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Data Catalog Coverage — Record Quality Audit & Base-100 Series
x402
Data Catalog Coverage — Record Quality Audit & Base-100 Series 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 analytical reports (record quality audit and base-100 index series) on supplied data catalog coverage rows, analyzing documented_fields vs total_fields ratios for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data catalog coverage — Record quality audit + Base-100 series: Record quality audit + Base-100 series 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
Returns two independent analytical reports: (1) a record quality audit identifying coverage issues and anomalies across the supplied rows based on documented_fields and total_fields, and (2) a base-100 normalized index series anchored at the specified base row, showing relative field documentation coverage over time. No external data is fetched; all analysis uses local analytical engines on the supplied rows only.
Example use cases
Monthly documentation coverage audit
“I want to audit our data catalog for October 2026 — I have 5 dataset groups with their documented_fields and total_fields counts per day. Can you run a record quality audit and base-100 index series on those rows using documented_fields as the metric and row 0 as the base index?”
Benchmarking catalog completeness across teams
“We have two teams — platform and analytics — each with their own dataset groups and varying field documentation rates. Can you run a quality audit and base-100 coverage series across all 12 rows (6 per team) using total_fields as the series field, starting the base index at row 0?”
Spotting underdocumented dataset groups
“I suspect some of our dataset groups have really poor field documentation. Can you do a record quality audit on these 20 catalog coverage rows I have, covering groups A through E from last quarter, with documented_fields and total_fields filled in, so I can see which groups are failing?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-21-012?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular data catalog coverage records with documented_fields and total_fields counts and need both a quality audit and a normalized base-100 trend series in a single call, without requiring external lookups or live data. It is especially suitable for batch analysis of up to 200 rows in data governance workflows where you want two complementary analytical views — absolute quality scoring and relative indexed trends — computed locally and cheaply at $0.01 per call.
Side effects
- Fewer than 1 row supplied — minimum 1 row required
- More than 200 rows supplied — hard limit of 200 rows per call
- Invalid date format — must match YYYY-MM-DD pattern
- Missing required fields (row_id, dataset_group, date, documented_fields, total_fields) on any row
- base_index out of range — must be 0–199 and within the actual row count
- Numeric fields outside allowed range (±1,000,000,000,000)
- Invalid field enum value — must be 'documented_fields' or 'total_fields'
- Payment not included or insufficient — requires 0.01 USDC via x402
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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