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Sampling Observations — Record Quality Audit + Trailing Mean Series
x402
Sampling Observations — 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 2026-10-24).
Runs two analytical reports on up to 200 sampling observation rows: a record quality audit and a trailing mean series computation over sample_value or sample_weight.
Price / call$0.01
Success—
StatusUnknown
How this service works
Sampling observations — Record quality audit + Trailing mean series: Record quality audit + Trailing mean series for supplied sampling observations records (sample_value, sample_weight). 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 issues such as missing values, anomalies, or malformed entries across the supplied rows, and (2) a trailing mean series computed over the selected field (sample_value or sample_weight) using the specified rolling window size — both generated locally without external lookups.
Example use cases
Survey sample quality check
“I have 120 rows of survey sampling data with sample_value and sample_weight fields across two groups — can you run a quality audit to flag any bad records, and also compute a trailing mean series with a window of 5 over sample_value?”
Weighted sample trend analysis
“Run a trailing mean series with a window size of 4 on sample_weight for my 80-row sampling dataset grouped by 'batch-A' and 'batch-B', and also give me a quality audit of the records at the same time.”
Clinical trial observation review
“I've got 40 clinical trial sampling observations for two patient groups from September 2026 — please audit the record quality and compute a trailing mean (window of 2) on the sample_value field so I can spot any anomalies.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-15-010?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a data quality audit and a rolling mean time series in a single API call for up to 200 sampling observation records. It is ideal when you have weighted sample data organized by group and date and want offline/local computation without external data lookups or predictions. The bundled two-report format makes it cost-efficient compared to calling separate audit and trend endpoints.
Side effects
- More than 200 rows submitted — request rejected with validation error
- window size larger than number of submitted rows — may produce empty or insufficient series
- Missing required fields (row_id, date, sample_value, sample_weight, dataset_group) — validation error
- Date strings not matching YYYY-MM-DD pattern — schema validation failure
- Numeric values outside ±1,000,000,000,000 range — rejected by schema
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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