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Data Collection Completeness — Record Quality Audit + Two-Measure Correlation
x402
Data Collection Completeness — 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 2026-10-24).
Audits record quality and computes two-measure correlation for data collection completeness records containing observed vs. expected values, returning two independent analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data collection completeness — Record quality audit + Two-measure correlation: Record quality audit + Two-measure correlation for supplied data collection completeness records (observed_values, expected_values). 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 flagging issues such as nulls, out-of-range values, or malformed entries across the submitted rows, and (2) a two-measure correlation report quantifying the statistical relationship between observed_values and expected_values across all provided records. Both reports are generated locally with no external lookups.
Example use cases
Course group completeness validation
“I have weekly data collection completeness records for two course groups — 'intro-math' and 'advanced-bio' — from October 2026, with observed and expected values for each row. Can you audit the record quality and run a correlation between observed and expected values for me?”
Education data audit before reporting
“Before I submit my end-of-quarter education report, I need a quality audit and correlation check on my completeness dataset — about 80 rows with observed and expected collection counts per course group and date. Can you run both analyses and flag any issues?”
Observed vs expected gap analysis
“I'm tracking how many data points were actually collected versus how many we expected each day across three course groups over the past month — around 90 rows total. Can you do a record quality audit and correlation analysis on this completeness data so I can see if there's a systematic gap?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-22-015?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a record quality audit and a two-measure correlation analysis on education or data-collection completeness records in a single low-cost call. It is ideal for datasets up to 200 rows where you want offline, deterministic analysis of observed vs. expected values without any live lookups, predictions, or external integrations. Prefer it over general-purpose analytics tools when working within an x402 micropayment agentic workflow and when the education/course-group data structure matches your schema.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, date, observed_values, expected_values) — validation error
- Date field does not match YYYY-MM-DD format — pattern validation failure
- observed_values or expected_values outside allowed numeric range — schema rejection
- Empty rows array (minItems:1 not satisfied) — request rejected
- Payment not included or insufficient USDC — 402 payment required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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