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Data Reconciliation Analytics: Record Quality Audit + String Normalisation + Grouped Numeric Summary
x402
Data Reconciliation Analytics: Record Quality Audit + String Normalisation + Grouped Numeric Summary 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 on up to 200 data reconciliation rows: a record quality audit, string normalisation, and a grouped numeric summary of source/target totals.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data reconciliation — Record quality audit + String normalisation + Grouped numeric summary: Record quality audit + String normalisation + Grouped numeric summary for supplied data reconciliation records (source_total, target_total). 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: (1) a record quality audit flagging null values, format violations, and completeness issues per row; (2) a string normalisation report cleaning and standardising the dataset_group and other string fields; and (3) a grouped numeric summary aggregating source_total or target_total values by dataset_group, with counts and statistics. All analysis is performed locally on the supplied data with no external lookups.
Example use cases
Finance team reconciliation data audit
“I have 150 rows of month-end reconciliation data with source_total and target_total figures — can you audit the record quality, normalise the dataset_group strings, and give me a grouped numeric summary of source_total broken down by group?”
Data pipeline output validation
“We just ran an ETL pipeline and I need to check the output quality — please audit these reconciliation records for missing or invalid fields, normalise the group name strings, and summarise source_total and target_total by dataset_group.”
Identifying anomalies in intercompany data
“Here are 80 rows of intercompany reconciliation records. Can you run the three-report analysis — quality audit, string normalisation, and grouped numeric summary on target_total — so I can spot any data issues before we close the books?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-11-194?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three combined analytical reports on a reconciliation dataset in a single API call without any external data lookups: specifically a quality audit, string normalisation, and grouped numeric summary. It is ideal for finance, data engineering, or ETL validation workflows where you want offline, deterministic analysis of up to 200 rows of source/target reconciliation data at very low cost ($0.01 USDC for all three reports).
Side effects
- Rows array empty or missing — returns validation error
- More than 200 rows submitted — rejected with max items error
- date field does not match YYYY-MM-DD pattern — schema validation failure
- row_id exceeds 80 characters or is empty — rejected
- source_total or target_total outside ±1,000,000,000,000 range — rejected
- Invalid field enum value (not 'source_total' or 'target_total') — rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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