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Null Coverage Analytics — Record Quality Audit, String Normalisation & Category Frequencies
x402
Null Coverage Analytics — Record Quality Audit, String Normalisation & Category Frequencies 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).
Performs three analytical reports on supplied null-coverage records: a record quality audit, string normalisation, and category frequency analysis — all offline, up to 200 rows per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Null coverage — Record quality audit + String normalisation + Category frequencies: Record quality audit + String normalisation + Category frequencies 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: (1) a record quality audit summarising null coverage health per row, (2) a string normalisation report cleaning and standardising text fields, and (3) a category frequency report showing counts and distributions across dataset_group values — all computed locally from the supplied data, with no external lookups.
Example use cases
Data pipeline completeness check
“I have 50 rows from my ETL pipeline with row IDs, dataset groups, dates, and counts of missing vs total values — can you run a null coverage quality audit plus category frequency breakdown on all of them so I can see which groups have the worst completeness?”
String normalisation across dataset groups
“My dataset has mixed casing and formatting in the dataset_group field across 120 records — can you send these through the string normalisation report along with the null coverage audit so I can clean them up?”
Missing value rate summary by group
“I need to understand how my two dataset groups, 'group-a' and 'group-b', compare in terms of missing values — here are 30 rows with dates from 2026-10-01 through 2026-10-30 — can you run the category frequencies and record quality audit on them?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-03-195?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of null-coverage data (missing_values and total_values per row with dataset groups and dates) and need all three analytical outputs — quality audit, string normalisation, and category frequencies — in a single low-cost call ($0.01 USDC). It is ideal for offline, batch data quality assessment without any need for live lookups, predictions, or external data sources.
Side effects
- More than 200 rows supplied — endpoint rejects payload exceeding maxItems limit
- Missing required fields (row_id, dataset_group, date, missing_values, total_values) — validation error returned
- Date field not matching YYYY-MM-DD pattern — schema validation failure
- Numeric values outside allowed range (±1,000,000,000,000) — rejected by schema
- Empty rows array (minItems: 1 not met) — request rejected
- Payment not completed via x402 protocol — endpoint returns 402 before processing
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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