайтов по действующему законодательству РФ: сканирует публичные страницы, формы, cookies, документы, платежные сценарии и внешние сервисы, сверяет применимые требования и возвращает отчет с рисками, источниками и готовым планом исправлений для Codex.\nExpected Runtime: ~180s.",
      "inputSchema": {
        "$defs": {
          "AgentPayload_ef3fd7d1": {
            "additionalProperties": true,
            "properties": {
              "url": {
                "description": "",
                "title": "Url",
                "type": "string"
              }
            },
            "required": [
              "url"
            ],
            "title": "AgentPayload_ef3fd7d1",
            "type": "object"
          }
        },
        "properties": {
          "payload": {
            "$ref": "#/$defs/AgentPayload_ef3fd7d1"
          }
        },
        "required": [
          "payload"
        ],
        "title": "dynamic_handlerArguments",
        "type": "object"
      },
      "name": "russian_website_legal_auditor"
    },
    {
      "description": "Executes Python or JavaScript code in an isolated, stateless sandbox to validate, test, or solve tasks. Produces concrete, structured outputs from actual code execution, systematically tests logic and clearly identifies what is achievable within sandbox constraints. Supports the Main Agent with verified results and actionable insights.\nExpected Runtime: ~45s.",
      "inputSchema": {
        "$defs": {
          "AgentPayload_7b98220c": {
            "additionalProperties": true,
            "properties": {
              "task_description": {
                "description": "",
                "title": "Task Description",
                "type": "string"
              }
            },
            "required": [
              "task_description"
            ],
            "title": "AgentPayload_7b98220c",
            "type": "object"
          }
        },
        "properties": {
          "payload": {
            "$ref": "#/$defs/AgentPayload_7b98220c"
          }
        },
        "required": [
          "payload"
        ],
        "title": "dynamic_handlerArguments",
        "type": "object"
      },
      "name": "sandboxcodingagent"
    },
    {
      "description": "Analyzes tasks, questions, or problems strictly from a scientific perspective. Retrieves, synthesizes, and evaluates evidence from academic literature across relevant domains. Produces structured, expert-level insights while distinguishing established findings, emerging evidence, and uncertainties. Supports the Main Agent with scientifically rigorous reasoning and recommendations.\nExpected Runtime: ~60s.",
      "inputSchema": {
        "$defs": {
          "AgentPayload_03375845": {
            "additionalProperties": true,
            "properties": {
              "task_description": {
                "description": "",
                "title": "Task Description",
                "type": "string"
              }
            },
            "required": [
              "task_description"
            ],
            "title": "AgentPayload_03375845",
            "type": "object"
          }
        },
        "properties": {
          "payload": {
            "$ref": "#/$defs/AgentPayload_03375845"
          }
        },
        "required": [
          "payload"
        ],
        "title": "dynamic_handlerArguments",
        "type": "object"
      },
      "name": "scientificresearchagent"
    },
    {
      "description": "Semantically search the live ClawHub skills registry (clawhub.ai).\n\n    ClawHub hosts OpenClaw SKILL.md packages — behavior templates, tool integrations,\n    and agent capabilities. Results include slug, author, summary, install hint, and\n    canonical URL. Follow up with get_skill(slug) to read the full SKILL.md.\n\n    Free to use — no API key required.\n\n    Args:\n        query: Natural language description of the capability you need (e.g. 'browser automation', 'send emails via gmail').\n        top_k: Number of results to return (default: 5, max: 10).\n    ",
      "inputSchema": {
        "properties": {
          "query": {
            "title": "Query",
            "type": "string"
          },
          "top_k": {
            "default": 5,
            "title": "Top K",
            "type": "integer"
          }
        },
        "required": [
          "query"
        ],
        "title": "search_skillsArguments",
        "type": "object"
      },
      "name": "search_skills"
    },
    {
      "description": "Creates a complete home restaurant experience from the household fridge, guest count, cuisine, time and budget. Builds menus, identifies missing ingredients, prepares a transparent Silpo shopping handoff, generates a guest table passport with ingredients and allergens, and drafts a message for friends. Sponsored products are labelled and only shown when relevant.\nExpected Runtime: ~15s.",
      "inputSchema": {
        "$defs": {
          "AgentPayload_0e2d56d3": {
            "additionalProperties": true,
            "properties": {
              "query": {
                "description": "",
                "title": "Query",
                "type": "string"
              }
            },
            "required": [
              "query"
            ],
            "title": "AgentPayload_0e2d56d3",
            "type": "object"
          }
        },
        "properties": {
          "payload": {
            "$ref": "#/$defs/AgentPayload_0e2d56d3"
          }
        },
        "required": [
          "payload"
        ],
        "title": "dynamic_handlerArguments",
        "type": "object"
      },
      "name": "silpo_home_restaurant"
    },
    {
      "description": "Tracks household food inventory, expiry risks and replenishment needs; considers user food restrictions and preferences; prepares transparent product recommendations, a draft Silpo basket and delivery options. Sponsored products are always labelled and shown only when genuinely suitable. Cart changes require explicit user approval.\nExpected Runtime: ~15s.",
      "inputSchema": {
        "$defs": {
