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Data Catalog Coverage — Record Quality Audit + Trailing Mean Series
x402
Data Catalog Coverage — Record Quality Audit + Trailing Mean 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 local analytical reports on data catalog coverage records: a record quality audit and a trailing mean series for documented_fields or total_fields across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data catalog coverage — Record quality audit + Trailing mean series: Record quality audit + Trailing mean 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 that evaluates each supplied catalog coverage record based on documented_fields and total_fields, and (2) a trailing mean series that smooths the selected field (documented_fields or total_fields) over the specified rolling window. All computation is performed locally with no external lookups or predictions.
Example use cases
Catalog documentation completeness audit
“I want to audit the quality of my data catalog records — I have up to 150 rows each with a row_id, dataset_group, date, documented_fields, and total_fields. Can you run a record quality audit on them using documented_fields and also give me a trailing mean series with a window of 5?”
Smoothed field coverage trend for reporting
“Can you compute a trailing mean series over our total_fields metric across our catalog groups? I have 80 rows of catalog coverage data with dates and group labels — use a window of 10 so I can spot coverage trends over time.”
Flagging under-documented dataset groups
“I need to identify which dataset groups in our catalog have poor field documentation. Run a record quality audit on my 60 catalog coverage rows — each has row_id, dataset_group, date, documented_fields, and total_fields — and include the trailing mean for documented_fields with window size 4.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-21-010?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two simultaneous local analytical reports — a quality audit and a rolling mean series — on data catalog coverage records, without any external data lookup or prediction. It is ideal for governance workflows where you want to assess field documentation completeness and smooth coverage trends over time in a single paid call. Prefer this over generic stats tools when working specifically with documented_fields and total_fields catalog metrics.
Side effects
- Fewer than 1 row supplied — minimum 1 row required
- More than 200 rows supplied — exceeds maxItems limit
- Missing required fields (row_id, dataset_group, date, documented_fields, total_fields) on any row
- Date values not matching YYYY-MM-DD pattern
- Window value outside allowed range of 2–200
- Invalid field enum value — must be 'documented_fields' or 'total_fields'
- Null numeric values may affect trailing mean computation quality
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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