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Data Catalog Coverage — String Normalisation + Adjacent Row Changes
x402
Data Catalog Coverage — String Normalisation + Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).
Runs two local analytical reports on data catalog coverage records: string normalisation and adjacent row change detection for up to 200 rows of documented_fields or total_fields data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data catalog coverage — String normalisation + Adjacent row changes: String normalisation + Adjacent row changes for supplied data catalog coverage records (documented_fields, total_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: (1) a string normalisation output showing standardised/cleaned string values for the selected field across supplied rows, and (2) an adjacent row change report showing differences between consecutive rows for the chosen numeric field (documented_fields or total_fields), all computed locally without external lookups.
Example use cases
Audit catalog field documentation gaps
“I have 150 dataset catalog records with documented_fields and total_fields counts by date and group — can you normalise the strings and flag wherever adjacent rows show big jumps in documented_fields coverage?”
Spot sudden drops in total fields
“Run the adjacent row change report on my catalog coverage data (up to 80 rows, groups: finance, ops, hr, dated this quarter) using the total_fields column so I can see where field counts dropped unexpectedly between days.”
Standardise catalog group name strings
“My data catalog export has messy group name strings across 60 rows — please run the string normalisation report on these coverage records for documented_fields so everything is consistently formatted before I merge the datasets.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-21-029?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, local string normalisation and adjacent-row change detection on small-to-medium data catalog coverage datasets (up to 200 rows) without any external data lookup, prediction, or live enrichment. It is ideal for data governance workflows where you want to audit catalog completeness metrics and clean string inconsistencies in a single low-cost call.
Side effects
- Fewer than 1 row supplied — request rejected (minItems: 1)
- More than 200 rows supplied — request rejected (maxItems: 200)
- Missing required fields (row_id, dataset_group, date, documented_fields, total_fields) — validation error
- Invalid date format (must match YYYY-MM-DD pattern) — schema validation failure
- Numeric field values outside allowed range (-1e12 to 1e12) — validation error
- Invalid field enum value (must be documented_fields or total_fields) — rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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