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Datum Audit — Offline CSV & JSON Quality Reports
x402
Datum Audit — Offline CSV & JSON Quality Reports is a paid API for AI agents from datum-audit-csv-json-20260802.estoyaburido7.chatgpt.site, paid per call via x402, $1/call, status unknown (last checked 2026-10-13).
Analyzes uploaded CSV or JSON data locally to detect missing values, duplicate rows, and incompatible data types, returning a structured quality report with a score.
Price / call$1
Success—
StatusUnknown
How this service works
Find missing values, duplicate rows, and incompatible types locally. Zero dependencies, zero uploads, 6 USDC.
Output
Returns a JSON object with a summary section containing row count, column count, missing cell count, and duplicate row count, plus an overall numeric quality score (0–100) and a schema version identifier (datum-audit/1.0).
Example use cases
Pre-pipeline data validation
“Before I load this sales_data.csv into our pipeline, can you audit it for missing cells, duplicates, and type issues and tell me the quality score?”
JSON dataset cleanup check
“I have a JSON dataset from our API export — can you check it for duplicate records, missing fields, and incompatible types so I know what needs fixing?”
Data handoff quality gate
“My vendor just sent over a CSV with customer records — can you run a quality audit on it and flag any missing values or duplicate rows before I import it?”
Technical details
Endpoint
POSThttps://datum-audit-csv-json-20260802.estoyaburido7.chatgpt.site/api/audit?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, privacy-preserving data quality check on a CSV or JSON file without uploading data to a third-party cloud service. It is ideal for pre-processing validation gates, vendor data handoffs, or any scenario where data sensitivity prevents external uploads. Prefer it over cloud-based profiling tools when zero-upload guarantees and local execution matter.
Side effects
- Malformed or unparseable file returns a parsing error
- Unsupported file format (e.g. Excel .xlsx) may return an error or empty results
- Empty file or zero-row dataset may produce a zero-quality score with no meaningful summary
- Very large files may hit size limits or time out
- Network or payment failure (x402) results in no response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| data | — | CSV text, JSON text, or an object/array for JSON |
| format | string | |
| delimiter | string |
Output
Schema · Response
{
"type": "json",
"example": {
"summary": {
"rows": 2,
"columns": 3,
"missingCells": 1,
"duplicateRows": 0
},
"qualityScore": 72,
"schemaVersion": "datum-audit/1.0"
}
}Tags
x402
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