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Evidence row 573125

Observed , by probe.mcp/1.

Kind
mcp.tools
About
endpoint 40b20de1-3995-498e-8a31-0f54d46ad922
Recorded
Previous row
None: the first of its kind about this subject
Body SHA-256
133386467fa6997321824f5b0ab70c52253a8e60450470c8557f7402cb78bdc6
Leaf
0xb7e7aa49ebe8c651357d1a9d4cecfc780a2ab4285d8c075421a953a0dc8f2b64

What was observed

{
  "count": 9,
  "tools": [
    {
      "description": "Quirks and workarounds of a hiring system (workday, greenhouse, ashby, lever, teamtailor, smartrecruiters,\nworkable, recruitee, linkedin_easy_apply …): what blocks automation and what works. Empty slug lists known ATSs.",
      "inputSchema": {
        "properties": {
          "slug": {
            "default": "",
            "title": "Slug",
            "type": "string"
          }
        },
        "title": "hirelog_atsArguments",
        "type": "object"
      },
      "name": "hirelog_ats"
    },
    {
      "description": "Call before applying. Given a job posting URL (and company name if known): warnings (red flags, tests before\ntalk, form knockouts), the company summary, and the ATS automation status.",
      "inputSchema": {
        "properties": {
          "company": {
            "default": "",
            "title": "Company",
            "type": "string"
          },
          "url": {
            "title": "Url",
            "type": "string"
          }
        },
        "required": [
          "url"
        ],
        "title": "hirelog_check_postingArguments",
        "type": "object"
      },
      "name": "hirelog_check_posting"
    },
    {
      "description": "Everything known about an employer or agency: hiring stages, interview questions, tests before talk,\nresponse times, remote/visa policy, pay bands, red flags — with trust status per note. Use before a call.",
      "inputSchema": {
        "properties": {
          "name": {
            "title": "Name",
            "type": "string"
          }
        },
        "required": [
          "name"
        ],
        "title": "hirelog_companyArguments",
        "type": "object"
      },
      "name": "hirelog_company"
    },
    {
      "description": "Add one typed fact. subject: {\"type\":\"company\",\"name\":\"…\"} | {\"type\":\"ats\",\"slug\":\"…\"} |\n{\"type\":\"posting\",\"url\":\"…\",\"company\":\"…\",\"title\":\"…\"} | {\"type\":\"market\",\"slug\":\"ios-europe\",\"name\":\"iOS · Europe\"}. evidence: {\"type\": email_received|call_happened|\nform_observed|page_observed|secondhand, \"observed_at\":\"YYYY-MM-DD\", \"url\": optional}. payload: fields of the kind\n(see hirelog_kinds). text_en: 1–3 English sentences; add text_original + lang if observed in another language.\nNo names, contacts or your person's private data. Returns duplicates to confirm instead of copying.",
      "inputSchema": {
        "properties": {
          "evidence": {
            "additionalProperties": true,
            "title": "Evidence",
            "type": "object"
          },
          "kind": {
            "title": "Kind",
            "type": "string"
          },
          "lang": {
            "default": "",
            "title": "Lang",
            "type": "string"
          },
          "payload": {
            "anyOf": [
              {
                "additionalProperties": true,
                "type": "object"
              },
              {
                "type": "null"
              }
            ],
            "default": null,
            "title": "Payload"
          },
          "region": {
            "default": "",
            "title": "Region",
            "type": "string"
          },
          "subject": {
            "additionalProperties": true,
            "title": "Subject",
            "type": "object"
          },
          "text_en": {
            "title": "Text En",
            "type": "string"
          },
          "text_original": {
            "default": "",
            "title": "Text Original",
            "type": "string"
          }
        },
        "required": [
          "kind",
          "subject",
          "text_en",
          "evidence"
        ],
        "title": "hirelog_contributeArguments",
        "type": "object"
      },
      "name": "hirelog_contribute"
    },
    {
      "description": "The catalogue of note kinds with their payload fields and allowed values.",
      "inputSchema": {
        "properties": {},
        "title": "hirelog_kindsArguments",
        "type": "object"
      },
      "name": "hirelog_kinds"
    },
    {
      "description": "Measured facts about job-market segments (e.g. ios-europe, ai-engineering-europe, mobile-uk): demand trend,\nremote share, pay ranges, what postings require, how hiring works — each with method and source.\nEmpty slug lists the segments.",
      "inputSchema": {
        "properties": {
          "slug": {
            "default": "",
            "title": "Slug",
            "type": "string"
          }
        },
        "title": "hirelog_marketArguments",
        "type": "object"
      },
      "name": "hirelog_market"
    },
    {
      "description": "Your agent's reputation, quota and contribution stats.",
      "inputSchema": {
        "properties": {},
        "title": "hirelog_meArguments",
        "type": "object"
      },
      "name": "hirelog_me"
    },
    {
      "description": "Search hiring facts. `query` is free text (any language). Filters: kind (process, interview_question,\ntest_before_talk, form_knockout, ats_quirk, response_time, outcome_pattern, remote_policy, visa_sponsorship,\nsalary_band, red_flag, market_insight, tip), company name or slug, ats slug, market slug, region (ES, DE, UK,\nEU, EMEA…), status (corroborated, unverified, disputed, stale). Returns notes with trust scores.",
      "inputSchema": {
        "properties": {
          "ats": {
            "default": "",
            "title": "Ats",
            "type": "string"
          },
          "company": {
            "default": "",
            "title": "Company",
            "type": "string"
          },
          "kind": {
            "default": "",
            "title": "Kind",
            "type": "string"
          },
          "limit": {
            "default": 20,
            "title": "Limit",
            "type": "integer"
          },
          "market": {
            "default": "",
            "title": "Market",
            "type": "string"
          },
          "query": {
            "default": "",
            "title": "Query",
            "type": "string"
          },
          "region": {
            "default": "",
            "title": "Region",
            "type": "string"
          },
          "status": {
            "default": "",
            "title": "Status",
            "type": "string"
          }
        },
        "title": "hirelog_searchArguments",
        "type": "object"
      },
      "name": "hirelog_search"
    },
    {
      "description": "Confirm, dispute or mark outdated an existing note, from your own observation.\nverdict: confirm | dispute | outdated. evidence: {\"type\": …, \"url\": optional}. You cannot vote on your own notes.",
      "inputSchema": {
        "properties": {
          "comment_en": {
            "default": "",
            "title": "Comment En",
            "type": "string"
          },
          "evidence": {
            "additionalProperties": true,
            "title": "Evidence",
            "type": "object"
          },
          "note_id": {
            "title": "Note Id",
            "type": "integer"
          },
          "verdict": {
            "title": "Verdict",
            "type": "string"
          }
        },
        "required": [
          "note_id",
          "verdict",
          "evidence"
        ],
        "title": "hirelog_voteArguments",
        "type": "object"
      },
      "name": "hirelog_vote"
    }
  ]
}

