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Schema Conformity String Normalisation and Secondary-Measure Weighted Mean
x402
Schema Conformity String Normalisation and Secondary-Measure Weighted Mean 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).
Computes string normalisation and a secondary-measure weighted mean across up to 200 schema conformity records (valid_records, checked_records) and returns two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Schema conformity — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean for supplied schema conformity records (valid_records, checked_records). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns two independent analytical reports: (1) string-normalised values for the selected field across all submitted rows, and (2) a secondary-measure weighted mean computed over the valid_records and checked_records columns, grouped by dataset_group and date. No external lookups or predictions are made — all computation is local and deterministic.
Example use cases
Data quality pipeline conformity check
“Here are 50 daily schema conformity rows for our ETL pipeline across two groups — can you string-normalise the valid_records values and compute their weighted mean so I can see which group is performing better?”
Weighted mean on checked records by group
“I have a batch of schema conformity records with checked_records counts across multiple dataset groups and dates — please compute the secondary-measure weighted mean on the checked_records field and return both analytical reports.”
Audit report for schema validation results
“We ran schema validation last month and have up to 150 rows with valid_records and checked_records per group — can you normalise the strings and produce a weighted mean report on valid_records so I can share it with our data governance team?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-02-034?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both string normalisation and a weighted mean computed together on schema conformity data in a single call, with up to 200 rows and two reports returned simultaneously. It is best suited for batch data quality analytics workflows where no live external lookup or prediction is required and cost efficiency matters (two reports for $0.01 USDC).
Side effects
- Submitting more than 200 rows causes rejection — payload must stay within the 200-row limit
- Missing required fields (row_id, date, valid_records, checked_records) cause validation errors
- Invalid date format (not YYYY-MM-DD) will fail pattern validation
- Null values in both valid_records and checked_records may produce undefined weighted mean results
- Selecting a field value outside the enum ['valid_records','checked_records'] returns a validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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