Evidence row 308980

What was observed

{
  "count": 10,
  "tools": [
    {
      "description": "Describe ONE topic in full — its axes and their operative definitions, its complete controlled theme and quality vocabularies, plus the vocabulary actually IN USE across the corpus with counts. The declared vocabulary and the used vocabulary are different facts; this returns both. FREE and read-only.\n\n[capability: topic-coordinate-systems · mirrors: GET /api/corpus/topics/:slug]",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "topic": {
            "default": "being-human",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "vela.corpus.describe_topic"
    },
    {
      "description": "Ground a claim in the corpus: hybrid semantic + theme retrieval over real passages, returning citations with source, passage code, scores, and a SHORT snippet. Use to check whether the corpus supports, complicates or is silent on an assertion. COSTS a small amount (one embedding per call).\n\n[capability: corpus-ingestion-dual-grade · mirrors: internal — lib/audit/retrieve.ts]",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "claim": {
            "description": "The claim to ground.",
            "minLength": 3,
            "type": "string"
          },
          "limit": {
            "default": 8,
            "maximum": 20,
            "minimum": 1,
            "type": "integer"
          }
        },
        "required": [
          "claim"
        ],
        "type": "object"
      },
      "name": "vela.corpus.ground_claim"
    },
    {
      "description": "List the coordinate systems the corpus can be queried through — each with its thesis, axes, and controlled vocabularies. Call this before vela.corpus.query to learn what axes and themes exist. FREE and read-only.\n\n[capability: topic-coordinate-systems · mirrors: GET /api/corpus/topics]",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {},
        "type": "object"
      },
      "name": "vela.corpus.list_topics"
    },
    {
      "description": "Ask the corpus by COORDINATE rather than keyword. Filter works by axis weights (e.g. religion ∈ {T,s} AND work ∈ {T,s} returns the God-and-Work source set across genres), controlled themes, qualities/emotions, genre, and free text. Returns card metadata: the one-line claim, themes, coordinates, qualities. FREE and read-only.\n\n[capability: library-extraction-cards · mirrors: POST /api/corpus/query]",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "axes": {
            "additionalProperties": {
              "items": {
                "type": "string"
              },
              "type": "array"
            },
            "description": "Axis → allowed weights. ALL listed axes must match. e.g. {\"religion\":[\"T\",\"s\"],\"work\":[\"T\",\"s\"]}",
            "propertyNames": {
              "type": "string"
            },
            "type": "object"
          },
          "genre": {
            "type": "string"
          },
          "include_passages": {
            "default": false,
            "description": "Include theme-anchored passage pointers.",
            "type": "boolean"
          },
          "limit": {
            "default": 50,
            "maximum": 200,
            "minimum": 1,
            "type": "integer"
          },
          "offset": {
            "default": 0,
            "maximum": 9007199254740991,
            "minimum": 0,
            "type": "integer"
          },
          "qualities": {
            "description": "Cards carrying ANY of these qualities (emotions, for being-human).",
            "items": {
              "type": "string"
            },
            "type": "array"
          },
          "text": {
            "description": "Substring match over title / author / one-line claim.",
            "type": "string"
          },
          "themes": {
            "description": "Cards citing ANY of these controlled themes.",
            "items": {
              "type": "string"
            },
            "type": "array"
          },
          "topic": {
            "default": "being-human",
            "description": "Coordinate system to query (topic_configs.slug).",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "vela.corpus.query"
    },
    {
      "description": "Literary Witness Rail (ASN-1577): return passages and one-line claims from Vela's 762-work corpus that illuminate the given themes and/or emotions. Designed for frame-family profile pages — PersonFrame × ProblemFrame × ConditionFrame — to add an inside-out layer (what writers who lived this say) alongside the outside-in portrait the frame join produces. Results carry evidence_grade 'T1' (single-extractor) until PRN-282 lands. FREE for claims; costs one embedding for the passage path.\n\n[capability: literary-witness · mirrors: GET /api/vela/witness]",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "axes": {
            "additionalProperties": {
              "items": {
                "type": "string"
              },
              "type": "array"
            },
            "description": "Axis weight filters for claims only — same format as vela.corpus.query (e.g. {work:[\"T\",\"s\"]}).",
            "propertyNames": {
              "type": "string"
            },
            "type": "object"
          },
          "condition_slug": {
            "description": "ConditionFrame entity slug (same reservation as problem_slug).",
            "type": "string"
          },
          "emotions": {
            "description": "Emotions to match (e.g. 'shame', 'betrayal', 'grief'). At least one of themes or emotions is required.",
            "items": {
              "minLength": 1,
              "type": "string"
            },
            "type": "array"
          },
