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Data Collection Completeness — String Normalisation + Daily Sum Series
x402
Data Collection Completeness — String Normalisation + Daily Sum Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-06).
Runs string normalisation and daily sum series analysis on up to 200 data collection completeness records (observed_values, expected_values), returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data collection completeness — String normalisation + Daily sum series: String normalisation + Daily sum series for supplied data collection completeness records (observed_values, expected_values). 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
Two independent analytical reports per call: (1) a string normalisation report processing the string fields in the supplied rows, and (2) a daily sum series report aggregating the selected numeric field (observed_values or expected_values) by date — both computed locally without external lookups or predictions, covering up to 200 input rows.
Example use cases
Daily completeness totals for course groups
“I have completeness records for two course groups over the past month — each row has a date, observed_values, and expected_values. Can you compute the daily sum series on observed_values and also normalize the strings so I can see how totals accumulate day by day across groups?”
Audit observed vs expected data coverage
“We track data collection completeness for our education platform across multiple course groups. Can you run string normalisation plus a daily sum series on these 80 rows of observed and expected values so I can audit which days had gaps?”
Aggregate completeness metrics for reporting
“I need two analytical reports on this dataset of 150 completeness records — string normalisation and a daily sum series on the expected_values field — to include in our weekly data quality report for course group A and B.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-22-027?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both string normalisation and daily sum series analytics in a single low-cost call on data collection completeness records (observed vs expected values) segmented by course group and date, with no need for live data lookup or external predictions. Ideal for education or monitoring pipelines that batch up to 200 rows and want two complementary reports for $0.01.
Side effects
- More than 200 rows submitted — request rejected or truncated
- Missing required fields (row_id, date, observed_values, expected_values) cause validation errors
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Numeric values outside ±1,000,000,000,000 range rejected
- Empty rows array returns an error
- Payment of 0.01 USDC not completed blocks the response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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