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UV Layouts Data Quality Audit — Record Quality, String Normalisation & Adjacent Row Changes
x402
UV Layouts Data Quality Audit — Record Quality, String Normalisation & Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-27).
Runs three local analytical reports (record quality audit, string normalisation, and adjacent row change detection) on up to 200 rows of UV layout data containing island_count and occupied_percent fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
UV layouts — Record quality audit + String normalisation + Adjacent row changes: Record quality audit + String normalisation + Adjacent row changes for supplied uv layouts records (island_count, occupied_percent). 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 separate analytical reports delivered together: (1) a record quality audit flagging nulls, out-of-range values, and other data issues; (2) a string normalisation report for text fields like asset_group; and (3) an adjacent row change report highlighting step-changes or anomalies between consecutive rows in the selected numeric field (island_count or occupied_percent). All analysis is performed locally on the supplied rows with no external lookups.
Example use cases
UV layout pipeline data quality gate
“Before I push my UV layout data downstream, can you audit these 50 rows for record quality issues, normalise the asset_group strings, and flag any big jumps between adjacent rows in the island_count field?”
Detecting sudden changes in occupancy metrics
“I've got 150 rows of UV layout data with occupied_percent values and I want to know if there are any sudden jumps between consecutive rows — can you also check overall record quality and clean up any string inconsistencies in the asset_group column?”
QA check on exported UV layout dataset
“I exported 80 UV layout rows from our tool and I'm worried the data might have nulls, dirty strings, or weird step-changes in the occupied_percent column — can you run the three-report quality check on this dataset?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-06-200?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three combined analytical reports (quality audit, string normalisation, adjacent row change detection) for UV layout records in a single low-cost call. It is best when your dataset is already collected and you need offline/local analysis without any live lookups, predictions, or external integrations. Prefer it over individual single-report endpoints when you need all three report types on the same dataset to save cost and round-trips.
Side effects
- More than 200 rows submitted — request rejected with validation error
- Invalid date format (not YYYY-MM-DD) causes row-level rejection
- Missing required fields (row_id, date, asset_group) causes validation failure
- Invalid field enum value (not island_count or occupied_percent) causes error
- Empty rows array rejected (minItems: 1)
- Numeric values outside allowed range cause validation errors
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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