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Schema Conformity Analytics — Record Quality Audit, String Normalisation & Duplicate Key Report
x402
Schema Conformity Analytics — Record Quality Audit, String Normalisation & Duplicate Key Report is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-14).
Runs three local analytical reports on schema conformity data (valid_records, checked_records): a record quality audit, string normalisation, and duplicate key detection — for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Schema conformity — Record quality audit + String normalisation + Duplicate key report: Record quality audit + String normalisation + Duplicate key report for supplied schema conformity records (valid_records, checked_records). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Returns three independent analytical reports for the supplied rows: (1) a record quality audit flagging anomalies in valid_records and checked_records values, (2) a string normalisation report identifying and correcting inconsistent string formatting in fields like dataset_group, and (3) a duplicate key report identifying repeated row_id or key combinations across the dataset. No external lookups or predictions are made — all analysis is performed locally on the supplied data.
Example use cases
Monthly conformity data quality check
“I have my monthly schema conformity export with about 150 rows — each row has a row_id, dataset_group, date, valid_records count, and checked_records count. Can you run the full quality audit, string normalisation, and duplicate key report on it so I can catch any issues before I submit it?”
Detecting duplicate keys in ETL output
“Our ETL pipeline just produced a conformity dataset with row IDs and dataset groups — can you check it for duplicate keys, normalise any inconsistent strings in the dataset_group field, and give me a record quality audit across all the valid_records and checked_records values?”
Pre-merge data validation for two dataset groups
“Before I merge group-a and group-b conformity records, can you run a duplicate key report, string normalisation, and record quality audit on the combined set of up to 200 rows so I know if there are any clashes or dirty strings?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-02-192?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three complementary data quality reports — record quality audit, string normalisation, and duplicate key detection — on schema conformity data (valid_records, checked_records) in a single $0.01 call for up to 200 rows, without requiring any external API calls, live lookups, or predictions. Prefer it over single-report sibling endpoints when you want all three analyses in one batch. Avoid if you need only one report type, need more than 200 rows, or require live data enrichment.
Side effects
- More than 200 rows submitted — request rejected with a row count limit error
- Missing required fields (row_id, dataset_group, date, valid_records, checked_records) on any row — validation error returned
- Invalid date format (not YYYY-MM-DD) causes row-level rejection
- row_id exceeds 80 characters — schema validation failure
- Numeric values outside the allowed range (±1,000,000,000,000) cause field-level errors
- Empty rows array (minItems:1 violated) returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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