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Metadata Completeness — String Normalisation + Missing-Value Fill
x402
Metadata Completeness — String Normalisation + 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).
Normalises strings and fills missing values in metadata completeness records (present_fields, expected_fields) for up to 200 rows, producing 2 analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Metadata completeness — String normalisation + Explicit missing-value fill: String normalisation + 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 analytical reports covering the supplied metadata completeness rows: one applying string normalisation to site_group and other string fields, and one with explicit missing-value fill (zero, mean, or median) applied to the chosen field (present_fields or expected_fields). Reports are generated locally without external lookups.
Example use cases
Imputing missing completeness counts
“I have 150 rows of metadata completeness data with site groups and dates, but about 20 of them have null present_fields values. Can you fill those nulls using median imputation and normalise the string fields so everything is consistent?”
Zero-filling expected fields for reporting
“My metadata completeness dataset has some missing expected_fields entries. Fill them with zero and normalise the site_group strings, then produce the two standard completeness reports for me — I have about 80 rows total.”
Pre-pipeline data quality cleanup
“Before I load my metadata completeness records into the warehouse, I need the strings normalised and any missing present_fields values filled using mean — here are 200 rows with row IDs, site groups, and dates. Can you run both reports?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-web-05-037?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, local string normalisation and missing-value imputation on metadata completeness records (present_fields / expected_fields) without any external lookups or ML predictions. It is ideal for pre-pipeline data quality cleanup on small-to-medium batches (up to 200 rows) where cost matters and you want two bundled analytical reports for $0.01 USDC.
Side effects
- Rows array empty or exceeds 200 items — validation error
- Invalid date format (not YYYY-MM-DD) — schema rejection
- present_fields or expected_fields outside allowed numeric range — validation error
- Invalid method enum value (not zero/mean/median) — rejection
- Invalid field enum value — rejection
- Missing required fields (row_id, site_group, date) — schema error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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