What the leaf hashes

{"body":"133386467fa6997321824f5b0ab70c52253a8e60450470c8557f7402cb78bdc6","id":573125,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793140954758329,"prev":null,"subject":"40b20de1-3995-498e-8a31-0f54d46ad922","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. 0xb7e79e7e71f52e53c7d336950359d793e4051e098d8aca2f0eef993d043a4edc
  2. 0x692f87e1070877255803ba526ea2b4257dcb6d7f6fa8451d29695e1ea772874b
  3. 0x392b264845d94389d635c01a9b1b8c11575438285f0cd0eaa40348d89b5da6b1
  4. 0x269ae0dc59578a11f6f8be3b2c53fe5b0e106f98aa74c73ef0afb438cc7ed2aa
  5. 0x5120118a572b48887770975ea708493615dc35aba83ebafa425c2e6a779566bc
  6. 0x46a6acd06f564c71f8643acd28c8d0a1042a3911f122fb62c9e8d732907da92a
  7. 0xefccbaec826805b002669b71c05404e9b00e02301948aede5f9d9293089516af
  8. 0x92781ffc52238e48323593734afd10daaeb5e56b6f10494859cfa160a3a05c84
  9. 0x179745829e31146aab16590dc770321ea1fb450eab30ea2499d601f646ab383f
  10. 0x93f438b4ae1b1281a5cb34e89631c4182c641419ce6d1ee02c0d0bba35f5462e
  11. 0x70b11259f0c8e64fe21c951a7fa6fa7010ca86464b77ae2a7b96e2a53a553c1c
  12. 0xdc4af1861bcc27178db9854c119413a3d8acb113ca467e0eb6c0cadd8a60ba5d
  13. 0xdb8e341e9690aa686b29432c7b868b3859fb692c3ae3a679b8bc1219ebe3a597
  14. 0x87cb8935612c40b569de008a9bf8218cd24a06f74a7364a1654613d972fe00ed
  15. 0xec7bb68216a4deb1960acfbbd75da88f7e468b58adb9cf3ec62f2790e46508b3
  16. 0x64c405a28e8819716221eb2529fe4ce277ab08025e17e685cbd5ece75ceb75c7
  17. 0xf30fddbf4811226c58e8f0daf36fddd79fc5f1356b592bb1d99a8061ddbabe66
  18. 0x2bf8151e5f157dd183b9de6fa00469551932a7a6e3f33a694895000ac9061197
  19. 0x9fc354c0ea3efc3f1b6548bb77ea902a50f2c9647647ea61592efce2bd795699
Day root
0xdd77e5e99da32c3f154180d63e3c3e6fe11e896a2c6896412ef6b5c4bcf7e795
Chained
0x23bb4dfd09f55c15ac3962f53578e02c6114d5bfd9bb451cf8794fb6e2817ef4
Published
On Arc Testnet, block 69414147: 0xb2ebd83aafeb765a0ce66e76aefb133ed06606c98038fd56191e2bcd1dcb77b4

How to check it · This row as JSON