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Null Coverage Analytics — Record Quality Audit, String Normalisation & Duplicate Key Report
x402
Null Coverage Analytics — Record Quality Audit, String Normalisation & Duplicate Key Report is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-14).
Runs three local analytical reports on null-coverage row data: a record quality audit, string normalisation, and duplicate key detection — for up to 200 rows per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Null coverage — Record quality audit + String normalisation + Duplicate key report: Record quality audit + String normalisation + Duplicate key report for supplied null coverage records (missing_values, total_values). 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 for the supplied rows: (1) a record quality audit summarising data health metrics around missing and total values, (2) a string normalisation report cleaning and standardising text fields such as row_id and dataset_group, and (3) a duplicate key report identifying any repeated row identifiers — all computed locally with no external lookups.
Example use cases
Pipeline data completeness audit
“I've got 120 rows from our ingestion pipeline, each with a row_id, dataset_group, date, missing_values, and total_values. Can you run all three reports — quality audit, string normalisation, and duplicate key check — so I can spot any completeness or naming issues before we load to the warehouse?”
Detecting duplicate keys in export
“I exported 80 rows of null coverage data from our BI tool and I'm worried there might be duplicate row IDs sneaking in. Can you run the duplicate key report alongside the quality audit and string normalisation for those rows?”
Normalising group names across datasets
“Our dataset_group labels are inconsistent across about 60 rows — some are mixed case or have trailing spaces. Can you run the string normalisation report on these null coverage records along with the record quality audit and duplicate key report?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-03-192?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three simultaneous data-quality reports — quality audit, string normalisation, and duplicate key detection — on null-coverage tabular data in a single $0.01 call, without requiring any external data lookups, live predictions, or professional assessments. It is ideal for lightweight, offline-style data quality pipelines processing up to 200 rows at a time.
Side effects
- More than 200 rows submitted — exceeds the per-call row limit
- Missing required fields (row_id, dataset_group, date, missing_values, total_values) causing schema validation failure
- Invalid date format (must match YYYY-MM-DD pattern)
- row_id exceeds 80-character maxLength limit
- Payment not provided or insufficient USDC balance (x402 payment failure)
- Empty rows array (minItems: 1 not satisfied)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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