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Data Reconciliation Record Quality Audit and IQR Outlier Flags
x402
Data Reconciliation Record Quality Audit and IQR Outlier Flags 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).
Performs a record quality audit and IQR-based outlier detection on up to 200 source/target reconciliation row pairs, returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data reconciliation — Record quality audit + IQR outlier flags: Record quality audit + IQR outlier flags for supplied data reconciliation records (source_total, target_total). 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) a record quality audit identifying issues such as nulls, format errors, or anomalous records across the supplied rows, and (2) IQR-based outlier flags marking which rows contain statistically unusual values in the selected field (source_total or target_total), all computed locally without external lookups.
Example use cases
ETL pipeline reconciliation sanity check
“I just ran my nightly ETL and have 50 reconciliation rows with source_total and target_total values by date and dataset group. Can you audit them for record quality issues and flag any IQR outliers on source_total so I know which rows to investigate before sign-off?”
Financial close data quality review
“We're doing month-end close and I need to quality-check 120 reconciliation records across two groups — 'ledger-a' and 'ledger-b' — comparing source_total to target_total by date. Run the IQR outlier flags on target_total and give me both reports.”
Data migration validation audit
“After migrating our database, I want to verify the reconciliation records look clean. I have up to 180 rows with source and target totals per date and group. Can you do the quality audit and IQR outlier detection on source_total so I can catch any suspicious values before we go live?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-11-014?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, local statistical quality assessment of reconciliation data — specifically IQR-based outlier detection combined with a record quality audit — without requiring external data lookups, ML predictions, or professional advisory output. Ideal for ETL validation, financial reconciliation checks, and data migration QA on batches up to 200 rows at very low cost ($0.01 per call for two reports).
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, date, source_total, target_total, dataset_group) cause request rejection
- Invalid date format (not YYYY-MM-DD) triggers a schema validation error
- Values outside the allowed numeric range (±1,000,000,000,000) are rejected
- Empty rows array returns an error
- Invalid field enum value (not 'source_total' or 'target_total') causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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