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Duplicate Observations Record Quality Audit and Category Frequencies
x402
Duplicate Observations Record Quality Audit and 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).
Analyzes up to 200 rows of duplicate-observation data to produce two reports: a record quality audit and category frequency breakdown by dataset group and date.
Price / call$0.01
Success—
StatusUnknown
How this service works
Duplicate observations — Record quality audit + Category frequencies: Record quality audit + Category frequencies for supplied duplicate observations records (duplicate_rows, total_rows). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns two independent analytical reports: (1) a record quality audit summarizing the integrity and quality characteristics of the supplied duplicate-observation rows, and (2) a category frequency report breaking down occurrences and duplicate rates by dataset_group and date. All computation is performed locally using shared analytical engines with no external lookups or predictions.
Example use cases
ETL pipeline deduplication audit
“We ran a deduplication pass on our ETL output and have a list of up to 150 rows, each with a row_id, dataset_group like 'sales' or 'returns', date, plus duplicate_rows and total_rows counts. Can you give me a record quality audit and category frequency breakdown so I know which groups are worst affected?”
Monthly data integrity review
“I need a quality report on our monthly data integrity check — I have 80 rows of results with row_id, dataset_group, date in YYYY-MM-DD format, and counts of duplicate_rows versus total_rows. Please run both the record quality audit and category frequency analysis.”
Cross-dataset duplicate rate comparison
“Can you analyze these 60 duplicate observation records across our three dataset groups — 'customers', 'transactions', and 'products' — each row has a row_id, date, duplicate_rows, and total_rows? I want the record quality audit and the category frequency report to compare duplication rates across groups.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-04-006?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a record quality audit and a category frequency analysis on duplicate observation data in a single call at low cost ($0.01 USDC). It is ideal for batch sizes up to 200 rows where you want offline, deterministic analysis of duplicate_rows versus total_rows ratios across dataset groups — without needing live lookups, predictions, or external data enrichment.
Side effects
- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) causes schema rejection
- Dates not matching YYYY-MM-DD pattern fail pattern validation
- Numeric fields outside the allowed range trigger validation errors
- Empty rows array (minItems: 1 not met) returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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