{
  "x402Version": 2,
  "id": 29576,
  "slug": "29576",
  "resource": "https://netintel.dev/extract/table",
  "description": "Extract tabular data from messy text or HTML using Claude Haiku — detects columns and rows in unstructured content and returns clean structured JSON (columns + rows) so agents can turn pasted tables, HTML tables, and delimited text into usable data in one call.",
  "type": "http",
  "serviceName": "NetIntel",
  "iconUrl": "https://res.cloudinary.com/bdb-prod/image/upload/c_fill,ar_1:1,w_256,h_256,f_auto,q_auto/v1784214098/bazaar-icons/7d2bf437631b2e4e.png",
  "resourceType": "AI Inference",
  "accepts": [
    {
      "scheme": "exact",
      "network": "eip155:8453",
      "payTo": "0xdaDc335482AD545296Fd7b28518A251fFCbEb9Df",
      "asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
      "amount": "20000",
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  ],
  "outputSchema": {
    "properties": {
      "example": {
        "properties": {
          "cached": {
            "description": "True if served from the in-memory cache.",
            "type": "boolean"
          },
          "column_count": {
            "description": "Number of columns detected.",
            "type": "number"
          },
          "findings": {
            "description": "Informational findings (e.g. no_table_found, count_mismatch).",
            "items": {
              "type": "string"
            },
            "type": "array"
          },
          "grade": {
            "description": "Letter grade A-F",
            "type": "string"
          },
          "score": {
            "description": "Quality score 0-100",
            "type": "number"
          },
          "table": {
            "description": "Parsed table: columns (array of column names), rows (array of objects keyed by column name), and row_count (number of rows). Empty columns/rows with row_count 0 when no tabular structure is detected.",
            "type": "object"
          }
        },
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        "type": "string"
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    "type": "object"
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    "bazaar": {
      "info": {
        "input": {
          "body": {
            "text": "product | price | qty\nWidget A | 5.00 | 10\nWidget B | 7.50 | 4"
          },
          "bodyType": "json",
          "method": "POST",
          "type": "http"
        },
        "output": {
          "example": {
            "cached": false,
            "column_count": 3,
            "findings": [],
            "grade": "A",
            "score": 100,
            "table": {
              "columns": [
                "product",
                "price",
                "qty"
              ],
              "row_count": 2,
              "rows": [
                {
                  "price": "5.00",
                  "product": "Widget A",
                  "qty": "10"
                },
                {
                  "price": "7.50",
                  "product": "Widget B",
                  "qty": "4"
                }
              ]
            }
          },
          "type": "json"
        }
      },
      "schema": {
        "$schema": "https://json-schema.org/draft/2020-12/schema",
        "properties": {
          "input": {
            "additionalProperties": false,
            "properties": {
              "body": {
                "properties": {
                  "text": {
                    "description": "The messy text or HTML containing tabular data to extract. Max 10000 words or 50KB. Aliases also accepted: content, html, csv, table, markdown, data.",
                    "type": "string"
                  }
                },
                "required": [
                  "text"
                ],
                "type": "object"
              },
              "bodyType": {
                "enum": [
                  "json",
                  "form-data",
                  "text"
                ],
                "type": "string"
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                  "POST"
                ],
                "type": "string"
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              "type": {
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                "type": "string"
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            },
            "required": [
              "type",
              "method",
              "bodyType",
              "body"
            ],
            "type": "object"
          },
          "output": {
            "properties": {
              "example": {
                "properties": {
                  "cached": {
                    "description": "True if served from the in-memory cache.",
                    "type": "boolean"
                  },
                  "column_count": {
                    "description": "Number of columns detected.",
                    "type": "number"
                  },
                  "findings": {
                    "description": "Informational findings (e.g. no_table_found, count_mismatch).",
                    "items": {
                      "type": "string"
                    },
                    "type": "array"
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                  "grade": {
                    "description": "Letter grade A-F",
                    "type": "string"
                  },
                  "score": {
                    "description": "Quality score 0-100",
                    "type": "number"
                  },
                  "table": {
                    "description": "Parsed table: columns (array of column names), rows (array of objects keyed by column name), and row_count (number of rows). Empty columns/rows with row_count 0 when no tabular structure is detected.",
                    "type": "object"
                  }
