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tessera.kbates9611.chatgpt.site

live Unverified (seed import) Productivity & Business 64 tools imperative implementation

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Tessera turns governed monthly data into decision-ready dashboards.

First seen 2026-11-05 · Last seen 2026-11-05 · Source: webmcp.com

Answer 5 · Act 59 · Transact 0 · Score: Not yet scored

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propose_dataset_month_outline

act imperative

Persist labelled outlines and source-to-canonical variables for a pending workbook. Outline every region the sheet contains: the table that feeds this dataset (kind table, confidence 1), any secondary tables (kind table, lower confidence), and the titles, notes, and footers people should see were deliberately skipped (kind narrative or footnote). Every region is drawn and labelled on the worksheet with its name. Prioritize exact fields already used by charts. Put every uncertain semantic choice into questions so Tessera can ask the user instead of guessing. MODEL GUIDANCE: Define table boundaries, headers, types, keys, and canonical fields. Surface ambiguous mappings as user questions rather than guessing.

Input schema

Property	Type	Required	Description
`datasetId`	string	yes	Dataset ID
`period`	string	yes	Month in YYYY-MM format
`regions`	array	yes	Every labelled region in the workbook; at least one must be kind table
`variableMappings`	array	yes	Source variables matched to stable canonical variables
`questions`	array	no	Ambiguous choices that require a user answer

Raw JSON schema

{
  "type": "object",
  "properties": {
    "datasetId": {
      "type": "string",
      "description": "Dataset ID",
      "maxLength": 8000
    },
    "period": {
      "type": "string",
      "description": "Month in YYYY-MM format",
      "maxLength": 8000
    },
    "regions": {
      "type": "array",
      "description": "Every labelled region in the workbook; at least one must be kind table",
      "items": {
        "type": "object",
        "properties": {
          "id": {
            "type": "string",
            "description": "Stable region ID",
            "maxLength": 8000
          },
          "sheet": {
            "type": "string",
            "description": "Exact worksheet name",
            "maxLength": 8000
          },
          "name": {
            "type": "string",
            "description": "Short label shown on the worksheet outline, such as Facility detail or Ops notes",
            "maxLength": 8000
          },
          "kind": {
            "type": "string",
            "description": "table for rows and columns to clean; narrative for titles, commentary, or prose; footnote for footers, sources, or totals",
            "enum": [
              "table",
              "narrative",
              "footnote"
            ]
          },
          "confidence": {
            "type": "number",
            "description": "1 for the table that feeds this dataset; lower for secondary tables and non-table regions",
            "minimum": 0,
            "maximum": 1
          },
          "canonicalName": {
            "type": "string",
            "description": "Dataset name for the primary table; otherwise the region name",
            "maxLength": 8000
          },
          "range": {
            "type": "object",
            "properties": {
              "startRow": {
                "type": "number",
                "description": "One-based inclusive start row",
                "minimum": 1
              },
              "startColumn": {
                "type": "number",
                "description": "One-based inclusive start column",
                "minimum": 1
              },
              "endRow": {
                "type": "number",
                "description": "One-based inclusive end row",
                "minimum": 2
              },
              "endColumn": {
                "type": "number",
                "description": "One-based inclusive end column",
                "minimum": 1
              }
            },
            "required": [
              "startRow",
              "startColumn",
              "endRow",
              "endColumn"
            ],
            "additionalProperties": false
          }
        },
        "required": [
          "name",
          "kind",
          "confidence",
          "canonicalName",
          "range"
        ],
        "additionalProperties": false
      },
      "maxItems": 1000
    },
    "variableMappings": {
      "type": "array",
      "description": "Source variables matched to stable canonical variables",
      "items": {
        "type": "object",
        "properties": {
          "source": {
            "type": "string",
            "description": "Exact source variable",
            "maxLength": 8000
          },
          "canonical": {
            "type": "string",
            "description": "Stable canonical variable",
            "maxLength": 8000
          },
          "confidence": {
            "type": "number",
            "description": "Mapping confidence",
            "minimum": 0,
            "maximum": 1
          },
          "matchedFromPrevious": {
            "type": "string",
            "description": "Prior approved variable that established the match",
            "maxLength": 8000
          },
          "usedByCharts": {
            "type": "boolean",
            "description": "Whether an existing chart or KPI depends on this variable"
          },
          "confirmed": {
            "type": "boolean",
            "description": "Whether the user explicitly confirmed it"
          }
        },
        "required": [
          "source",
          "canonical",
          "confidence"
        ],
        "additionalProperties": false
      },
      "maxItems": 1000
    },
    "questions": {
      "type": "array",
      "description": "Ambiguous choices that require a user answer",
      "items": {
        "type": "object",
        "properties": {
          "id": {
            "type": "string",
            "description": "Stable question ID",
            "maxLength": 8000
          },
          "prompt": {
            "type": "string",
            "description": "Short user-facing question",
            "maxLength": 8000
          },
          "detail": {
            "type": "string",
            "description": "Context explaining why the choice matters",
            "maxLength": 8000
          },
          "choices": {
            "type": "array",
            "description": "Two or more mutually exclusive choices",
            "items": {
              "type": "object",
              "properties": {
                "id": {
                  "type": "string",
                  "description": "Choice ID",
                  "maxLength": 8000
                },
                "label": {
                  "type": "string",
                  "description": "Short choice label",
                  "maxLength": 8000
                },
                "description": {
                  "type": "string",
                  "description": "Impact of choosing this option",
                  "maxLength": 8000
                }
              },
              "required": [
                "id",
                "label"
              ],
              "additionalProperties": false
            },
            "maxItems": 1000
          },
          "recommendedChoiceId": {
            "type": "string",
            "description": "Recommended choice ID",
            "maxLength": 8000
          },
          "answerChoiceId": {
            "type": "string",
            "description": "User-selected choice ID",
            "maxLength": 8000
          }
        },
        "required": [
          "id",
          "prompt",
          "choices"
        ],
        "additionalProperties": false
      },
      "maxItems": 1000
    }
  },
  "required": [
    "datasetId",
    "period",
    "regions",
    "variableMappings"
  ],
  "additionalProperties": false
}

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