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Dataset Storage Record Quality Audit, String Normalisation & Numeric Distribution
x402
Dataset Storage Record Quality Audit, String Normalisation & Numeric Distribution 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 dataset storage records: a record quality audit, string normalisation check, and numeric distribution analysis for the used_mb and row_count fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Dataset storage — Record quality audit + String normalisation + Numeric distribution: Record quality audit + String normalisation + Numeric distribution for supplied dataset storage records (used_mb, row_count). 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 nulls, missing values, and data completeness issues; (2) a string normalisation report checking and cleaning string fields like row_id and dataset_group; (3) a numeric distribution summary (e.g. min, max, mean, percentiles, outlier flags) for the selected numeric field (used_mb or row_count). All computed locally with no external lookups. Covers up to 200 input rows.
Example use cases
Pre-ingestion data quality check
“Before I load these dataset storage records into our warehouse, can you audit them for quality issues, check the string fields are well-formed, and show me the numeric distribution of used_mb? I have about 80 rows with row_id, dataset_group, date, used_mb, and row_count.”
Storage anomaly detection by group
“I've got 150 rows of storage tracking data across multiple dataset groups and I want to know if there are any outliers or weird distributions in the row_count field — can you run the quality audit and numeric distribution report on them?”
Monthly dataset health report
“Here are this month's 200 storage records with used_mb and row_count per dataset group — run the full three-report analysis including string normalisation and numeric distribution on used_mb so I can include it in our monthly data health summary.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-18-193?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 dataset storage records (with used_mb and row_count fields) and need three combined analytical outputs — quality audit, string normalisation, and numeric distribution — in a single low-cost call. Ideal for lightweight pre-ingestion validation or periodic data health checks where no external data enrichment or predictive modelling is required. Not suitable for large datasets over 200 rows, real-time monitoring, or tasks requiring live lookups or ML-based predictions.
Side effects
- Input array is empty or missing — minItems:1 not satisfied
- More than 200 rows submitted — maxItems exceeded
- row_id missing or empty — minLength:1 violation
- date field does not match YYYY-MM-DD pattern — pattern validation failure
- used_mb or row_count values outside allowed numeric range
- Invalid field enum value provided — must be 'used_mb' or 'row_count'
- Payment not completed — x402 payment required before response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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