          "AgentPayload_883ca260": {
            "additionalProperties": true,
            "properties": {
              "query": {
                "description": "",
                "title": "Query",
                "type": "string"
              }
            },
            "required": [
              "query"
            ],
            "title": "AgentPayload_883ca260",
            "type": "object"
          }
        },
        "properties": {
          "payload": {
            "$ref": "#/$defs/AgentPayload_883ca260"
          }
        },
        "required": [
          "payload"
        ],
        "title": "dynamic_handlerArguments",
        "type": "object"
      },
      "name": "smart_fridge___nutrition"
    },
    {
      "description": "Performs expert-level software engineering analysis to solve tasks using repository and code evidence as the primary source. Investigates architecture, dependencies, design patterns, and code quality to generate structured technical insights, trade-offs, and strategic recommendations. Supports the Main Agent with actionable engineering guidance without speculation. Can't execute code.\nExpected Runtime: ~50s.",
      "inputSchema": {
        "$defs": {
          "AgentPayload_fb62bb71": {
            "additionalProperties": true,
            "properties": {
              "task_desciption": {
                "description": "",
                "title": "Task Desciption",
                "type": "string"
              }
            },
            "required": [
              "task_desciption"
            ],
            "title": "AgentPayload_fb62bb71",
            "type": "object"
          }
        },
        "properties": {
          "payload": {
            "$ref": "#/$defs/AgentPayload_fb62bb71"
          }
        },
        "required": [
          "payload"
        ],
        "title": "dynamic_handlerArguments",
        "type": "object"
      },
      "name": "softwareengineeringexpert"
    },
    {
      "description": "Fundamental Analysis\nExpected Runtime: ~30s.",
      "inputSchema": {
        "$defs": {
          "AgentPayload_f5d1ebd5": {
            "additionalProperties": true,
            "properties": {
              "analysis_type": {
                "description": "",
                "title": "Analysis Type",
                "type": "string"
              },
              "market": {
                "description": "",
                "title": "Market",
                "type": "string"
              },
              "symbol": {
                "description": "",
                "title": "Symbol",
                "type": "string"
              },
              "timeframe": {
                "description": "",
                "title": "Timeframe",
                "type": "string"
              }
            },
            "required": [
              "market",
              "symbol",
              "timeframe",
              "analysis_type"
            ],
            "title": "AgentPayload_f5d1ebd5",
            "type": "object"
          }
        },
        "properties": {
          "payload": {
            "$ref": "#/$defs/AgentPayload_f5d1ebd5"
          }
        },
        "required": [
          "payload"
        ],
        "title": "dynamic_handlerArguments",
        "type": "object"
      },
      "name": "stock_market"
    },
    {
      "description": "Generates structured, iterative execution plans from complex user requests or problems. Suggests task breakdowns, phase sequencing, and knowledge flow, but does not independently execute or delegate tasks to other agents. Supports the Main Agent in preparing actionable plans.\nExpected Runtime: ~30s.",
      "inputSchema": {
        "$defs": {
          "AgentPayload_3b2b67b9": {
            "additionalProperties": true,
            "properties": {
              "task_description": {
                "description": "",
                "title": "Task Description",
                "type": "string"
              }
            },
            "required": [
              "task_description"
            ],
            "title": "AgentPayload_3b2b67b9",
            "type": "object"
          }
        },
        "properties": {
          "payload": {
            "$ref": "#/$defs/AgentPayload_3b2b67b9"
          }
        },
        "required": [
          "payload"
        ],
        "title": "dynamic_handlerArguments",
        "type": "object"
      },
      "name": "taskplanner"
    },
    {
      "description": "Delegates a task to the specialized agent: TestAgent\nExpected Runtime: ~30s.",
      "inputSchema": {
        "$defs": {
          "AgentPayload_00000000": {
            "additionalProperties": true,
            "properties": {},
            "title": "AgentPayload_00000000",
            "type": "object"
          }
        },
        "properties": {
          "payload": {
            "$ref": "#/$defs/AgentPayload_00000000"
          }
        },
        "required": [
          "payload"
        ],
        "title": "dynamic_handlerArguments",
        "type": "object"
      },
      "name": "testagent"
    },
    {
      "description": "Wait for a platform agent task to complete and return its result.\n\n    Only needed when a platform agent tool returned STATUS=RUNNING with a task_id\n    (i.e. the task was still running after the initial 50s inline wait).\n    NOT needed when the tool already returned STATUS=COMPLETED or STATUS=FAILED.\n    NOT needed for a2a_call_agent — that always returns directly.\n\n    Args:\n        task_id: The task UUID from a platform agent response with STATUS=RUNNING.\n        max_wait_seconds: Max seconds to wait (default 45, max 300).\n    ",
      "inputSchema": {
        "properties": {
          "max_wait_seconds": {
            "default": 45,
            "title": "Max Wait Seconds",
            "type": "number"
          },
          "task_id": {
            "title": "Task Id",
            "type": "string"
          }
        },
        "required": [
          "task_id"
        ],
        "title": "wait_for_taskArguments",
        "type": "object"
      },
      "name": "wait_for_task"
    }
  ]
}

