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Reading Activity String Normalisation & Secondary-Measure Weighted Mean
x402
Reading Activity 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 2026-11-02).
Performs string normalisation and secondary-measure weighted mean analysis on reading activity records (pages_read, reading_minutes) for up to 200 rows, returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Reading activity — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean for supplied reading activity records (pages_read, reading_minutes). 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: (1) a string normalisation report cleaning course_group and related text fields, and (2) a secondary-measure weighted mean report for the selected numeric field (pages_read or reading_minutes), computed across up to 200 supplied reading activity rows. No live lookup or external data is involved.
Example use cases
Course group reading comparison
“I have 120 reading session records with course_group, pages_read, and reading_minutes for each student. Can you normalise the course group strings and compute the weighted mean of pages_read weighted by reading_minutes across all groups?”
Educator weekly reading digest
“Here are 80 rows of weekly reading logs with row IDs, dates, course groups, pages read, and reading minutes. Please normalise the text fields and give me a weighted mean report using reading_minutes as the field — I need two summary reports for my dashboard.”
Data quality cleanup for reading tracker
“Our reading tracker has inconsistent course group labels across 200 rows. Can you run string normalisation on the course_group field and also compute a secondary-measure weighted mean on pages_read so I can see clean, comparable averages?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-04-034?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have reading activity tabular data (up to 200 rows) that needs both text/string normalisation of course group labels and a weighted mean computed across a secondary numeric measure (pages_read or reading_minutes). It is purpose-built for education analytics on supplied local data, requiring no external lookups, and delivers two reports for $0.01 USDC — making it cost-effective for lightweight batch analysis of student reading logs.
Side effects
- More than 200 rows submitted — request rejected or truncated
- Missing required fields (row_id, date, pages_read, reading_minutes, course_group) — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Null values in both numeric fields preventing weighted mean computation
- Field enum value not in ['pages_read','reading_minutes'] — invalid input error
- Empty rows array — minimum 1 item not satisfied
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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