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Structured Data Observations — Record Quality Audit + Two-Measure Correlation
x402
Structured Data Observations — Record Quality Audit + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-25).
Performs a record quality audit and two-measure correlation analysis on up to 200 rows of structured observations containing valid_items and total_items fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Structured data observations — Record quality audit + Two-measure correlation: Record quality audit + Two-measure correlation for supplied structured data observations records (valid_items, total_items). 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 identifying completeness, validity, and anomalies across all submitted rows; and (2) a two-measure correlation report quantifying the statistical relationship between valid_items and total_items across the dataset. Both reports are generated locally from the supplied data with no external lookups.
Example use cases
Pre-pipeline data quality check
“Before I push this batch to our pipeline, can you audit these 50 observation rows for record quality issues — nulls, out-of-range values, missing dates — and also tell me how correlated valid_items and total_items are? I'll paste the rows with row_id, site_group, date, valid_items, and total_items.”
Detecting anomalies in site group data
“I have 120 rows of site group observations from last quarter with valid_items and total_items columns — can you run a quality audit to flag any bad records and then give me a correlation report to see if sites with more total items also tend to have more valid items?”
Monthly reporting validation for observation records
“For my monthly report I need two things: a quality audit on these 80 structured observation rows checking for missing or invalid values, and a two-measure correlation between valid_items and total_items — can you run both and give me the results?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-web-08-015?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a data quality audit and a correlation analysis on structured observation data with valid_items and total_items fields in a single low-cost call. It is ideal for pre-processing validation of small-to-medium datasets (up to 200 rows) where you want to identify record completeness issues and understand the statistical relationship between two numeric measures simultaneously, without requiring external data lookups or predictions.
Side effects
- Exceeding 200 rows causes rejection — trim dataset to at most 200 rows
- Missing required fields (row_id, site_group, date, valid_items, total_items) causes validation error
- Invalid date format (not YYYY-MM-DD) triggers schema rejection
- Numeric values outside ±1,000,000,000,000 are rejected
- Empty rows array returns an error — at least 1 row required
- Payment failure via x402 protocol prevents processing
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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