                },
                "type": "object"
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            "type": "object"
          }
        },
        "required": [
          "input"
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        "type": "object"
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    }
  },
  "tags": [
    "data extraction",
    "document parsing",
    "structured data",
    "text to json",
    "llm extraction",
    "bazaar"
  ],
  "sourceHost": "netintel.dev",
  "lastUpdated": "2026-10-08T06:08:33.981Z",
  "quality": {
    "calls30d": 2,
    "uniquePayers30d": 2,
    "lastCalledAt": "2026-10-08T06:08:33.795Z"
  },
  "metadata": {
    "serviceName": "NetIntel",
    "iconUrl": "https://res.cloudinary.com/bdb-prod/image/upload/c_fill,ar_1:1,w_256,h_256,f_auto,q_auto/v1784214098/bazaar-icons/7d2bf437631b2e4e.png",
    "extensions": {
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        "info": {
          "input": {
            "body": {
              "text": "product | price | qty\nWidget A | 5.00 | 10\nWidget B | 7.50 | 4"
            },
            "bodyType": "json",
            "method": "POST",
            "type": "http"
          },
          "output": {
            "example": {
              "cached": false,
              "column_count": 3,
              "findings": [],
              "grade": "A",
              "score": 100,
              "table": {
                "columns": [
                  "product",
                  "price",
                  "qty"
                ],
                "row_count": 2,
                "rows": [
                  {
                    "price": "5.00",
                    "product": "Widget A",
                    "qty": "10"
                  },
                  {
                    "price": "7.50",
                    "product": "Widget B",
                    "qty": "4"
                  }
                ]
              }
            },
            "type": "json"
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        },
        "schema": {
          "$schema": "https://json-schema.org/draft/2020-12/schema",
          "properties": {
            "input": {
              "additionalProperties": false,
              "properties": {
                "body": {
                  "properties": {
                    "text": {
                      "description": "The messy text or HTML containing tabular data to extract. Max 10000 words or 50KB. Aliases also accepted: content, html, csv, table, markdown, data.",
                      "type": "string"
                    }
                  },
                  "required": [
                    "text"
                  ],
                  "type": "object"
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                "bodyType": {
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                    "form-data",
                    "text"
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                  "type": "string"
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                "method": {
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                "body"
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              "type": "object"
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            "output": {
              "properties": {
                "example": {
                  "properties": {
                    "cached": {
                      "description": "True if served from the in-memory cache.",
                      "type": "boolean"
                    },
                    "column_count": {
                      "description": "Number of columns detected.",
                      "type": "number"
                    },
                    "findings": {
                      "description": "Informational findings (e.g. no_table_found, count_mismatch).",
                      "items": {
                        "type": "string"
                      },
                      "type": "array"
                    },
                    "grade": {
                      "description": "Letter grade A-F",
                      "type": "string"
                    },
                    "score": {
                      "description": "Quality score 0-100",
                      "type": "number"
                    },
                    "table": {
                      "description": "Parsed table: columns (array of column names), rows (array of objects keyed by column name), and row_count (number of rows). Empty columns/rows with row_count 0 when no tabular structure is detected.",
                      "type": "object"
                    }
                  },
                  "type": "object"
                },
                "type": {
                  "type": "string"
                }
              },
              "required": [
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              "type": "object"
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          "required": [
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          ],
          "type": "object"
        }
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  "featured": false,
  "provider": {
    "host": "netintel.dev",
    "manifest_name": "netintel.dev",
    "source": "cdp-mirror",
    "source_manifest_url": "https://api.cdp.coinbase.com/platform/v2/x402/discovery/resources",
    "submitted_at": "2026-10-14T01:15:01.050Z"
  },
  "exampleResponse": {
    "cached": false,
    "column_count": 3,
    "findings": [],
    "grade": "A",
    "score": 100,
    "table": {
      "columns": [
        "product",
        "price",
        "qty"
      ],
      "row_count": 2,
      "rows": [
        {
          "price": "5.00",
          "product": "Widget A",
          "qty": "10"
        },
        {
          "price": "7.50",
          "product": "Widget B",
          "qty": "4"
        }
      ]
    }
  }
}