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Data Freshness Record Quality Audit + Numeric Distribution
x402
Data Freshness Record Quality Audit + Numeric Distribution is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Runs two local analytical reports — a record quality audit and a numeric distribution analysis — on up to 200 supplied data freshness rows containing age_minutes and record_count fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data freshness — Record quality audit + Numeric distribution: Record quality audit + Numeric distribution for supplied data freshness records (age_minutes, record_count). 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 highlighting issues such as nulls, out-of-range values, and anomalies in the supplied rows, and (2) a numeric distribution summary (e.g. min, max, mean, percentiles, histogram bins) for the selected numeric field (age_minutes or record_count). Both reports are computed locally from the supplied data with no external lookups.
Example use cases
Pipeline freshness quality audit
“I have a batch of 80 data freshness records from my ETL pipeline — each row has a date, dataset group, age_minutes, and record_count. Can you run a record quality audit and show me a numeric distribution of the age_minutes values so I can spot any stale or bad records?”
Record count distribution profiling
“Can you analyze these 120 data freshness rows and give me a quality audit plus a numeric distribution of the record_count field? I want to understand the spread and flag any problematic rows across my dataset groups.”
Data freshness monitoring check
“Here are 40 freshness tracking rows from our monitoring system, each with a row_id, date, dataset_group, age_minutes, and record_count. Please run both a record quality audit and a numeric distribution on age_minutes so I can see where data freshness is degrading.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-06-004?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have a batch of up to 200 data freshness records and need two quick analytical outputs — a record quality audit and a numeric distribution — without requiring any external data lookup, live API, or prediction. It is best suited for offline profiling of freshness monitoring data (age_minutes, record_count) grouped by dataset and date. Prefer it over general-purpose analytics when you specifically want these two combined report types at low cost ($0.01 USDC for both).
Side effects
- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — exceeds maximum row limit
- Missing required fields (row_id, dataset_group, date, age_minutes, record_count) in any row — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- field parameter not one of 'age_minutes' or 'record_count' — enum validation error
- Numeric values outside allowed range (-1000000000000 to 1000000000000) — rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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