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Local Event Calendars — Record Quality Audit + String Normalisation + Secondary-Measure Weighted Mean
x402
Local Event Calendars — Record Quality Audit + String Normalisation + Secondary-Measure Weighted Mean 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).
Audits record quality, normalises strings, and computes a secondary-measure weighted mean for up to 200 rows of local event calendar data (listed_events, updated_events) in three bundled analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Local event calendars — Record quality audit + String normalisation + Secondary-measure weighted mean: Record quality audit + String normalisation + Secondary-measure weighted mean for supplied local event calendars records (listed_events, updated_events). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Returns three analytical reports for the submitted rows: (1) a record quality audit flagging issues such as missing values, invalid formats, or out-of-range numbers; (2) a string normalisation report standardising text fields like channel_group; and (3) a secondary-measure weighted mean computed for the selected field (listed_events or updated_events) across the supplied rows. All processing is local with no external lookups.
Example use cases
Monthly event listing quality check
“I have 50 rows of local event calendar entries with listed_events and updated_events counts per channel group — can you run a quality audit, normalise the strings, and give me a weighted mean for listed_events across all of them?”
Channel group data cleanup before reporting
“Before I send this month's event calendar report, can you audit the record quality and normalise the channel group strings in my 120 rows of event data, and also compute the secondary-measure weighted mean for updated_events?”
Detecting anomalies in event update rates
“I want to check data integrity for 80 rows of local event calendar records across different channel groups — please run the record quality audit and string normalisation, and calculate the weighted mean for the updated_events field so I can spot any unusual patterns.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-news-19-205?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled analytical reports — record quality audit, string normalisation, and secondary-measure weighted mean — on local event calendar data (listed_events, updated_events) in a single low-cost call. It is ideal for batch data quality checks on up to 200 rows without any need for live lookups or external data enrichment. Prefer it over single-report endpoints when all three analyses are needed simultaneously to save cost and round-trips.
Side effects
- Submitting more than 200 rows returns an error (maxItems exceeded)
- Missing required fields (row_id, date, channel_group, listed_events, updated_events) causes validation failure
- Invalid date format (not YYYY-MM-DD) triggers schema rejection
- Numeric values outside ±1,000,000,000,000 range are rejected
- Invalid field enum value (anything other than listed_events or updated_events) causes an error
- Empty rows array (minItems=1 not met) returns a validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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