What the leaf hashes

{"body":"f1631e9415ac2874776c9dc2742d35898fbab9b575e58b475e6ab587ffa6594f","id":574560,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793141579554316,"prev":null,"subject":"c4096c17-204d-4ebc-8567-746b3f5c93f6","subject_kind":"endpoint"}

Proof

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

  1. 0x1675eb3f2a334da2bd51a86b444d599a995a28064d0a8c8245a9608569f8c379
  2. 0x62310738bf93448b436e74846e23c72e441e75b355075336d0c5fe4def27c8d8
  3. 0xb6be2518bc7da3af502526b5bc4635c10f738f9ea9ed9d0b7864b40428fe847c
  4. 0x604d30c0673ebf115dda79541198740d52f7f6aefb46ebfd750761df202f506f
  5. 0x234b30686c026dfb8f234fa6033b7cd3799a7f9bf050559b4e74071e81ae25f9
  6. 0x411494cc78b45d10ce5fbe45af6c07f19f451dd78cd5a54dfc8a0c34257974ba
  7. 0xa0e62ae168ad6b8694806cdbb2910a5a1057a20a7bbdd7220971db7a20256ecd
  8. 0x81c127da3029e1627058c442baa611cb2aaaeab782eda663c039c02a05d64c35
  9. 0xd776c64064adc662311e1d02faf6081284fd7876c70b633691380fdf2e949018
  10. 0xc474f4cadad9cf875adfb0740e1340dca82d50667d0f0472f73da476abd4880e
  11. 0x55acee356f0b717dd0920b0cde9e99b43bd0a0b1161a35ac6c315aa50f2d66f6
  12. 0x62c7e7967ec467dcf70ca9a9f01831f05b5b4a07c07491cc03340b1479c7ea31
  13. 0xfae7ed2d06f4d6ced86c104b6381c26d795f82be10e6314b53b0524bd75a292f
  14. 0x52c5141da0cbee106a30396ee7d1360fd22f55084aca2ca436c8007892775670
  15. 0x6913cb48392acb8dc5c940dcdb6e6fc889d544f85dff11da249551a5f027e688
  16. 0x518b93854db03dc9fc938883abf30da6eaae5ae0d4336903968fd32a7df8c71b
  17. 0x22c1fb9487ee0b9732fa017a0cc321eb27a60c08450d112f755089796e12cb1c
  18. 0xa20d48798a34aba12eb9c7297722982d910f06c148f5e27ac59307422964a585
  19. 0x9fc354c0ea3efc3f1b6548bb77ea902a50f2c9647647ea61592efce2bd795699
Day root
0xdd77e5e99da32c3f154180d63e3c3e6fe11e896a2c6896412ef6b5c4bcf7e795
Chained
0x23bb4dfd09f55c15ac3962f53578e02c6114d5bfd9bb451cf8794fb6e2817ef4
Published
On Arc Testnet, block 69414147: 0xb2ebd83aafeb765a0ce66e76aefb133ed06606c98038fd56191e2bcd1dcb77b4

How to check it · This row as JSON