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Metadata Completeness Record Quality Audit and Missing-Value Fill
x402
Metadata Completeness Record Quality Audit and Missing-Value Fill 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).
Audits metadata completeness records for quality issues and fills missing values in present_fields or expected_fields columns using zero, mean, or median imputation, for up to 200 rows with 2 independent reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Metadata completeness — Record quality audit + Explicit missing-value fill: Record quality audit + Explicit missing-value fill for supplied metadata completeness records (present_fields, expected_fields). 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 such as missing, null, or anomalous values in the completeness records; and (2) an explicit missing-value fill report showing imputed values for the chosen field (present_fields or expected_fields) using the selected method (zero, mean, or median). No external lookups or predictions are made — all analysis is local.
Example use cases
Imputing missing completeness counts before reporting
“I have a dataset of metadata completeness records with some null present_fields values across several site groups and dates — can you fill those missing values using median imputation and give me a quality audit report at the same time?”
Auditing metadata quality across site groups
“Can you run a record quality audit on my metadata completeness data? I have about 80 rows with row_id, site_group, date, present_fields, and expected_fields, and I want to know which records have issues.”
Zero-filling missing expected_fields for pipeline validation
“My pipeline has missing expected_fields values in the metadata completeness table — can you fill them with zero and also audit the records for quality problems? I'll send you the rows with row_id, site_group, and date included.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-web-05-019?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a combined record quality audit plus missing-value imputation for metadata completeness data (present_fields and expected_fields) in a single low-cost call. It is best suited for small-to-medium batches (up to 200 rows) where you want two independent local analytical reports without any external lookups, live data enrichment, or predictions. Prefer alternatives if you need outlier detection, deduplication, string normalization, or distribution analysis beyond completeness auditing.
Side effects
- Empty rows array or missing required fields (row_id, date, present_fields, expected_fields) causes validation error
- More than 200 rows submitted exceeds the maximum batch size
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Invalid method enum value (not zero, mean, or median) causes rejection
- Invalid field enum value (not present_fields or expected_fields) causes rejection
- Payment of 0.01 USDC not provided causes 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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