          "max_claims": {
            "default": 3,
            "description": "Max one-line claims to return (default 3).",
            "maximum": 8,
            "minimum": 1,
            "type": "integer"
          },
          "max_passages": {
            "default": 5,
            "description": "Max passages to return (default 5).",
            "maximum": 10,
            "minimum": 1,
            "type": "integer"
          },
          "problem_slug": {
            "description": "ProblemFrame entity slug (echoed in response; reserved for frame_tags[] pre-cache after PA-1153 ID-freeze).",
            "type": "string"
          },
          "themes": {
            "description": "Controlled themes from Vela's vocabulary (e.g. 'fairness', 'recognition').",
            "items": {
              "minLength": 1,
              "type": "string"
            },
            "type": "array"
          }
        },
        "type": "object"
      },
      "name": "vela.corpus.witness"
    },
    {
      "description": "The reading list an emotion or theme page shows: books with one-line claims and a short attributed passage (≤300 chars). Exactly one of emotion or theme. FREE and read-only. Every url carries ?ref=mcp for citation arrival measurement.\n\n[capability: library-extraction-cards · mirrors: GET /api/corpus/reading-list]",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "emotion": {
            "description": "Emotion primary slug (e.g. grief). Mutually exclusive with theme.",
            "type": "string"
          },
          "limit": {
            "default": 24,
            "maximum": 24,
            "minimum": 1,
            "type": "integer"
          },
          "theme": {
            "description": "Controlled theme slug (e.g. desire). Mutually exclusive with emotion.",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "vela.library.reading_list"
    },
    {
      "description": "Whether a magazine's corpus can support the adaptive promise its pages render. Reports, per property, each relational dimension's fill AND its separating power — a field present on every piece with one distinct value carries no information, so fill rate alone is misleading. Read-only.\n\n[capability: adaptive-magazine-engine · mirrors: npm run magazine:relation-floor]",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "property": {
            "description": "Restrict to one property id; omit for every property with published pieces.",
            "maxLength": 64,
            "minLength": 1,
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "vela.magazine.relation_floor"
    },
    {
      "description": "Ask what this magazine would actually give a reader who said they wanted these things. Returns the REAL sequenced path with the rationale for each piece — the same core the anonymous intake calls, not a preview. Read-only: writes nothing and records no signal.\n\n[capability: adaptive-magazine-engine · mirrors: POST /api/magazine/start-path]",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "emotions": {
            "description": "Emotions the reader is steering by.",
            "items": {
              "maxLength": 64,
              "minLength": 1,
              "type": "string"
            },
            "maxItems": 12,
            "type": "array"
          },
          "forms": {
            "description": "Article forms to steer by. At least one of emotions/forms is required.",
            "items": {
              "maxLength": 64,
              "minLength": 1,
              "type": "string"
            },
            "maxItems": 12,
            "type": "array"
          },
          "limit": {
            "description": "Pieces to return (default 4).",
            "maximum": 12,
            "minimum": 1,
            "type": "integer"
          },
          "property": {
            "description": "Property id; defaults to vela.",
            "maxLength": 64,
            "minLength": 1,
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "vela.magazine.sequence_path"
    },
    {
      "description": "One FieldStation study as a library-kit ProfileDTO plus the raw StudyRecord. Unknown id is an error. FREE and read-only.\n\n[capability: study-catalogue · mirrors: GET /api/research/studies/:id]",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "id": {
            "description": "Catalogue id, e.g. S-01.",
            "minLength": 1,
            "type": "string"
          }
        },
        "required": [
          "id"
        ],
        "type": "object"
      },
      "name": "vela.research.get_study"
    },
    {
      "description": "List FieldStation research ideas as a library-kit DiscoveryDTO. Each card is a study we can support, not a running participant surface. The honesty gate (limitations, readiness, doNotClaim) is enforced by research:catalog-check — this tool publishes that same file. FREE and read-only. Presence is gated; truth is not.\n\n[capability: study-catalogue · mirrors: GET /api/research/studies]",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {},
        "type": "object"
      },
      "name": "vela.research.list_studies"
    }
  ]
}

What the leaf hashes

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Proof

Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of 2026-10-26 (296695 rows).

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15. 0xc3a6a3ae44ec0da1848b16d40c45d7aac97a67352eea8df18e0f26edabea8a2f
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Day root

0xf43e8dcc3d451a4788b26be904c55e8c4c0fa75c9666796c51db38d37e2c0df8

Chained

0x702d5ac508f08b0d1accf36af25822d8e5660367494edd17a642fb61e158a57a

Published

On Arc Testnet, block 69251483: 0x495162f8936e19f0039918feebe6c307f327cd6bf8c37219620b1970041fa9ae