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Aggregation Checks — Record Quality Audit + String Normalisation + Numeric Row Ordering
x402
Aggregation Checks — Record Quality Audit + String Normalisation + Numeric Row Ordering is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Runs three local analytical reports (record quality audit, string normalisation, and numeric row ordering) on up to 200 rows of aggregation check data containing source_sum and aggregate_sum fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Aggregation checks — Record quality audit + String normalisation + Numeric row ordering: Record quality audit + String normalisation + Numeric row ordering for supplied aggregation checks records (source_sum, aggregate_sum). 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
Three independent analytical reports: (1) a record quality audit flagging completeness, consistency, and structural issues in the supplied rows; (2) a string normalisation report cleaning and standardising text fields like dataset_group; (3) a numeric row ordering report ranking rows by the selected numeric field (source_sum or aggregate_sum). All computed locally on up to 200 supplied rows with no external lookups.
Example use cases
Financial reconciliation data quality check
“I have 80 aggregation check records with source_sum and aggregate_sum values from our monthly reconciliation — can you run a record quality audit, string normalisation, and numeric row ordering on them using source_sum as the field to analyse?”
ETL pipeline output validation
“After our ETL pipeline ran, I have 150 rows of aggregation data with row_id, dataset_group, date, source_sum, and aggregate_sum — please audit their quality, normalise the strings, and order them numerically by aggregate_sum.”
Dataset group consistency review
“I've got about 40 aggregation check records across two dataset groups and want three reports — a record quality audit, string normalisation, and numeric row ordering — run locally against the source_sum field so I can spot inconsistencies.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-17-196?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled local analytical operations — quality auditing, string normalisation, and numeric ordering — on aggregation check data (source_sum vs aggregate_sum) in a single cost-efficient call. Prefer it over building custom scripts when you need fast, no-setup data quality reports on up to 200 rows without any external lookups or predictions.
Side effects
- Rows array empty or missing — minItems:1 not met
- More than 200 rows submitted — maxItems exceeded
- Invalid date format (not YYYY-MM-DD) in any row
- source_sum or aggregate_sum values outside ±1,000,000,000,000 range
- row_id missing or empty string (minLength:1 required)
- Invalid field enum value (must be 'source_sum' or 'aggregate_sum')
- Payment of 0.01 USDC not completed — x402 payment required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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