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Data Collection Completeness — Record Quality Audit + Numeric Row Ordering
x402
Data Collection Completeness — Record Quality Audit + Numeric Row Ordering is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-29).
Performs a record quality audit and numeric row ordering on up to 200 rows of data collection completeness records (observed_values, expected_values), returning 2 independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data collection completeness — Record quality audit + Numeric row ordering: Record quality audit + Numeric row ordering 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
Two independent analytical reports: (1) a record quality audit identifying issues in the supplied completeness records, and (2) a numeric row ordering of the same records — both generated locally from the submitted observed_values and expected_values data without any external lookups or predictions.
Example use cases
Education data completeness audit
“I have 50 rows of course completion data with observed and expected values for groups A through F, dated across Q3 2026. Can you run a record quality audit and numeric row ordering on them so I can see which rows have quality issues and how they rank numerically?”
Detecting anomalies in observed vs expected counts
“My data pipeline collected observed_values and expected_values for multiple course groups last month and I need to audit record quality and get a numeric ordering of the rows — can you run both reports on my 120-row dataset?”
Pre-submission data validation for reporting
“Before I submit my course group completeness report, can you audit the record quality and produce a numeric row ordering for my 80 rows of observed and expected values data so I can catch any issues first?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-22-007?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, local (no external lookup) quality auditing and numeric ordering of data collection completeness records — specifically tabular rows with observed and expected value pairs grouped by course or category. It is well-suited for education or research data pipelines where you want two simultaneous analytical reports (quality audit + ordering) for up to 200 rows at minimal cost.
Side effects
- Missing required fields (row_id, date, observed_values, expected_values) cause validation errors
- Submitting more than 200 rows exceeds the row limit and is rejected
- Invalid date format (non-YYYY-MM-DD) triggers schema validation failure
- Null values in both observed_values and expected_values may produce incomplete audit results
- Selecting a field enum value not in [observed_values, expected_values] causes a schema error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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