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UV Layouts — Record Quality Audit + String Normalisation + IQR Outlier Flags
x402
UV Layouts — Record Quality Audit + String Normalisation + 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 2026-10-27).
Audits up to 200 UV layout records for quality issues, normalises string fields, and flags numeric outliers using IQR analysis across island_count and occupied_percent fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
UV layouts — Record quality audit + String normalisation + IQR outlier flags: Record quality audit + String normalisation + IQR outlier flags 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
Returns three independent analytical reports: (1) a record quality audit identifying missing, malformed, or invalid field values; (2) a string normalisation report showing standardised versions of text fields like asset_group; and (3) an IQR-based outlier flag report identifying rows with statistically anomalous values in the selected numeric field (island_count or occupied_percent). All analysis is performed locally on the supplied data with no external lookups.
Example use cases
Pre-pipeline UV layout data validation
“Before I run my UV layout pipeline, can you check this batch of 120 UV layout records for quality issues, normalise the asset_group strings, and flag any outliers in island_count using IQR analysis?”
Occupied percent anomaly detection
“I've got a dataset of UV layout records and I'm worried some occupied_percent values are way off — can you run the quality audit and IQR outlier flags on the occupied_percent field for all 80 rows?”
Asset group string cleaning audit
“My UV layout export from last week has inconsistent asset_group labels across 60 rows — can you run a string normalisation and record quality audit on it, and also flag any island_count outliers while you're at it?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-06-203?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a combined data quality audit, string normalisation, and IQR outlier detection in a single call for UV layout records specifically containing island_count and occupied_percent metrics. It is ideal for pre-processing pipelines where you want three analytical reports in one low-cost API call without any external data lookups or predictions. Prefer it over single-report alternatives when you need all three analyses simultaneously on datasets up to 200 rows.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Invalid date format (not YYYY-MM-DD) causes row-level validation failure
- Missing required fields (row_id, asset_group, date, island_count, occupied_percent) cause row rejection
- Invalid field selector enum value (not island_count or occupied_percent) causes error
- Empty rows array causes immediate failure
- 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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